Ex5
Araê Cainã e Gustavo Martins
06/07/2021
Abre banco
- Faça o dwonload do arquivo de http://www.labape.com.br/rprimi/TRI/2019_slides_exerc/enem_2015.RData
load("enem_2015.RData")- Bibliotecas
library(TAM)
library(tidyverse)
library(mirt)
library(skimr)
library(sjmisc)
library(CDM)
library(psych)
library(ggplot2)Calibrando o modelo de Rasch
score_ch2 <- score_ch %>% slice_sample(n = 20000)
rownames(score_ch2)## [1] "1" "2" "3" "4" "5" "6" "7" "8" "9"
## [10] "10" "11" "12" "13" "14" "15" "16" "17" "18"
## [19] "19" "20" "21" "22" "23" "24" "25" "26" "27"
## [28] "28" "29" "30" "31" "32" "33" "34" "35" "36"
## [37] "37" "38" "39" "40" "41" "42" "43" "44" "45"
## [46] "46" "47" "48" "49" "50" "51" "52" "53" "54"
## [55] "55" "56" "57" "58" "59" "60" "61" "62" "63"
## [64] "64" "65" "66" "67" "68" "69" "70" "71" "72"
## [73] "73" "74" "75" "76" "77" "78" "79" "80" "81"
## [82] "82" "83" "84" "85" "86" "87" "88" "89" "90"
## [91] "91" "92" "93" "94" "95" "96" "97" "98" "99"
## [100] "100" "101" "102" "103" "104" "105" "106" "107" "108"
## [109] "109" "110" "111" "112" "113" "114" "115" "116" "117"
## [118] "118" "119" "120" "121" "122" "123" "124" "125" "126"
## [127] "127" "128" "129" "130" "131" "132" "133" "134" "135"
## [136] "136" "137" "138" "139" "140" "141" "142" "143" "144"
## [145] "145" "146" "147" "148" "149" "150" "151" "152" "153"
## [154] "154" "155" "156" "157" "158" "159" "160" "161" "162"
## [163] "163" "164" "165" "166" "167" "168" "169" "170" "171"
## [172] "172" "173" "174" "175" "176" "177" "178" "179" "180"
## [181] "181" "182" "183" "184" "185" "186" "187" "188" "189"
## [190] "190" "191" "192" "193" "194" "195" "196" "197" "198"
## [199] "199" "200" "201" "202" "203" "204" "205" "206" "207"
## [208] "208" "209" "210" "211" "212" "213" "214" "215" "216"
## [217] "217" "218" "219" "220" "221" "222" "223" "224" "225"
## [226] "226" "227" "228" "229" "230" "231" "232" "233" "234"
## [235] "235" "236" "237" "238" "239" "240" "241" "242" "243"
## [244] "244" "245" "246" "247" "248" "249" "250" "251" "252"
## [253] "253" "254" "255" "256" "257" "258" "259" "260" "261"
## [262] "262" "263" "264" "265" "266" "267" "268" "269" "270"
## [271] "271" "272" "273" "274" "275" "276" "277" "278" "279"
## [280] "280" "281" "282" "283" "284" "285" "286" "287" "288"
## [289] "289" "290" "291" "292" "293" "294" "295" "296" "297"
## [298] "298" "299" "300" "301" "302" "303" "304" "305" "306"
## [307] "307" "308" "309" "310" "311" "312" "313" "314" "315"
## [316] "316" "317" "318" "319" "320" "321" "322" "323" "324"
## [325] "325" "326" "327" "328" "329" "330" "331" "332" "333"
## [334] "334" "335" "336" "337" "338" "339" "340" "341" "342"
## [343] "343" "344" "345" "346" "347" "348" "349" "350" "351"
## [352] "352" "353" "354" "355" "356" "357" "358" "359" "360"
## [361] "361" "362" "363" "364" "365" "366" "367" "368" "369"
## [370] "370" "371" "372" "373" "374" "375" "376" "377" "378"
## [379] "379" "380" "381" "382" "383" "384" "385" "386" "387"
## [388] "388" "389" "390" "391" "392" "393" "394" "395" "396"
## [397] "397" "398" "399" "400" "401" "402" "403" "404" "405"
## [406] "406" "407" "408" "409" "410" "411" "412" "413" "414"
## [415] "415" "416" "417" "418" "419" "420" "421" "422" "423"
## [424] "424" "425" "426" "427" "428" "429" "430" "431" "432"
## [433] "433" "434" "435" "436" "437" "438" "439" "440" "441"
## [442] "442" "443" "444" "445" "446" "447" "448" "449" "450"
## [451] "451" "452" "453" "454" "455" "456" "457" "458" "459"
## [460] "460" "461" "462" "463" "464" "465" "466" "467" "468"
## [469] "469" "470" "471" "472" "473" "474" "475" "476" "477"
## [478] "478" "479" "480" "481" "482" "483" "484" "485" "486"
## [487] "487" "488" "489" "490" "491" "492" "493" "494" "495"
## [496] "496" "497" "498" "499" "500" "501" "502" "503" "504"
## [505] "505" "506" "507" "508" "509" "510" "511" "512" "513"
## [514] "514" "515" "516" "517" "518" "519" "520" "521" "522"
## [523] "523" "524" "525" "526" "527" "528" "529" "530" "531"
## [532] "532" "533" "534" "535" "536" "537" "538" "539" "540"
## [541] "541" "542" "543" "544" "545" "546" "547" "548" "549"
## [550] "550" "551" "552" "553" "554" "555" "556" "557" "558"
## [559] "559" "560" "561" "562" "563" "564" "565" "566" "567"
## [568] "568" "569" "570" "571" "572" "573" "574" "575" "576"
## [577] "577" "578" "579" "580" "581" "582" "583" "584" "585"
## [586] "586" "587" "588" "589" "590" "591" "592" "593" "594"
## [595] "595" "596" "597" "598" "599" "600" "601" "602" "603"
## [604] "604" "605" "606" "607" "608" "609" "610" "611" "612"
## [613] "613" "614" "615" "616" "617" "618" "619" "620" "621"
## [622] "622" "623" "624" "625" "626" "627" "628" "629" "630"
## [631] "631" "632" "633" "634" "635" "636" "637" "638" "639"
## [640] "640" "641" "642" "643" "644" "645" "646" "647" "648"
## [649] "649" "650" "651" "652" "653" "654" "655" "656" "657"
## [658] "658" "659" "660" "661" "662" "663" "664" "665" "666"
## [667] "667" "668" "669" "670" "671" "672" "673" "674" "675"
## [676] "676" "677" "678" "679" "680" "681" "682" "683" "684"
## [685] "685" "686" "687" "688" "689" "690" "691" "692" "693"
## [694] "694" "695" "696" "697" "698" "699" "700" "701" "702"
## [703] "703" "704" "705" "706" "707" "708" "709" "710" "711"
## [712] "712" "713" "714" "715" "716" "717" "718" "719" "720"
## [721] "721" "722" "723" "724" "725" "726" "727" "728" "729"
## [730] "730" "731" "732" "733" "734" "735" "736" "737" "738"
## [739] "739" "740" "741" "742" "743" "744" "745" "746" "747"
## [748] "748" "749" "750" "751" "752" "753" "754" "755" "756"
## [757] "757" "758" "759" "760" "761" "762" "763" "764" "765"
## [766] "766" "767" "768" "769" "770" "771" "772" "773" "774"
## [775] "775" "776" "777" "778" "779" "780" "781" "782" "783"
## [784] "784" "785" "786" "787" "788" "789" "790" "791" "792"
## [793] "793" "794" "795" "796" "797" "798" "799" "800" "801"
## [802] "802" "803" "804" "805" "806" "807" "808" "809" "810"
## [811] "811" "812" "813" "814" "815" "816" "817" "818" "819"
## [820] "820" "821" "822" "823" "824" "825" "826" "827" "828"
## [829] "829" "830" "831" "832" "833" "834" "835" "836" "837"
## [838] "838" "839" "840" "841" "842" "843" "844" "845" "846"
## [847] "847" "848" "849" "850" "851" "852" "853" "854" "855"
## [856] "856" "857" "858" "859" "860" "861" "862" "863" "864"
## [865] "865" "866" "867" "868" "869" "870" "871" "872" "873"
## [874] "874" "875" "876" "877" "878" "879" "880" "881" "882"
## [883] "883" "884" "885" "886" "887" "888" "889" "890" "891"
## [892] "892" "893" "894" "895" "896" "897" "898" "899" "900"
## [901] "901" "902" "903" "904" "905" "906" "907" "908" "909"
## [910] "910" "911" "912" "913" "914" "915" "916" "917" "918"
## [919] "919" "920" "921" "922" "923" "924" "925" "926" "927"
## [928] "928" "929" "930" "931" "932" "933" "934" "935" "936"
## [937] "937" "938" "939" "940" "941" "942" "943" "944" "945"
## [946] "946" "947" "948" "949" "950" "951" "952" "953" "954"
## [955] "955" "956" "957" "958" "959" "960" "961" "962" "963"
## [964] "964" "965" "966" "967" "968" "969" "970" "971" "972"
## [973] "973" "974" "975" "976" "977" "978" "979" "980" "981"
## [982] "982" "983" "984" "985" "986" "987" "988" "989" "990"
## [991] "991" "992" "993" "994" "995" "996" "997" "998" "999"
## [1000] "1000" "1001" "1002" "1003" "1004" "1005" "1006" "1007" "1008"
## [1009] "1009" "1010" "1011" "1012" "1013" "1014" "1015" "1016" "1017"
## [1018] "1018" "1019" "1020" "1021" "1022" "1023" "1024" "1025" "1026"
## [1027] "1027" "1028" "1029" "1030" "1031" "1032" "1033" "1034" "1035"
## [1036] "1036" "1037" "1038" "1039" "1040" "1041" "1042" "1043" "1044"
## [1045] "1045" "1046" "1047" "1048" "1049" "1050" "1051" "1052" "1053"
## [1054] "1054" "1055" "1056" "1057" "1058" "1059" "1060" "1061" "1062"
## [1063] "1063" "1064" "1065" "1066" "1067" "1068" "1069" "1070" "1071"
## [1072] "1072" "1073" "1074" "1075" "1076" "1077" "1078" "1079" "1080"
## [1081] "1081" "1082" "1083" "1084" "1085" "1086" "1087" "1088" "1089"
## [1090] "1090" "1091" "1092" "1093" "1094" "1095" "1096" "1097" "1098"
## [1099] "1099" "1100" "1101" "1102" "1103" "1104" "1105" "1106" "1107"
## [1108] "1108" "1109" "1110" "1111" "1112" "1113" "1114" "1115" "1116"
## [1117] "1117" "1118" "1119" "1120" "1121" "1122" "1123" "1124" "1125"
## [1126] "1126" "1127" "1128" "1129" "1130" "1131" "1132" "1133" "1134"
## [1135] "1135" "1136" "1137" "1138" "1139" "1140" "1141" "1142" "1143"
## [1144] "1144" "1145" "1146" "1147" "1148" "1149" "1150" "1151" "1152"
## [1153] "1153" "1154" "1155" "1156" "1157" "1158" "1159" "1160" "1161"
## [1162] "1162" "1163" "1164" "1165" "1166" "1167" "1168" "1169" "1170"
## [1171] "1171" "1172" "1173" "1174" "1175" "1176" "1177" "1178" "1179"
## [1180] "1180" "1181" "1182" "1183" "1184" "1185" "1186" "1187" "1188"
## [1189] "1189" "1190" "1191" "1192" "1193" "1194" "1195" "1196" "1197"
## [1198] "1198" "1199" "1200" "1201" "1202" "1203" "1204" "1205" "1206"
## [1207] "1207" "1208" "1209" "1210" "1211" "1212" "1213" "1214" "1215"
## [1216] "1216" "1217" "1218" "1219" "1220" "1221" "1222" "1223" "1224"
## [1225] "1225" "1226" "1227" "1228" "1229" "1230" "1231" "1232" "1233"
## [1234] "1234" "1235" "1236" "1237" "1238" "1239" "1240" "1241" "1242"
## [1243] "1243" "1244" "1245" "1246" "1247" "1248" "1249" "1250" "1251"
## [1252] "1252" "1253" "1254" "1255" "1256" "1257" "1258" "1259" "1260"
## [1261] "1261" "1262" "1263" "1264" "1265" "1266" "1267" "1268" "1269"
## [1270] "1270" "1271" "1272" "1273" "1274" "1275" "1276" "1277" "1278"
## [1279] "1279" "1280" "1281" "1282" "1283" "1284" "1285" "1286" "1287"
## [1288] "1288" "1289" "1290" "1291" "1292" "1293" "1294" "1295" "1296"
## [1297] "1297" "1298" "1299" "1300" "1301" "1302" "1303" "1304" "1305"
## [1306] "1306" "1307" "1308" "1309" "1310" "1311" "1312" "1313" "1314"
## [1315] "1315" "1316" "1317" "1318" "1319" "1320" "1321" "1322" "1323"
## [1324] "1324" "1325" "1326" "1327" "1328" "1329" "1330" "1331" "1332"
## [1333] "1333" "1334" "1335" "1336" "1337" "1338" "1339" "1340" "1341"
## [1342] "1342" "1343" "1344" "1345" "1346" "1347" "1348" "1349" "1350"
## [1351] "1351" "1352" "1353" "1354" "1355" "1356" "1357" "1358" "1359"
## [1360] "1360" "1361" "1362" "1363" "1364" "1365" "1366" "1367" "1368"
## [1369] "1369" "1370" "1371" "1372" "1373" "1374" "1375" "1376" "1377"
## [1378] "1378" "1379" "1380" "1381" "1382" "1383" "1384" "1385" "1386"
## [1387] "1387" "1388" "1389" "1390" "1391" "1392" "1393" "1394" "1395"
## [1396] "1396" "1397" "1398" "1399" "1400" "1401" "1402" "1403" "1404"
## [1405] "1405" "1406" "1407" "1408" "1409" "1410" "1411" "1412" "1413"
## [1414] "1414" "1415" "1416" "1417" "1418" "1419" "1420" "1421" "1422"
## [1423] "1423" "1424" "1425" "1426" "1427" "1428" "1429" "1430" "1431"
## [1432] "1432" "1433" "1434" "1435" "1436" "1437" "1438" "1439" "1440"
## [1441] "1441" "1442" "1443" "1444" "1445" "1446" "1447" "1448" "1449"
## [1450] "1450" "1451" "1452" "1453" "1454" "1455" "1456" "1457" "1458"
## [1459] "1459" "1460" "1461" "1462" "1463" "1464" "1465" "1466" "1467"
## [1468] "1468" "1469" "1470" "1471" "1472" "1473" "1474" "1475" "1476"
## [1477] "1477" "1478" "1479" "1480" "1481" "1482" "1483" "1484" "1485"
## [1486] "1486" "1487" "1488" "1489" "1490" "1491" "1492" "1493" "1494"
## [1495] "1495" "1496" "1497" "1498" "1499" "1500" "1501" "1502" "1503"
## [1504] "1504" "1505" "1506" "1507" "1508" "1509" "1510" "1511" "1512"
## [1513] "1513" "1514" "1515" "1516" "1517" "1518" "1519" "1520" "1521"
## [1522] "1522" "1523" "1524" "1525" "1526" "1527" "1528" "1529" "1530"
## [1531] "1531" "1532" "1533" "1534" "1535" "1536" "1537" "1538" "1539"
## [1540] "1540" "1541" "1542" "1543" "1544" "1545" "1546" "1547" "1548"
## [1549] "1549" "1550" "1551" "1552" "1553" "1554" "1555" "1556" "1557"
## [1558] "1558" "1559" "1560" "1561" "1562" "1563" "1564" "1565" "1566"
## [1567] "1567" "1568" "1569" "1570" "1571" "1572" "1573" "1574" "1575"
## [1576] "1576" "1577" "1578" "1579" "1580" "1581" "1582" "1583" "1584"
## [1585] "1585" "1586" "1587" "1588" "1589" "1590" "1591" "1592" "1593"
## [1594] "1594" "1595" "1596" "1597" "1598" "1599" "1600" "1601" "1602"
## [1603] "1603" "1604" "1605" "1606" "1607" "1608" "1609" "1610" "1611"
## [1612] "1612" "1613" "1614" "1615" "1616" "1617" "1618" "1619" "1620"
## [1621] "1621" "1622" "1623" "1624" "1625" "1626" "1627" "1628" "1629"
## [1630] "1630" "1631" "1632" "1633" "1634" "1635" "1636" "1637" "1638"
## [1639] "1639" "1640" "1641" "1642" "1643" "1644" "1645" "1646" "1647"
## [1648] "1648" "1649" "1650" "1651" "1652" "1653" "1654" "1655" "1656"
## [1657] "1657" "1658" "1659" "1660" "1661" "1662" "1663" "1664" "1665"
## [1666] "1666" "1667" "1668" "1669" "1670" "1671" "1672" "1673" "1674"
## [1675] "1675" "1676" "1677" "1678" "1679" "1680" "1681" "1682" "1683"
## [1684] "1684" "1685" "1686" "1687" "1688" "1689" "1690" "1691" "1692"
## [1693] "1693" "1694" "1695" "1696" "1697" "1698" "1699" "1700" "1701"
## [1702] "1702" "1703" "1704" "1705" "1706" "1707" "1708" "1709" "1710"
## [1711] "1711" "1712" "1713" "1714" "1715" "1716" "1717" "1718" "1719"
## [1720] "1720" "1721" "1722" "1723" "1724" "1725" "1726" "1727" "1728"
## [1729] "1729" "1730" "1731" "1732" "1733" "1734" "1735" "1736" "1737"
## [1738] "1738" "1739" "1740" "1741" "1742" "1743" "1744" "1745" "1746"
## [1747] "1747" "1748" "1749" "1750" "1751" "1752" "1753" "1754" "1755"
## [1756] "1756" "1757" "1758" "1759" "1760" "1761" "1762" "1763" "1764"
## [1765] "1765" "1766" "1767" "1768" "1769" "1770" "1771" "1772" "1773"
## [1774] "1774" "1775" "1776" "1777" "1778" "1779" "1780" "1781" "1782"
## [1783] "1783" "1784" "1785" "1786" "1787" "1788" "1789" "1790" "1791"
## [1792] "1792" "1793" "1794" "1795" "1796" "1797" "1798" "1799" "1800"
## [1801] "1801" "1802" "1803" "1804" "1805" "1806" "1807" "1808" "1809"
## [1810] "1810" "1811" "1812" "1813" "1814" "1815" "1816" "1817" "1818"
## [1819] "1819" "1820" "1821" "1822" "1823" "1824" "1825" "1826" "1827"
## [1828] "1828" "1829" "1830" "1831" "1832" "1833" "1834" "1835" "1836"
## [1837] "1837" "1838" "1839" "1840" "1841" "1842" "1843" "1844" "1845"
## [1846] "1846" "1847" "1848" "1849" "1850" "1851" "1852" "1853" "1854"
## [1855] "1855" "1856" "1857" "1858" "1859" "1860" "1861" "1862" "1863"
## [1864] "1864" "1865" "1866" "1867" "1868" "1869" "1870" "1871" "1872"
## [1873] "1873" "1874" "1875" "1876" "1877" "1878" "1879" "1880" "1881"
## [1882] "1882" "1883" "1884" "1885" "1886" "1887" "1888" "1889" "1890"
## [1891] "1891" "1892" "1893" "1894" "1895" "1896" "1897" "1898" "1899"
## [1900] "1900" "1901" "1902" "1903" "1904" "1905" "1906" "1907" "1908"
## [1909] "1909" "1910" "1911" "1912" "1913" "1914" "1915" "1916" "1917"
## [1918] "1918" "1919" "1920" "1921" "1922" "1923" "1924" "1925" "1926"
## [1927] "1927" "1928" "1929" "1930" "1931" "1932" "1933" "1934" "1935"
## [1936] "1936" "1937" "1938" "1939" "1940" "1941" "1942" "1943" "1944"
## [1945] "1945" "1946" "1947" "1948" "1949" "1950" "1951" "1952" "1953"
## [1954] "1954" "1955" "1956" "1957" "1958" "1959" "1960" "1961" "1962"
## [1963] "1963" "1964" "1965" "1966" "1967" "1968" "1969" "1970" "1971"
## [1972] "1972" "1973" "1974" "1975" "1976" "1977" "1978" "1979" "1980"
## [1981] "1981" "1982" "1983" "1984" "1985" "1986" "1987" "1988" "1989"
## [1990] "1990" "1991" "1992" "1993" "1994" "1995" "1996" "1997" "1998"
## [1999] "1999" "2000" "2001" "2002" "2003" "2004" "2005" "2006" "2007"
## [2008] "2008" "2009" "2010" "2011" "2012" "2013" "2014" "2015" "2016"
## [2017] "2017" "2018" "2019" "2020" "2021" "2022" "2023" "2024" "2025"
## [2026] "2026" "2027" "2028" "2029" "2030" "2031" "2032" "2033" "2034"
## [2035] "2035" "2036" "2037" "2038" "2039" "2040" "2041" "2042" "2043"
## [2044] "2044" "2045" "2046" "2047" "2048" "2049" "2050" "2051" "2052"
## [2053] "2053" "2054" "2055" "2056" "2057" "2058" "2059" "2060" "2061"
## [2062] "2062" "2063" "2064" "2065" "2066" "2067" "2068" "2069" "2070"
## [2071] "2071" "2072" "2073" "2074" "2075" "2076" "2077" "2078" "2079"
## [2080] "2080" "2081" "2082" "2083" "2084" "2085" "2086" "2087" "2088"
## [2089] "2089" "2090" "2091" "2092" "2093" "2094" "2095" "2096" "2097"
## [2098] "2098" "2099" "2100" "2101" "2102" "2103" "2104" "2105" "2106"
## [2107] "2107" "2108" "2109" "2110" "2111" "2112" "2113" "2114" "2115"
## [2116] "2116" "2117" "2118" "2119" "2120" "2121" "2122" "2123" "2124"
## [2125] "2125" "2126" "2127" "2128" "2129" "2130" "2131" "2132" "2133"
## [2134] "2134" "2135" "2136" "2137" "2138" "2139" "2140" "2141" "2142"
## [2143] "2143" "2144" "2145" "2146" "2147" "2148" "2149" "2150" "2151"
## [2152] "2152" "2153" "2154" "2155" "2156" "2157" "2158" "2159" "2160"
## [2161] "2161" "2162" "2163" "2164" "2165" "2166" "2167" "2168" "2169"
## [2170] "2170" "2171" "2172" "2173" "2174" "2175" "2176" "2177" "2178"
## [2179] "2179" "2180" "2181" "2182" "2183" "2184" "2185" "2186" "2187"
## [2188] "2188" "2189" "2190" "2191" "2192" "2193" "2194" "2195" "2196"
## [2197] "2197" "2198" "2199" "2200" "2201" "2202" "2203" "2204" "2205"
## [2206] "2206" "2207" "2208" "2209" "2210" "2211" "2212" "2213" "2214"
## [2215] "2215" "2216" "2217" "2218" "2219" "2220" "2221" "2222" "2223"
## [2224] "2224" "2225" "2226" "2227" "2228" "2229" "2230" "2231" "2232"
## [2233] "2233" "2234" "2235" "2236" "2237" "2238" "2239" "2240" "2241"
## [2242] "2242" "2243" "2244" "2245" "2246" "2247" "2248" "2249" "2250"
## [2251] "2251" "2252" "2253" "2254" "2255" "2256" "2257" "2258" "2259"
## [2260] "2260" "2261" "2262" "2263" "2264" "2265" "2266" "2267" "2268"
## [2269] "2269" "2270" "2271" "2272" "2273" "2274" "2275" "2276" "2277"
## [2278] "2278" "2279" "2280" "2281" "2282" "2283" "2284" "2285" "2286"
## [2287] "2287" "2288" "2289" "2290" "2291" "2292" "2293" "2294" "2295"
## [2296] "2296" "2297" "2298" "2299" "2300" "2301" "2302" "2303" "2304"
## [2305] "2305" "2306" "2307" "2308" "2309" "2310" "2311" "2312" "2313"
## [2314] "2314" "2315" "2316" "2317" "2318" "2319" "2320" "2321" "2322"
## [2323] "2323" "2324" "2325" "2326" "2327" "2328" "2329" "2330" "2331"
## [2332] "2332" "2333" "2334" "2335" "2336" "2337" "2338" "2339" "2340"
## [2341] "2341" "2342" "2343" "2344" "2345" "2346" "2347" "2348" "2349"
## [2350] "2350" "2351" "2352" "2353" "2354" "2355" "2356" "2357" "2358"
## [2359] "2359" "2360" "2361" "2362" "2363" "2364" "2365" "2366" "2367"
## [2368] "2368" "2369" "2370" "2371" "2372" "2373" "2374" "2375" "2376"
## [2377] "2377" "2378" "2379" "2380" "2381" "2382" "2383" "2384" "2385"
## [2386] "2386" "2387" "2388" "2389" "2390" "2391" "2392" "2393" "2394"
## [2395] "2395" "2396" "2397" "2398" "2399" "2400" "2401" "2402" "2403"
## [2404] "2404" "2405" "2406" "2407" "2408" "2409" "2410" "2411" "2412"
## [2413] "2413" "2414" "2415" "2416" "2417" "2418" "2419" "2420" "2421"
## [2422] "2422" "2423" "2424" "2425" "2426" "2427" "2428" "2429" "2430"
## [2431] "2431" "2432" "2433" "2434" "2435" "2436" "2437" "2438" "2439"
## [2440] "2440" "2441" "2442" "2443" "2444" "2445" "2446" "2447" "2448"
## [2449] "2449" "2450" "2451" "2452" "2453" "2454" "2455" "2456" "2457"
## [2458] "2458" "2459" "2460" "2461" "2462" "2463" "2464" "2465" "2466"
## [2467] "2467" "2468" "2469" "2470" "2471" "2472" "2473" "2474" "2475"
## [2476] "2476" "2477" "2478" "2479" "2480" "2481" "2482" "2483" "2484"
## [2485] "2485" "2486" "2487" "2488" "2489" "2490" "2491" "2492" "2493"
## [2494] "2494" "2495" "2496" "2497" "2498" "2499" "2500" "2501" "2502"
## [2503] "2503" "2504" "2505" "2506" "2507" "2508" "2509" "2510" "2511"
## [2512] "2512" "2513" "2514" "2515" "2516" "2517" "2518" "2519" "2520"
## [2521] "2521" "2522" "2523" "2524" "2525" "2526" "2527" "2528" "2529"
## [2530] "2530" "2531" "2532" "2533" "2534" "2535" "2536" "2537" "2538"
## [2539] "2539" "2540" "2541" "2542" "2543" "2544" "2545" "2546" "2547"
## [2548] "2548" "2549" "2550" "2551" "2552" "2553" "2554" "2555" "2556"
## [2557] "2557" "2558" "2559" "2560" "2561" "2562" "2563" "2564" "2565"
## [2566] "2566" "2567" "2568" "2569" "2570" "2571" "2572" "2573" "2574"
## [2575] "2575" "2576" "2577" "2578" "2579" "2580" "2581" "2582" "2583"
## [2584] "2584" "2585" "2586" "2587" "2588" "2589" "2590" "2591" "2592"
## [2593] "2593" "2594" "2595" "2596" "2597" "2598" "2599" "2600" "2601"
## [2602] "2602" "2603" "2604" "2605" "2606" "2607" "2608" "2609" "2610"
## [2611] "2611" "2612" "2613" "2614" "2615" "2616" "2617" "2618" "2619"
## [2620] "2620" "2621" "2622" "2623" "2624" "2625" "2626" "2627" "2628"
## [2629] "2629" "2630" "2631" "2632" "2633" "2634" "2635" "2636" "2637"
## [2638] "2638" "2639" "2640" "2641" "2642" "2643" "2644" "2645" "2646"
## [2647] "2647" "2648" "2649" "2650" "2651" "2652" "2653" "2654" "2655"
## [2656] "2656" "2657" "2658" "2659" "2660" "2661" "2662" "2663" "2664"
## [2665] "2665" "2666" "2667" "2668" "2669" "2670" "2671" "2672" "2673"
## [2674] "2674" "2675" "2676" "2677" "2678" "2679" "2680" "2681" "2682"
## [2683] "2683" "2684" "2685" "2686" "2687" "2688" "2689" "2690" "2691"
## [2692] "2692" "2693" "2694" "2695" "2696" "2697" "2698" "2699" "2700"
## [2701] "2701" "2702" "2703" "2704" "2705" "2706" "2707" "2708" "2709"
## [2710] "2710" "2711" "2712" "2713" "2714" "2715" "2716" "2717" "2718"
## [2719] "2719" "2720" "2721" "2722" "2723" "2724" "2725" "2726" "2727"
## [2728] "2728" "2729" "2730" "2731" "2732" "2733" "2734" "2735" "2736"
## [2737] "2737" "2738" "2739" "2740" "2741" "2742" "2743" "2744" "2745"
## [2746] "2746" "2747" "2748" "2749" "2750" "2751" "2752" "2753" "2754"
## [2755] "2755" "2756" "2757" "2758" "2759" "2760" "2761" "2762" "2763"
## [2764] "2764" "2765" "2766" "2767" "2768" "2769" "2770" "2771" "2772"
## [2773] "2773" "2774" "2775" "2776" "2777" "2778" "2779" "2780" "2781"
## [2782] "2782" "2783" "2784" "2785" "2786" "2787" "2788" "2789" "2790"
## [2791] "2791" "2792" "2793" "2794" "2795" "2796" "2797" "2798" "2799"
## [2800] "2800" "2801" "2802" "2803" "2804" "2805" "2806" "2807" "2808"
## [2809] "2809" "2810" "2811" "2812" "2813" "2814" "2815" "2816" "2817"
## [2818] "2818" "2819" "2820" "2821" "2822" "2823" "2824" "2825" "2826"
## [2827] "2827" "2828" "2829" "2830" "2831" "2832" "2833" "2834" "2835"
## [2836] "2836" "2837" "2838" "2839" "2840" "2841" "2842" "2843" "2844"
## [2845] "2845" "2846" "2847" "2848" "2849" "2850" "2851" "2852" "2853"
## [2854] "2854" "2855" "2856" "2857" "2858" "2859" "2860" "2861" "2862"
## [2863] "2863" "2864" "2865" "2866" "2867" "2868" "2869" "2870" "2871"
## [2872] "2872" "2873" "2874" "2875" "2876" "2877" "2878" "2879" "2880"
## [2881] "2881" "2882" "2883" "2884" "2885" "2886" "2887" "2888" "2889"
## [2890] "2890" "2891" "2892" "2893" "2894" "2895" "2896" "2897" "2898"
## [2899] "2899" "2900" "2901" "2902" "2903" "2904" "2905" "2906" "2907"
## [2908] "2908" "2909" "2910" "2911" "2912" "2913" "2914" "2915" "2916"
## [2917] "2917" "2918" "2919" "2920" "2921" "2922" "2923" "2924" "2925"
## [2926] "2926" "2927" "2928" "2929" "2930" "2931" "2932" "2933" "2934"
## [2935] "2935" "2936" "2937" "2938" "2939" "2940" "2941" "2942" "2943"
## [2944] "2944" "2945" "2946" "2947" "2948" "2949" "2950" "2951" "2952"
## [2953] "2953" "2954" "2955" "2956" "2957" "2958" "2959" "2960" "2961"
## [2962] "2962" "2963" "2964" "2965" "2966" "2967" "2968" "2969" "2970"
## [2971] "2971" "2972" "2973" "2974" "2975" "2976" "2977" "2978" "2979"
## [2980] "2980" "2981" "2982" "2983" "2984" "2985" "2986" "2987" "2988"
## [2989] "2989" "2990" "2991" "2992" "2993" "2994" "2995" "2996" "2997"
## [2998] "2998" "2999" "3000" "3001" "3002" "3003" "3004" "3005" "3006"
## [3007] "3007" "3008" "3009" "3010" "3011" "3012" "3013" "3014" "3015"
## [3016] "3016" "3017" "3018" "3019" "3020" "3021" "3022" "3023" "3024"
## [3025] "3025" "3026" "3027" "3028" "3029" "3030" "3031" "3032" "3033"
## [3034] "3034" "3035" "3036" "3037" "3038" "3039" "3040" "3041" "3042"
## [3043] "3043" "3044" "3045" "3046" "3047" "3048" "3049" "3050" "3051"
## [3052] "3052" "3053" "3054" "3055" "3056" "3057" "3058" "3059" "3060"
## [3061] "3061" "3062" "3063" "3064" "3065" "3066" "3067" "3068" "3069"
## [3070] "3070" "3071" "3072" "3073" "3074" "3075" "3076" "3077" "3078"
## [3079] "3079" "3080" "3081" "3082" "3083" "3084" "3085" "3086" "3087"
## [3088] "3088" "3089" "3090" "3091" "3092" "3093" "3094" "3095" "3096"
## [3097] "3097" "3098" "3099" "3100" "3101" "3102" "3103" "3104" "3105"
## [3106] "3106" "3107" "3108" "3109" "3110" "3111" "3112" "3113" "3114"
## [3115] "3115" "3116" "3117" "3118" "3119" "3120" "3121" "3122" "3123"
## [3124] "3124" "3125" "3126" "3127" "3128" "3129" "3130" "3131" "3132"
## [3133] "3133" "3134" "3135" "3136" "3137" "3138" "3139" "3140" "3141"
## [3142] "3142" "3143" "3144" "3145" "3146" "3147" "3148" "3149" "3150"
## [3151] "3151" "3152" "3153" "3154" "3155" "3156" "3157" "3158" "3159"
## [3160] "3160" "3161" "3162" "3163" "3164" "3165" "3166" "3167" "3168"
## [3169] "3169" "3170" "3171" "3172" "3173" "3174" "3175" "3176" "3177"
## [3178] "3178" "3179" "3180" "3181" "3182" "3183" "3184" "3185" "3186"
## [3187] "3187" "3188" "3189" "3190" "3191" "3192" "3193" "3194" "3195"
## [3196] "3196" "3197" "3198" "3199" "3200" "3201" "3202" "3203" "3204"
## [3205] "3205" "3206" "3207" "3208" "3209" "3210" "3211" "3212" "3213"
## [3214] "3214" "3215" "3216" "3217" "3218" "3219" "3220" "3221" "3222"
## [3223] "3223" "3224" "3225" "3226" "3227" "3228" "3229" "3230" "3231"
## [3232] "3232" "3233" "3234" "3235" "3236" "3237" "3238" "3239" "3240"
## [3241] "3241" "3242" "3243" "3244" "3245" "3246" "3247" "3248" "3249"
## [3250] "3250" "3251" "3252" "3253" "3254" "3255" "3256" "3257" "3258"
## [3259] "3259" "3260" "3261" "3262" "3263" "3264" "3265" "3266" "3267"
## [3268] "3268" "3269" "3270" "3271" "3272" "3273" "3274" "3275" "3276"
## [3277] "3277" "3278" "3279" "3280" "3281" "3282" "3283" "3284" "3285"
## [3286] "3286" "3287" "3288" "3289" "3290" "3291" "3292" "3293" "3294"
## [3295] "3295" "3296" "3297" "3298" "3299" "3300" "3301" "3302" "3303"
## [3304] "3304" "3305" "3306" "3307" "3308" "3309" "3310" "3311" "3312"
## [3313] "3313" "3314" "3315" "3316" "3317" "3318" "3319" "3320" "3321"
## [3322] "3322" "3323" "3324" "3325" "3326" "3327" "3328" "3329" "3330"
## [3331] "3331" "3332" "3333" "3334" "3335" "3336" "3337" "3338" "3339"
## [3340] "3340" "3341" "3342" "3343" "3344" "3345" "3346" "3347" "3348"
## [3349] "3349" "3350" "3351" "3352" "3353" "3354" "3355" "3356" "3357"
## [3358] "3358" "3359" "3360" "3361" "3362" "3363" "3364" "3365" "3366"
## [3367] "3367" "3368" "3369" "3370" "3371" "3372" "3373" "3374" "3375"
## [3376] "3376" "3377" "3378" "3379" "3380" "3381" "3382" "3383" "3384"
## [3385] "3385" "3386" "3387" "3388" "3389" "3390" "3391" "3392" "3393"
## [3394] "3394" "3395" "3396" "3397" "3398" "3399" "3400" "3401" "3402"
## [3403] "3403" "3404" "3405" "3406" "3407" "3408" "3409" "3410" "3411"
## [3412] "3412" "3413" "3414" "3415" "3416" "3417" "3418" "3419" "3420"
## [3421] "3421" "3422" "3423" "3424" "3425" "3426" "3427" "3428" "3429"
## [3430] "3430" "3431" "3432" "3433" "3434" "3435" "3436" "3437" "3438"
## [3439] "3439" "3440" "3441" "3442" "3443" "3444" "3445" "3446" "3447"
## [3448] "3448" "3449" "3450" "3451" "3452" "3453" "3454" "3455" "3456"
## [3457] "3457" "3458" "3459" "3460" "3461" "3462" "3463" "3464" "3465"
## [3466] "3466" "3467" "3468" "3469" "3470" "3471" "3472" "3473" "3474"
## [3475] "3475" "3476" "3477" "3478" "3479" "3480" "3481" "3482" "3483"
## [3484] "3484" "3485" "3486" "3487" "3488" "3489" "3490" "3491" "3492"
## [3493] "3493" "3494" "3495" "3496" "3497" "3498" "3499" "3500" "3501"
## [3502] "3502" "3503" "3504" "3505" "3506" "3507" "3508" "3509" "3510"
## [3511] "3511" "3512" "3513" "3514" "3515" "3516" "3517" "3518" "3519"
## [3520] "3520" "3521" "3522" "3523" "3524" "3525" "3526" "3527" "3528"
## [3529] "3529" "3530" "3531" "3532" "3533" "3534" "3535" "3536" "3537"
## [3538] "3538" "3539" "3540" "3541" "3542" "3543" "3544" "3545" "3546"
## [3547] "3547" "3548" "3549" "3550" "3551" "3552" "3553" "3554" "3555"
## [3556] "3556" "3557" "3558" "3559" "3560" "3561" "3562" "3563" "3564"
## [3565] "3565" "3566" "3567" "3568" "3569" "3570" "3571" "3572" "3573"
## [3574] "3574" "3575" "3576" "3577" "3578" "3579" "3580" "3581" "3582"
## [3583] "3583" "3584" "3585" "3586" "3587" "3588" "3589" "3590" "3591"
## [3592] "3592" "3593" "3594" "3595" "3596" "3597" "3598" "3599" "3600"
## [3601] "3601" "3602" "3603" "3604" "3605" "3606" "3607" "3608" "3609"
## [3610] "3610" "3611" "3612" "3613" "3614" "3615" "3616" "3617" "3618"
## [3619] "3619" "3620" "3621" "3622" "3623" "3624" "3625" "3626" "3627"
## [3628] "3628" "3629" "3630" "3631" "3632" "3633" "3634" "3635" "3636"
## [3637] "3637" "3638" "3639" "3640" "3641" "3642" "3643" "3644" "3645"
## [3646] "3646" "3647" "3648" "3649" "3650" "3651" "3652" "3653" "3654"
## [3655] "3655" "3656" "3657" "3658" "3659" "3660" "3661" "3662" "3663"
## [3664] "3664" "3665" "3666" "3667" "3668" "3669" "3670" "3671" "3672"
## [3673] "3673" "3674" "3675" "3676" "3677" "3678" "3679" "3680" "3681"
## [3682] "3682" "3683" "3684" "3685" "3686" "3687" "3688" "3689" "3690"
## [3691] "3691" "3692" "3693" "3694" "3695" "3696" "3697" "3698" "3699"
## [3700] "3700" "3701" "3702" "3703" "3704" "3705" "3706" "3707" "3708"
## [3709] "3709" "3710" "3711" "3712" "3713" "3714" "3715" "3716" "3717"
## [3718] "3718" "3719" "3720" "3721" "3722" "3723" "3724" "3725" "3726"
## [3727] "3727" "3728" "3729" "3730" "3731" "3732" "3733" "3734" "3735"
## [3736] "3736" "3737" "3738" "3739" "3740" "3741" "3742" "3743" "3744"
## [3745] "3745" "3746" "3747" "3748" "3749" "3750" "3751" "3752" "3753"
## [3754] "3754" "3755" "3756" "3757" "3758" "3759" "3760" "3761" "3762"
## [3763] "3763" "3764" "3765" "3766" "3767" "3768" "3769" "3770" "3771"
## [3772] "3772" "3773" "3774" "3775" "3776" "3777" "3778" "3779" "3780"
## [3781] "3781" "3782" "3783" "3784" "3785" "3786" "3787" "3788" "3789"
## [3790] "3790" "3791" "3792" "3793" "3794" "3795" "3796" "3797" "3798"
## [3799] "3799" "3800" "3801" "3802" "3803" "3804" "3805" "3806" "3807"
## [3808] "3808" "3809" "3810" "3811" "3812" "3813" "3814" "3815" "3816"
## [3817] "3817" "3818" "3819" "3820" "3821" "3822" "3823" "3824" "3825"
## [3826] "3826" "3827" "3828" "3829" "3830" "3831" "3832" "3833" "3834"
## [3835] "3835" "3836" "3837" "3838" "3839" "3840" "3841" "3842" "3843"
## [3844] "3844" "3845" "3846" "3847" "3848" "3849" "3850" "3851" "3852"
## [3853] "3853" "3854" "3855" "3856" "3857" "3858" "3859" "3860" "3861"
## [3862] "3862" "3863" "3864" "3865" "3866" "3867" "3868" "3869" "3870"
## [3871] "3871" "3872" "3873" "3874" "3875" "3876" "3877" "3878" "3879"
## [3880] "3880" "3881" "3882" "3883" "3884" "3885" "3886" "3887" "3888"
## [3889] "3889" "3890" "3891" "3892" "3893" "3894" "3895" "3896" "3897"
## [3898] "3898" "3899" "3900" "3901" "3902" "3903" "3904" "3905" "3906"
## [3907] "3907" "3908" "3909" "3910" "3911" "3912" "3913" "3914" "3915"
## [3916] "3916" "3917" "3918" "3919" "3920" "3921" "3922" "3923" "3924"
## [3925] "3925" "3926" "3927" "3928" "3929" "3930" "3931" "3932" "3933"
## [3934] "3934" "3935" "3936" "3937" "3938" "3939" "3940" "3941" "3942"
## [3943] "3943" "3944" "3945" "3946" "3947" "3948" "3949" "3950" "3951"
## [3952] "3952" "3953" "3954" "3955" "3956" "3957" "3958" "3959" "3960"
## [3961] "3961" "3962" "3963" "3964" "3965" "3966" "3967" "3968" "3969"
## [3970] "3970" "3971" "3972" "3973" "3974" "3975" "3976" "3977" "3978"
## [3979] "3979" "3980" "3981" "3982" "3983" "3984" "3985" "3986" "3987"
## [3988] "3988" "3989" "3990" "3991" "3992" "3993" "3994" "3995" "3996"
## [3997] "3997" "3998" "3999" "4000" "4001" "4002" "4003" "4004" "4005"
## [4006] "4006" "4007" "4008" "4009" "4010" "4011" "4012" "4013" "4014"
## [4015] "4015" "4016" "4017" "4018" "4019" "4020" "4021" "4022" "4023"
## [4024] "4024" "4025" "4026" "4027" "4028" "4029" "4030" "4031" "4032"
## [4033] "4033" "4034" "4035" "4036" "4037" "4038" "4039" "4040" "4041"
## [4042] "4042" "4043" "4044" "4045" "4046" "4047" "4048" "4049" "4050"
## [4051] "4051" "4052" "4053" "4054" "4055" "4056" "4057" "4058" "4059"
## [4060] "4060" "4061" "4062" "4063" "4064" "4065" "4066" "4067" "4068"
## [4069] "4069" "4070" "4071" "4072" "4073" "4074" "4075" "4076" "4077"
## [4078] "4078" "4079" "4080" "4081" "4082" "4083" "4084" "4085" "4086"
## [4087] "4087" "4088" "4089" "4090" "4091" "4092" "4093" "4094" "4095"
## [4096] "4096" "4097" "4098" "4099" "4100" "4101" "4102" "4103" "4104"
## [4105] "4105" "4106" "4107" "4108" "4109" "4110" "4111" "4112" "4113"
## [4114] "4114" "4115" "4116" "4117" "4118" "4119" "4120" "4121" "4122"
## [4123] "4123" "4124" "4125" "4126" "4127" "4128" "4129" "4130" "4131"
## [4132] "4132" "4133" "4134" "4135" "4136" "4137" "4138" "4139" "4140"
## [4141] "4141" "4142" "4143" "4144" "4145" "4146" "4147" "4148" "4149"
## [4150] "4150" "4151" "4152" "4153" "4154" "4155" "4156" "4157" "4158"
## [4159] "4159" "4160" "4161" "4162" "4163" "4164" "4165" "4166" "4167"
## [4168] "4168" "4169" "4170" "4171" "4172" "4173" "4174" "4175" "4176"
## [4177] "4177" "4178" "4179" "4180" "4181" "4182" "4183" "4184" "4185"
## [4186] "4186" "4187" "4188" "4189" "4190" "4191" "4192" "4193" "4194"
## [4195] "4195" "4196" "4197" "4198" "4199" "4200" "4201" "4202" "4203"
## [4204] "4204" "4205" "4206" "4207" "4208" "4209" "4210" "4211" "4212"
## [4213] "4213" "4214" "4215" "4216" "4217" "4218" "4219" "4220" "4221"
## [4222] "4222" "4223" "4224" "4225" "4226" "4227" "4228" "4229" "4230"
## [4231] "4231" "4232" "4233" "4234" "4235" "4236" "4237" "4238" "4239"
## [4240] "4240" "4241" "4242" "4243" "4244" "4245" "4246" "4247" "4248"
## [4249] "4249" "4250" "4251" "4252" "4253" "4254" "4255" "4256" "4257"
## [4258] "4258" "4259" "4260" "4261" "4262" "4263" "4264" "4265" "4266"
## [4267] "4267" "4268" "4269" "4270" "4271" "4272" "4273" "4274" "4275"
## [4276] "4276" "4277" "4278" "4279" "4280" "4281" "4282" "4283" "4284"
## [4285] "4285" "4286" "4287" "4288" "4289" "4290" "4291" "4292" "4293"
## [4294] "4294" "4295" "4296" "4297" "4298" "4299" "4300" "4301" "4302"
## [4303] "4303" "4304" "4305" "4306" "4307" "4308" "4309" "4310" "4311"
## [4312] "4312" "4313" "4314" "4315" "4316" "4317" "4318" "4319" "4320"
## [4321] "4321" "4322" "4323" "4324" "4325" "4326" "4327" "4328" "4329"
## [4330] "4330" "4331" "4332" "4333" "4334" "4335" "4336" "4337" "4338"
## [4339] "4339" "4340" "4341" "4342" "4343" "4344" "4345" "4346" "4347"
## [4348] "4348" "4349" "4350" "4351" "4352" "4353" "4354" "4355" "4356"
## [4357] "4357" "4358" "4359" "4360" "4361" "4362" "4363" "4364" "4365"
## [4366] "4366" "4367" "4368" "4369" "4370" "4371" "4372" "4373" "4374"
## [4375] "4375" "4376" "4377" "4378" "4379" "4380" "4381" "4382" "4383"
## [4384] "4384" "4385" "4386" "4387" "4388" "4389" "4390" "4391" "4392"
## [4393] "4393" "4394" "4395" "4396" "4397" "4398" "4399" "4400" "4401"
## [4402] "4402" "4403" "4404" "4405" "4406" "4407" "4408" "4409" "4410"
## [4411] "4411" "4412" "4413" "4414" "4415" "4416" "4417" "4418" "4419"
## [4420] "4420" "4421" "4422" "4423" "4424" "4425" "4426" "4427" "4428"
## [4429] "4429" "4430" "4431" "4432" "4433" "4434" "4435" "4436" "4437"
## [4438] "4438" "4439" "4440" "4441" "4442" "4443" "4444" "4445" "4446"
## [4447] "4447" "4448" "4449" "4450" "4451" "4452" "4453" "4454" "4455"
## [4456] "4456" "4457" "4458" "4459" "4460" "4461" "4462" "4463" "4464"
## [4465] "4465" "4466" "4467" "4468" "4469" "4470" "4471" "4472" "4473"
## [4474] "4474" "4475" "4476" "4477" "4478" "4479" "4480" "4481" "4482"
## [4483] "4483" "4484" "4485" "4486" "4487" "4488" "4489" "4490" "4491"
## [4492] "4492" "4493" "4494" "4495" "4496" "4497" "4498" "4499" "4500"
## [4501] "4501" "4502" "4503" "4504" "4505" "4506" "4507" "4508" "4509"
## [4510] "4510" "4511" "4512" "4513" "4514" "4515" "4516" "4517" "4518"
## [4519] "4519" "4520" "4521" "4522" "4523" "4524" "4525" "4526" "4527"
## [4528] "4528" "4529" "4530" "4531" "4532" "4533" "4534" "4535" "4536"
## [4537] "4537" "4538" "4539" "4540" "4541" "4542" "4543" "4544" "4545"
## [4546] "4546" "4547" "4548" "4549" "4550" "4551" "4552" "4553" "4554"
## [4555] "4555" "4556" "4557" "4558" "4559" "4560" "4561" "4562" "4563"
## [4564] "4564" "4565" "4566" "4567" "4568" "4569" "4570" "4571" "4572"
## [4573] "4573" "4574" "4575" "4576" "4577" "4578" "4579" "4580" "4581"
## [4582] "4582" "4583" "4584" "4585" "4586" "4587" "4588" "4589" "4590"
## [4591] "4591" "4592" "4593" "4594" "4595" "4596" "4597" "4598" "4599"
## [4600] "4600" "4601" "4602" "4603" "4604" "4605" "4606" "4607" "4608"
## [4609] "4609" "4610" "4611" "4612" "4613" "4614" "4615" "4616" "4617"
## [4618] "4618" "4619" "4620" "4621" "4622" "4623" "4624" "4625" "4626"
## [4627] "4627" "4628" "4629" "4630" "4631" "4632" "4633" "4634" "4635"
## [4636] "4636" "4637" "4638" "4639" "4640" "4641" "4642" "4643" "4644"
## [4645] "4645" "4646" "4647" "4648" "4649" "4650" "4651" "4652" "4653"
## [4654] "4654" "4655" "4656" "4657" "4658" "4659" "4660" "4661" "4662"
## [4663] "4663" "4664" "4665" "4666" "4667" "4668" "4669" "4670" "4671"
## [4672] "4672" "4673" "4674" "4675" "4676" "4677" "4678" "4679" "4680"
## [4681] "4681" "4682" "4683" "4684" "4685" "4686" "4687" "4688" "4689"
## [4690] "4690" "4691" "4692" "4693" "4694" "4695" "4696" "4697" "4698"
## [4699] "4699" "4700" "4701" "4702" "4703" "4704" "4705" "4706" "4707"
## [4708] "4708" "4709" "4710" "4711" "4712" "4713" "4714" "4715" "4716"
## [4717] "4717" "4718" "4719" "4720" "4721" "4722" "4723" "4724" "4725"
## [4726] "4726" "4727" "4728" "4729" "4730" "4731" "4732" "4733" "4734"
## [4735] "4735" "4736" "4737" "4738" "4739" "4740" "4741" "4742" "4743"
## [4744] "4744" "4745" "4746" "4747" "4748" "4749" "4750" "4751" "4752"
## [4753] "4753" "4754" "4755" "4756" "4757" "4758" "4759" "4760" "4761"
## [4762] "4762" "4763" "4764" "4765" "4766" "4767" "4768" "4769" "4770"
## [4771] "4771" "4772" "4773" "4774" "4775" "4776" "4777" "4778" "4779"
## [4780] "4780" "4781" "4782" "4783" "4784" "4785" "4786" "4787" "4788"
## [4789] "4789" "4790" "4791" "4792" "4793" "4794" "4795" "4796" "4797"
## [4798] "4798" "4799" "4800" "4801" "4802" "4803" "4804" "4805" "4806"
## [4807] "4807" "4808" "4809" "4810" "4811" "4812" "4813" "4814" "4815"
## [4816] "4816" "4817" "4818" "4819" "4820" "4821" "4822" "4823" "4824"
## [4825] "4825" "4826" "4827" "4828" "4829" "4830" "4831" "4832" "4833"
## [4834] "4834" "4835" "4836" "4837" "4838" "4839" "4840" "4841" "4842"
## [4843] "4843" "4844" "4845" "4846" "4847" "4848" "4849" "4850" "4851"
## [4852] "4852" "4853" "4854" "4855" "4856" "4857" "4858" "4859" "4860"
## [4861] "4861" "4862" "4863" "4864" "4865" "4866" "4867" "4868" "4869"
## [4870] "4870" "4871" "4872" "4873" "4874" "4875" "4876" "4877" "4878"
## [4879] "4879" "4880" "4881" "4882" "4883" "4884" "4885" "4886" "4887"
## [4888] "4888" "4889" "4890" "4891" "4892" "4893" "4894" "4895" "4896"
## [4897] "4897" "4898" "4899" "4900" "4901" "4902" "4903" "4904" "4905"
## [4906] "4906" "4907" "4908" "4909" "4910" "4911" "4912" "4913" "4914"
## [4915] "4915" "4916" "4917" "4918" "4919" "4920" "4921" "4922" "4923"
## [4924] "4924" "4925" "4926" "4927" "4928" "4929" "4930" "4931" "4932"
## [4933] "4933" "4934" "4935" "4936" "4937" "4938" "4939" "4940" "4941"
## [4942] "4942" "4943" "4944" "4945" "4946" "4947" "4948" "4949" "4950"
## [4951] "4951" "4952" "4953" "4954" "4955" "4956" "4957" "4958" "4959"
## [4960] "4960" "4961" "4962" "4963" "4964" "4965" "4966" "4967" "4968"
## [4969] "4969" "4970" "4971" "4972" "4973" "4974" "4975" "4976" "4977"
## [4978] "4978" "4979" "4980" "4981" "4982" "4983" "4984" "4985" "4986"
## [4987] "4987" "4988" "4989" "4990" "4991" "4992" "4993" "4994" "4995"
## [4996] "4996" "4997" "4998" "4999" "5000" "5001" "5002" "5003" "5004"
## [5005] "5005" "5006" "5007" "5008" "5009" "5010" "5011" "5012" "5013"
## [5014] "5014" "5015" "5016" "5017" "5018" "5019" "5020" "5021" "5022"
## [5023] "5023" "5024" "5025" "5026" "5027" "5028" "5029" "5030" "5031"
## [5032] "5032" "5033" "5034" "5035" "5036" "5037" "5038" "5039" "5040"
## [5041] "5041" "5042" "5043" "5044" "5045" "5046" "5047" "5048" "5049"
## [5050] "5050" "5051" "5052" "5053" "5054" "5055" "5056" "5057" "5058"
## [5059] "5059" "5060" "5061" "5062" "5063" "5064" "5065" "5066" "5067"
## [5068] "5068" "5069" "5070" "5071" "5072" "5073" "5074" "5075" "5076"
## [5077] "5077" "5078" "5079" "5080" "5081" "5082" "5083" "5084" "5085"
## [5086] "5086" "5087" "5088" "5089" "5090" "5091" "5092" "5093" "5094"
## [5095] "5095" "5096" "5097" "5098" "5099" "5100" "5101" "5102" "5103"
## [5104] "5104" "5105" "5106" "5107" "5108" "5109" "5110" "5111" "5112"
## [5113] "5113" "5114" "5115" "5116" "5117" "5118" "5119" "5120" "5121"
## [5122] "5122" "5123" "5124" "5125" "5126" "5127" "5128" "5129" "5130"
## [5131] "5131" "5132" "5133" "5134" "5135" "5136" "5137" "5138" "5139"
## [5140] "5140" "5141" "5142" "5143" "5144" "5145" "5146" "5147" "5148"
## [5149] "5149" "5150" "5151" "5152" "5153" "5154" "5155" "5156" "5157"
## [5158] "5158" "5159" "5160" "5161" "5162" "5163" "5164" "5165" "5166"
## [5167] "5167" "5168" "5169" "5170" "5171" "5172" "5173" "5174" "5175"
## [5176] "5176" "5177" "5178" "5179" "5180" "5181" "5182" "5183" "5184"
## [5185] "5185" "5186" "5187" "5188" "5189" "5190" "5191" "5192" "5193"
## [5194] "5194" "5195" "5196" "5197" "5198" "5199" "5200" "5201" "5202"
## [5203] "5203" "5204" "5205" "5206" "5207" "5208" "5209" "5210" "5211"
## [5212] "5212" "5213" "5214" "5215" "5216" "5217" "5218" "5219" "5220"
## [5221] "5221" "5222" "5223" "5224" "5225" "5226" "5227" "5228" "5229"
## [5230] "5230" "5231" "5232" "5233" "5234" "5235" "5236" "5237" "5238"
## [5239] "5239" "5240" "5241" "5242" "5243" "5244" "5245" "5246" "5247"
## [5248] "5248" "5249" "5250" "5251" "5252" "5253" "5254" "5255" "5256"
## [5257] "5257" "5258" "5259" "5260" "5261" "5262" "5263" "5264" "5265"
## [5266] "5266" "5267" "5268" "5269" "5270" "5271" "5272" "5273" "5274"
## [5275] "5275" "5276" "5277" "5278" "5279" "5280" "5281" "5282" "5283"
## [5284] "5284" "5285" "5286" "5287" "5288" "5289" "5290" "5291" "5292"
## [5293] "5293" "5294" "5295" "5296" "5297" "5298" "5299" "5300" "5301"
## [5302] "5302" "5303" "5304" "5305" "5306" "5307" "5308" "5309" "5310"
## [5311] "5311" "5312" "5313" "5314" "5315" "5316" "5317" "5318" "5319"
## [5320] "5320" "5321" "5322" "5323" "5324" "5325" "5326" "5327" "5328"
## [5329] "5329" "5330" "5331" "5332" "5333" "5334" "5335" "5336" "5337"
## [5338] "5338" "5339" "5340" "5341" "5342" "5343" "5344" "5345" "5346"
## [5347] "5347" "5348" "5349" "5350" "5351" "5352" "5353" "5354" "5355"
## [5356] "5356" "5357" "5358" "5359" "5360" "5361" "5362" "5363" "5364"
## [5365] "5365" "5366" "5367" "5368" "5369" "5370" "5371" "5372" "5373"
## [5374] "5374" "5375" "5376" "5377" "5378" "5379" "5380" "5381" "5382"
## [5383] "5383" "5384" "5385" "5386" "5387" "5388" "5389" "5390" "5391"
## [5392] "5392" "5393" "5394" "5395" "5396" "5397" "5398" "5399" "5400"
## [5401] "5401" "5402" "5403" "5404" "5405" "5406" "5407" "5408" "5409"
## [5410] "5410" "5411" "5412" "5413" "5414" "5415" "5416" "5417" "5418"
## [5419] "5419" "5420" "5421" "5422" "5423" "5424" "5425" "5426" "5427"
## [5428] "5428" "5429" "5430" "5431" "5432" "5433" "5434" "5435" "5436"
## [5437] "5437" "5438" "5439" "5440" "5441" "5442" "5443" "5444" "5445"
## [5446] "5446" "5447" "5448" "5449" "5450" "5451" "5452" "5453" "5454"
## [5455] "5455" "5456" "5457" "5458" "5459" "5460" "5461" "5462" "5463"
## [5464] "5464" "5465" "5466" "5467" "5468" "5469" "5470" "5471" "5472"
## [5473] "5473" "5474" "5475" "5476" "5477" "5478" "5479" "5480" "5481"
## [5482] "5482" "5483" "5484" "5485" "5486" "5487" "5488" "5489" "5490"
## [5491] "5491" "5492" "5493" "5494" "5495" "5496" "5497" "5498" "5499"
## [5500] "5500" "5501" "5502" "5503" "5504" "5505" "5506" "5507" "5508"
## [5509] "5509" "5510" "5511" "5512" "5513" "5514" "5515" "5516" "5517"
## [5518] "5518" "5519" "5520" "5521" "5522" "5523" "5524" "5525" "5526"
## [5527] "5527" "5528" "5529" "5530" "5531" "5532" "5533" "5534" "5535"
## [5536] "5536" "5537" "5538" "5539" "5540" "5541" "5542" "5543" "5544"
## [5545] "5545" "5546" "5547" "5548" "5549" "5550" "5551" "5552" "5553"
## [5554] "5554" "5555" "5556" "5557" "5558" "5559" "5560" "5561" "5562"
## [5563] "5563" "5564" "5565" "5566" "5567" "5568" "5569" "5570" "5571"
## [5572] "5572" "5573" "5574" "5575" "5576" "5577" "5578" "5579" "5580"
## [5581] "5581" "5582" "5583" "5584" "5585" "5586" "5587" "5588" "5589"
## [5590] "5590" "5591" "5592" "5593" "5594" "5595" "5596" "5597" "5598"
## [5599] "5599" "5600" "5601" "5602" "5603" "5604" "5605" "5606" "5607"
## [5608] "5608" "5609" "5610" "5611" "5612" "5613" "5614" "5615" "5616"
## [5617] "5617" "5618" "5619" "5620" "5621" "5622" "5623" "5624" "5625"
## [5626] "5626" "5627" "5628" "5629" "5630" "5631" "5632" "5633" "5634"
## [5635] "5635" "5636" "5637" "5638" "5639" "5640" "5641" "5642" "5643"
## [5644] "5644" "5645" "5646" "5647" "5648" "5649" "5650" "5651" "5652"
## [5653] "5653" "5654" "5655" "5656" "5657" "5658" "5659" "5660" "5661"
## [5662] "5662" "5663" "5664" "5665" "5666" "5667" "5668" "5669" "5670"
## [5671] "5671" "5672" "5673" "5674" "5675" "5676" "5677" "5678" "5679"
## [5680] "5680" "5681" "5682" "5683" "5684" "5685" "5686" "5687" "5688"
## [5689] "5689" "5690" "5691" "5692" "5693" "5694" "5695" "5696" "5697"
## [5698] "5698" "5699" "5700" "5701" "5702" "5703" "5704" "5705" "5706"
## [5707] "5707" "5708" "5709" "5710" "5711" "5712" "5713" "5714" "5715"
## [5716] "5716" "5717" "5718" "5719" "5720" "5721" "5722" "5723" "5724"
## [5725] "5725" "5726" "5727" "5728" "5729" "5730" "5731" "5732" "5733"
## [5734] "5734" "5735" "5736" "5737" "5738" "5739" "5740" "5741" "5742"
## [5743] "5743" "5744" "5745" "5746" "5747" "5748" "5749" "5750" "5751"
## [5752] "5752" "5753" "5754" "5755" "5756" "5757" "5758" "5759" "5760"
## [5761] "5761" "5762" "5763" "5764" "5765" "5766" "5767" "5768" "5769"
## [5770] "5770" "5771" "5772" "5773" "5774" "5775" "5776" "5777" "5778"
## [5779] "5779" "5780" "5781" "5782" "5783" "5784" "5785" "5786" "5787"
## [5788] "5788" "5789" "5790" "5791" "5792" "5793" "5794" "5795" "5796"
## [5797] "5797" "5798" "5799" "5800" "5801" "5802" "5803" "5804" "5805"
## [5806] "5806" "5807" "5808" "5809" "5810" "5811" "5812" "5813" "5814"
## [5815] "5815" "5816" "5817" "5818" "5819" "5820" "5821" "5822" "5823"
## [5824] "5824" "5825" "5826" "5827" "5828" "5829" "5830" "5831" "5832"
## [5833] "5833" "5834" "5835" "5836" "5837" "5838" "5839" "5840" "5841"
## [5842] "5842" "5843" "5844" "5845" "5846" "5847" "5848" "5849" "5850"
## [5851] "5851" "5852" "5853" "5854" "5855" "5856" "5857" "5858" "5859"
## [5860] "5860" "5861" "5862" "5863" "5864" "5865" "5866" "5867" "5868"
## [5869] "5869" "5870" "5871" "5872" "5873" "5874" "5875" "5876" "5877"
## [5878] "5878" "5879" "5880" "5881" "5882" "5883" "5884" "5885" "5886"
## [5887] "5887" "5888" "5889" "5890" "5891" "5892" "5893" "5894" "5895"
## [5896] "5896" "5897" "5898" "5899" "5900" "5901" "5902" "5903" "5904"
## [5905] "5905" "5906" "5907" "5908" "5909" "5910" "5911" "5912" "5913"
## [5914] "5914" "5915" "5916" "5917" "5918" "5919" "5920" "5921" "5922"
## [5923] "5923" "5924" "5925" "5926" "5927" "5928" "5929" "5930" "5931"
## [5932] "5932" "5933" "5934" "5935" "5936" "5937" "5938" "5939" "5940"
## [5941] "5941" "5942" "5943" "5944" "5945" "5946" "5947" "5948" "5949"
## [5950] "5950" "5951" "5952" "5953" "5954" "5955" "5956" "5957" "5958"
## [5959] "5959" "5960" "5961" "5962" "5963" "5964" "5965" "5966" "5967"
## [5968] "5968" "5969" "5970" "5971" "5972" "5973" "5974" "5975" "5976"
## [5977] "5977" "5978" "5979" "5980" "5981" "5982" "5983" "5984" "5985"
## [5986] "5986" "5987" "5988" "5989" "5990" "5991" "5992" "5993" "5994"
## [5995] "5995" "5996" "5997" "5998" "5999" "6000" "6001" "6002" "6003"
## [6004] "6004" "6005" "6006" "6007" "6008" "6009" "6010" "6011" "6012"
## [6013] "6013" "6014" "6015" "6016" "6017" "6018" "6019" "6020" "6021"
## [6022] "6022" "6023" "6024" "6025" "6026" "6027" "6028" "6029" "6030"
## [6031] "6031" "6032" "6033" "6034" "6035" "6036" "6037" "6038" "6039"
## [6040] "6040" "6041" "6042" "6043" "6044" "6045" "6046" "6047" "6048"
## [6049] "6049" "6050" "6051" "6052" "6053" "6054" "6055" "6056" "6057"
## [6058] "6058" "6059" "6060" "6061" "6062" "6063" "6064" "6065" "6066"
## [6067] "6067" "6068" "6069" "6070" "6071" "6072" "6073" "6074" "6075"
## [6076] "6076" "6077" "6078" "6079" "6080" "6081" "6082" "6083" "6084"
## [6085] "6085" "6086" "6087" "6088" "6089" "6090" "6091" "6092" "6093"
## [6094] "6094" "6095" "6096" "6097" "6098" "6099" "6100" "6101" "6102"
## [6103] "6103" "6104" "6105" "6106" "6107" "6108" "6109" "6110" "6111"
## [6112] "6112" "6113" "6114" "6115" "6116" "6117" "6118" "6119" "6120"
## [6121] "6121" "6122" "6123" "6124" "6125" "6126" "6127" "6128" "6129"
## [6130] "6130" "6131" "6132" "6133" "6134" "6135" "6136" "6137" "6138"
## [6139] "6139" "6140" "6141" "6142" "6143" "6144" "6145" "6146" "6147"
## [6148] "6148" "6149" "6150" "6151" "6152" "6153" "6154" "6155" "6156"
## [6157] "6157" "6158" "6159" "6160" "6161" "6162" "6163" "6164" "6165"
## [6166] "6166" "6167" "6168" "6169" "6170" "6171" "6172" "6173" "6174"
## [6175] "6175" "6176" "6177" "6178" "6179" "6180" "6181" "6182" "6183"
## [6184] "6184" "6185" "6186" "6187" "6188" "6189" "6190" "6191" "6192"
## [6193] "6193" "6194" "6195" "6196" "6197" "6198" "6199" "6200" "6201"
## [6202] "6202" "6203" "6204" "6205" "6206" "6207" "6208" "6209" "6210"
## [6211] "6211" "6212" "6213" "6214" "6215" "6216" "6217" "6218" "6219"
## [6220] "6220" "6221" "6222" "6223" "6224" "6225" "6226" "6227" "6228"
## [6229] "6229" "6230" "6231" "6232" "6233" "6234" "6235" "6236" "6237"
## [6238] "6238" "6239" "6240" "6241" "6242" "6243" "6244" "6245" "6246"
## [6247] "6247" "6248" "6249" "6250" "6251" "6252" "6253" "6254" "6255"
## [6256] "6256" "6257" "6258" "6259" "6260" "6261" "6262" "6263" "6264"
## [6265] "6265" "6266" "6267" "6268" "6269" "6270" "6271" "6272" "6273"
## [6274] "6274" "6275" "6276" "6277" "6278" "6279" "6280" "6281" "6282"
## [6283] "6283" "6284" "6285" "6286" "6287" "6288" "6289" "6290" "6291"
## [6292] "6292" "6293" "6294" "6295" "6296" "6297" "6298" "6299" "6300"
## [6301] "6301" "6302" "6303" "6304" "6305" "6306" "6307" "6308" "6309"
## [6310] "6310" "6311" "6312" "6313" "6314" "6315" "6316" "6317" "6318"
## [6319] "6319" "6320" "6321" "6322" "6323" "6324" "6325" "6326" "6327"
## [6328] "6328" "6329" "6330" "6331" "6332" "6333" "6334" "6335" "6336"
## [6337] "6337" "6338" "6339" "6340" "6341" "6342" "6343" "6344" "6345"
## [6346] "6346" "6347" "6348" "6349" "6350" "6351" "6352" "6353" "6354"
## [6355] "6355" "6356" "6357" "6358" "6359" "6360" "6361" "6362" "6363"
## [6364] "6364" "6365" "6366" "6367" "6368" "6369" "6370" "6371" "6372"
## [6373] "6373" "6374" "6375" "6376" "6377" "6378" "6379" "6380" "6381"
## [6382] "6382" "6383" "6384" "6385" "6386" "6387" "6388" "6389" "6390"
## [6391] "6391" "6392" "6393" "6394" "6395" "6396" "6397" "6398" "6399"
## [6400] "6400" "6401" "6402" "6403" "6404" "6405" "6406" "6407" "6408"
## [6409] "6409" "6410" "6411" "6412" "6413" "6414" "6415" "6416" "6417"
## [6418] "6418" "6419" "6420" "6421" "6422" "6423" "6424" "6425" "6426"
## [6427] "6427" "6428" "6429" "6430" "6431" "6432" "6433" "6434" "6435"
## [6436] "6436" "6437" "6438" "6439" "6440" "6441" "6442" "6443" "6444"
## [6445] "6445" "6446" "6447" "6448" "6449" "6450" "6451" "6452" "6453"
## [6454] "6454" "6455" "6456" "6457" "6458" "6459" "6460" "6461" "6462"
## [6463] "6463" "6464" "6465" "6466" "6467" "6468" "6469" "6470" "6471"
## [6472] "6472" "6473" "6474" "6475" "6476" "6477" "6478" "6479" "6480"
## [6481] "6481" "6482" "6483" "6484" "6485" "6486" "6487" "6488" "6489"
## [6490] "6490" "6491" "6492" "6493" "6494" "6495" "6496" "6497" "6498"
## [6499] "6499" "6500" "6501" "6502" "6503" "6504" "6505" "6506" "6507"
## [6508] "6508" "6509" "6510" "6511" "6512" "6513" "6514" "6515" "6516"
## [6517] "6517" "6518" "6519" "6520" "6521" "6522" "6523" "6524" "6525"
## [6526] "6526" "6527" "6528" "6529" "6530" "6531" "6532" "6533" "6534"
## [6535] "6535" "6536" "6537" "6538" "6539" "6540" "6541" "6542" "6543"
## [6544] "6544" "6545" "6546" "6547" "6548" "6549" "6550" "6551" "6552"
## [6553] "6553" "6554" "6555" "6556" "6557" "6558" "6559" "6560" "6561"
## [6562] "6562" "6563" "6564" "6565" "6566" "6567" "6568" "6569" "6570"
## [6571] "6571" "6572" "6573" "6574" "6575" "6576" "6577" "6578" "6579"
## [6580] "6580" "6581" "6582" "6583" "6584" "6585" "6586" "6587" "6588"
## [6589] "6589" "6590" "6591" "6592" "6593" "6594" "6595" "6596" "6597"
## [6598] "6598" "6599" "6600" "6601" "6602" "6603" "6604" "6605" "6606"
## [6607] "6607" "6608" "6609" "6610" "6611" "6612" "6613" "6614" "6615"
## [6616] "6616" "6617" "6618" "6619" "6620" "6621" "6622" "6623" "6624"
## [6625] "6625" "6626" "6627" "6628" "6629" "6630" "6631" "6632" "6633"
## [6634] "6634" "6635" "6636" "6637" "6638" "6639" "6640" "6641" "6642"
## [6643] "6643" "6644" "6645" "6646" "6647" "6648" "6649" "6650" "6651"
## [6652] "6652" "6653" "6654" "6655" "6656" "6657" "6658" "6659" "6660"
## [6661] "6661" "6662" "6663" "6664" "6665" "6666" "6667" "6668" "6669"
## [6670] "6670" "6671" "6672" "6673" "6674" "6675" "6676" "6677" "6678"
## [6679] "6679" "6680" "6681" "6682" "6683" "6684" "6685" "6686" "6687"
## [6688] "6688" "6689" "6690" "6691" "6692" "6693" "6694" "6695" "6696"
## [6697] "6697" "6698" "6699" "6700" "6701" "6702" "6703" "6704" "6705"
## [6706] "6706" "6707" "6708" "6709" "6710" "6711" "6712" "6713" "6714"
## [6715] "6715" "6716" "6717" "6718" "6719" "6720" "6721" "6722" "6723"
## [6724] "6724" "6725" "6726" "6727" "6728" "6729" "6730" "6731" "6732"
## [6733] "6733" "6734" "6735" "6736" "6737" "6738" "6739" "6740" "6741"
## [6742] "6742" "6743" "6744" "6745" "6746" "6747" "6748" "6749" "6750"
## [6751] "6751" "6752" "6753" "6754" "6755" "6756" "6757" "6758" "6759"
## [6760] "6760" "6761" "6762" "6763" "6764" "6765" "6766" "6767" "6768"
## [6769] "6769" "6770" "6771" "6772" "6773" "6774" "6775" "6776" "6777"
## [6778] "6778" "6779" "6780" "6781" "6782" "6783" "6784" "6785" "6786"
## [6787] "6787" "6788" "6789" "6790" "6791" "6792" "6793" "6794" "6795"
## [6796] "6796" "6797" "6798" "6799" "6800" "6801" "6802" "6803" "6804"
## [6805] "6805" "6806" "6807" "6808" "6809" "6810" "6811" "6812" "6813"
## [6814] "6814" "6815" "6816" "6817" "6818" "6819" "6820" "6821" "6822"
## [6823] "6823" "6824" "6825" "6826" "6827" "6828" "6829" "6830" "6831"
## [6832] "6832" "6833" "6834" "6835" "6836" "6837" "6838" "6839" "6840"
## [6841] "6841" "6842" "6843" "6844" "6845" "6846" "6847" "6848" "6849"
## [6850] "6850" "6851" "6852" "6853" "6854" "6855" "6856" "6857" "6858"
## [6859] "6859" "6860" "6861" "6862" "6863" "6864" "6865" "6866" "6867"
## [6868] "6868" "6869" "6870" "6871" "6872" "6873" "6874" "6875" "6876"
## [6877] "6877" "6878" "6879" "6880" "6881" "6882" "6883" "6884" "6885"
## [6886] "6886" "6887" "6888" "6889" "6890" "6891" "6892" "6893" "6894"
## [6895] "6895" "6896" "6897" "6898" "6899" "6900" "6901" "6902" "6903"
## [6904] "6904" "6905" "6906" "6907" "6908" "6909" "6910" "6911" "6912"
## [6913] "6913" "6914" "6915" "6916" "6917" "6918" "6919" "6920" "6921"
## [6922] "6922" "6923" "6924" "6925" "6926" "6927" "6928" "6929" "6930"
## [6931] "6931" "6932" "6933" "6934" "6935" "6936" "6937" "6938" "6939"
## [6940] "6940" "6941" "6942" "6943" "6944" "6945" "6946" "6947" "6948"
## [6949] "6949" "6950" "6951" "6952" "6953" "6954" "6955" "6956" "6957"
## [6958] "6958" "6959" "6960" "6961" "6962" "6963" "6964" "6965" "6966"
## [6967] "6967" "6968" "6969" "6970" "6971" "6972" "6973" "6974" "6975"
## [6976] "6976" "6977" "6978" "6979" "6980" "6981" "6982" "6983" "6984"
## [6985] "6985" "6986" "6987" "6988" "6989" "6990" "6991" "6992" "6993"
## [6994] "6994" "6995" "6996" "6997" "6998" "6999" "7000" "7001" "7002"
## [7003] "7003" "7004" "7005" "7006" "7007" "7008" "7009" "7010" "7011"
## [7012] "7012" "7013" "7014" "7015" "7016" "7017" "7018" "7019" "7020"
## [7021] "7021" "7022" "7023" "7024" "7025" "7026" "7027" "7028" "7029"
## [7030] "7030" "7031" "7032" "7033" "7034" "7035" "7036" "7037" "7038"
## [7039] "7039" "7040" "7041" "7042" "7043" "7044" "7045" "7046" "7047"
## [7048] "7048" "7049" "7050" "7051" "7052" "7053" "7054" "7055" "7056"
## [7057] "7057" "7058" "7059" "7060" "7061" "7062" "7063" "7064" "7065"
## [7066] "7066" "7067" "7068" "7069" "7070" "7071" "7072" "7073" "7074"
## [7075] "7075" "7076" "7077" "7078" "7079" "7080" "7081" "7082" "7083"
## [7084] "7084" "7085" "7086" "7087" "7088" "7089" "7090" "7091" "7092"
## [7093] "7093" "7094" "7095" "7096" "7097" "7098" "7099" "7100" "7101"
## [7102] "7102" "7103" "7104" "7105" "7106" "7107" "7108" "7109" "7110"
## [7111] "7111" "7112" "7113" "7114" "7115" "7116" "7117" "7118" "7119"
## [7120] "7120" "7121" "7122" "7123" "7124" "7125" "7126" "7127" "7128"
## [7129] "7129" "7130" "7131" "7132" "7133" "7134" "7135" "7136" "7137"
## [7138] "7138" "7139" "7140" "7141" "7142" "7143" "7144" "7145" "7146"
## [7147] "7147" "7148" "7149" "7150" "7151" "7152" "7153" "7154" "7155"
## [7156] "7156" "7157" "7158" "7159" "7160" "7161" "7162" "7163" "7164"
## [7165] "7165" "7166" "7167" "7168" "7169" "7170" "7171" "7172" "7173"
## [7174] "7174" "7175" "7176" "7177" "7178" "7179" "7180" "7181" "7182"
## [7183] "7183" "7184" "7185" "7186" "7187" "7188" "7189" "7190" "7191"
## [7192] "7192" "7193" "7194" "7195" "7196" "7197" "7198" "7199" "7200"
## [7201] "7201" "7202" "7203" "7204" "7205" "7206" "7207" "7208" "7209"
## [7210] "7210" "7211" "7212" "7213" "7214" "7215" "7216" "7217" "7218"
## [7219] "7219" "7220" "7221" "7222" "7223" "7224" "7225" "7226" "7227"
## [7228] "7228" "7229" "7230" "7231" "7232" "7233" "7234" "7235" "7236"
## [7237] "7237" "7238" "7239" "7240" "7241" "7242" "7243" "7244" "7245"
## [7246] "7246" "7247" "7248" "7249" "7250" "7251" "7252" "7253" "7254"
## [7255] "7255" "7256" "7257" "7258" "7259" "7260" "7261" "7262" "7263"
## [7264] "7264" "7265" "7266" "7267" "7268" "7269" "7270" "7271" "7272"
## [7273] "7273" "7274" "7275" "7276" "7277" "7278" "7279" "7280" "7281"
## [7282] "7282" "7283" "7284" "7285" "7286" "7287" "7288" "7289" "7290"
## [7291] "7291" "7292" "7293" "7294" "7295" "7296" "7297" "7298" "7299"
## [7300] "7300" "7301" "7302" "7303" "7304" "7305" "7306" "7307" "7308"
## [7309] "7309" "7310" "7311" "7312" "7313" "7314" "7315" "7316" "7317"
## [7318] "7318" "7319" "7320" "7321" "7322" "7323" "7324" "7325" "7326"
## [7327] "7327" "7328" "7329" "7330" "7331" "7332" "7333" "7334" "7335"
## [7336] "7336" "7337" "7338" "7339" "7340" "7341" "7342" "7343" "7344"
## [7345] "7345" "7346" "7347" "7348" "7349" "7350" "7351" "7352" "7353"
## [7354] "7354" "7355" "7356" "7357" "7358" "7359" "7360" "7361" "7362"
## [7363] "7363" "7364" "7365" "7366" "7367" "7368" "7369" "7370" "7371"
## [7372] "7372" "7373" "7374" "7375" "7376" "7377" "7378" "7379" "7380"
## [7381] "7381" "7382" "7383" "7384" "7385" "7386" "7387" "7388" "7389"
## [7390] "7390" "7391" "7392" "7393" "7394" "7395" "7396" "7397" "7398"
## [7399] "7399" "7400" "7401" "7402" "7403" "7404" "7405" "7406" "7407"
## [7408] "7408" "7409" "7410" "7411" "7412" "7413" "7414" "7415" "7416"
## [7417] "7417" "7418" "7419" "7420" "7421" "7422" "7423" "7424" "7425"
## [7426] "7426" "7427" "7428" "7429" "7430" "7431" "7432" "7433" "7434"
## [7435] "7435" "7436" "7437" "7438" "7439" "7440" "7441" "7442" "7443"
## [7444] "7444" "7445" "7446" "7447" "7448" "7449" "7450" "7451" "7452"
## [7453] "7453" "7454" "7455" "7456" "7457" "7458" "7459" "7460" "7461"
## [7462] "7462" "7463" "7464" "7465" "7466" "7467" "7468" "7469" "7470"
## [7471] "7471" "7472" "7473" "7474" "7475" "7476" "7477" "7478" "7479"
## [7480] "7480" "7481" "7482" "7483" "7484" "7485" "7486" "7487" "7488"
## [7489] "7489" "7490" "7491" "7492" "7493" "7494" "7495" "7496" "7497"
## [7498] "7498" "7499" "7500" "7501" "7502" "7503" "7504" "7505" "7506"
## [7507] "7507" "7508" "7509" "7510" "7511" "7512" "7513" "7514" "7515"
## [7516] "7516" "7517" "7518" "7519" "7520" "7521" "7522" "7523" "7524"
## [7525] "7525" "7526" "7527" "7528" "7529" "7530" "7531" "7532" "7533"
## [7534] "7534" "7535" "7536" "7537" "7538" "7539" "7540" "7541" "7542"
## [7543] "7543" "7544" "7545" "7546" "7547" "7548" "7549" "7550" "7551"
## [7552] "7552" "7553" "7554" "7555" "7556" "7557" "7558" "7559" "7560"
## [7561] "7561" "7562" "7563" "7564" "7565" "7566" "7567" "7568" "7569"
## [7570] "7570" "7571" "7572" "7573" "7574" "7575" "7576" "7577" "7578"
## [7579] "7579" "7580" "7581" "7582" "7583" "7584" "7585" "7586" "7587"
## [7588] "7588" "7589" "7590" "7591" "7592" "7593" "7594" "7595" "7596"
## [7597] "7597" "7598" "7599" "7600" "7601" "7602" "7603" "7604" "7605"
## [7606] "7606" "7607" "7608" "7609" "7610" "7611" "7612" "7613" "7614"
## [7615] "7615" "7616" "7617" "7618" "7619" "7620" "7621" "7622" "7623"
## [7624] "7624" "7625" "7626" "7627" "7628" "7629" "7630" "7631" "7632"
## [7633] "7633" "7634" "7635" "7636" "7637" "7638" "7639" "7640" "7641"
## [7642] "7642" "7643" "7644" "7645" "7646" "7647" "7648" "7649" "7650"
## [7651] "7651" "7652" "7653" "7654" "7655" "7656" "7657" "7658" "7659"
## [7660] "7660" "7661" "7662" "7663" "7664" "7665" "7666" "7667" "7668"
## [7669] "7669" "7670" "7671" "7672" "7673" "7674" "7675" "7676" "7677"
## [7678] "7678" "7679" "7680" "7681" "7682" "7683" "7684" "7685" "7686"
## [7687] "7687" "7688" "7689" "7690" "7691" "7692" "7693" "7694" "7695"
## [7696] "7696" "7697" "7698" "7699" "7700" "7701" "7702" "7703" "7704"
## [7705] "7705" "7706" "7707" "7708" "7709" "7710" "7711" "7712" "7713"
## [7714] "7714" "7715" "7716" "7717" "7718" "7719" "7720" "7721" "7722"
## [7723] "7723" "7724" "7725" "7726" "7727" "7728" "7729" "7730" "7731"
## [7732] "7732" "7733" "7734" "7735" "7736" "7737" "7738" "7739" "7740"
## [7741] "7741" "7742" "7743" "7744" "7745" "7746" "7747" "7748" "7749"
## [7750] "7750" "7751" "7752" "7753" "7754" "7755" "7756" "7757" "7758"
## [7759] "7759" "7760" "7761" "7762" "7763" "7764" "7765" "7766" "7767"
## [7768] "7768" "7769" "7770" "7771" "7772" "7773" "7774" "7775" "7776"
## [7777] "7777" "7778" "7779" "7780" "7781" "7782" "7783" "7784" "7785"
## [7786] "7786" "7787" "7788" "7789" "7790" "7791" "7792" "7793" "7794"
## [7795] "7795" "7796" "7797" "7798" "7799" "7800" "7801" "7802" "7803"
## [7804] "7804" "7805" "7806" "7807" "7808" "7809" "7810" "7811" "7812"
## [7813] "7813" "7814" "7815" "7816" "7817" "7818" "7819" "7820" "7821"
## [7822] "7822" "7823" "7824" "7825" "7826" "7827" "7828" "7829" "7830"
## [7831] "7831" "7832" "7833" "7834" "7835" "7836" "7837" "7838" "7839"
## [7840] "7840" "7841" "7842" "7843" "7844" "7845" "7846" "7847" "7848"
## [7849] "7849" "7850" "7851" "7852" "7853" "7854" "7855" "7856" "7857"
## [7858] "7858" "7859" "7860" "7861" "7862" "7863" "7864" "7865" "7866"
## [7867] "7867" "7868" "7869" "7870" "7871" "7872" "7873" "7874" "7875"
## [7876] "7876" "7877" "7878" "7879" "7880" "7881" "7882" "7883" "7884"
## [7885] "7885" "7886" "7887" "7888" "7889" "7890" "7891" "7892" "7893"
## [7894] "7894" "7895" "7896" "7897" "7898" "7899" "7900" "7901" "7902"
## [7903] "7903" "7904" "7905" "7906" "7907" "7908" "7909" "7910" "7911"
## [7912] "7912" "7913" "7914" "7915" "7916" "7917" "7918" "7919" "7920"
## [7921] "7921" "7922" "7923" "7924" "7925" "7926" "7927" "7928" "7929"
## [7930] "7930" "7931" "7932" "7933" "7934" "7935" "7936" "7937" "7938"
## [7939] "7939" "7940" "7941" "7942" "7943" "7944" "7945" "7946" "7947"
## [7948] "7948" "7949" "7950" "7951" "7952" "7953" "7954" "7955" "7956"
## [7957] "7957" "7958" "7959" "7960" "7961" "7962" "7963" "7964" "7965"
## [7966] "7966" "7967" "7968" "7969" "7970" "7971" "7972" "7973" "7974"
## [7975] "7975" "7976" "7977" "7978" "7979" "7980" "7981" "7982" "7983"
## [7984] "7984" "7985" "7986" "7987" "7988" "7989" "7990" "7991" "7992"
## [7993] "7993" "7994" "7995" "7996" "7997" "7998" "7999" "8000" "8001"
## [8002] "8002" "8003" "8004" "8005" "8006" "8007" "8008" "8009" "8010"
## [8011] "8011" "8012" "8013" "8014" "8015" "8016" "8017" "8018" "8019"
## [8020] "8020" "8021" "8022" "8023" "8024" "8025" "8026" "8027" "8028"
## [8029] "8029" "8030" "8031" "8032" "8033" "8034" "8035" "8036" "8037"
## [8038] "8038" "8039" "8040" "8041" "8042" "8043" "8044" "8045" "8046"
## [8047] "8047" "8048" "8049" "8050" "8051" "8052" "8053" "8054" "8055"
## [8056] "8056" "8057" "8058" "8059" "8060" "8061" "8062" "8063" "8064"
## [8065] "8065" "8066" "8067" "8068" "8069" "8070" "8071" "8072" "8073"
## [8074] "8074" "8075" "8076" "8077" "8078" "8079" "8080" "8081" "8082"
## [8083] "8083" "8084" "8085" "8086" "8087" "8088" "8089" "8090" "8091"
## [8092] "8092" "8093" "8094" "8095" "8096" "8097" "8098" "8099" "8100"
## [8101] "8101" "8102" "8103" "8104" "8105" "8106" "8107" "8108" "8109"
## [8110] "8110" "8111" "8112" "8113" "8114" "8115" "8116" "8117" "8118"
## [8119] "8119" "8120" "8121" "8122" "8123" "8124" "8125" "8126" "8127"
## [8128] "8128" "8129" "8130" "8131" "8132" "8133" "8134" "8135" "8136"
## [8137] "8137" "8138" "8139" "8140" "8141" "8142" "8143" "8144" "8145"
## [8146] "8146" "8147" "8148" "8149" "8150" "8151" "8152" "8153" "8154"
## [8155] "8155" "8156" "8157" "8158" "8159" "8160" "8161" "8162" "8163"
## [8164] "8164" "8165" "8166" "8167" "8168" "8169" "8170" "8171" "8172"
## [8173] "8173" "8174" "8175" "8176" "8177" "8178" "8179" "8180" "8181"
## [8182] "8182" "8183" "8184" "8185" "8186" "8187" "8188" "8189" "8190"
## [8191] "8191" "8192" "8193" "8194" "8195" "8196" "8197" "8198" "8199"
## [8200] "8200" "8201" "8202" "8203" "8204" "8205" "8206" "8207" "8208"
## [8209] "8209" "8210" "8211" "8212" "8213" "8214" "8215" "8216" "8217"
## [8218] "8218" "8219" "8220" "8221" "8222" "8223" "8224" "8225" "8226"
## [8227] "8227" "8228" "8229" "8230" "8231" "8232" "8233" "8234" "8235"
## [8236] "8236" "8237" "8238" "8239" "8240" "8241" "8242" "8243" "8244"
## [8245] "8245" "8246" "8247" "8248" "8249" "8250" "8251" "8252" "8253"
## [8254] "8254" "8255" "8256" "8257" "8258" "8259" "8260" "8261" "8262"
## [8263] "8263" "8264" "8265" "8266" "8267" "8268" "8269" "8270" "8271"
## [8272] "8272" "8273" "8274" "8275" "8276" "8277" "8278" "8279" "8280"
## [8281] "8281" "8282" "8283" "8284" "8285" "8286" "8287" "8288" "8289"
## [8290] "8290" "8291" "8292" "8293" "8294" "8295" "8296" "8297" "8298"
## [8299] "8299" "8300" "8301" "8302" "8303" "8304" "8305" "8306" "8307"
## [8308] "8308" "8309" "8310" "8311" "8312" "8313" "8314" "8315" "8316"
## [8317] "8317" "8318" "8319" "8320" "8321" "8322" "8323" "8324" "8325"
## [8326] "8326" "8327" "8328" "8329" "8330" "8331" "8332" "8333" "8334"
## [8335] "8335" "8336" "8337" "8338" "8339" "8340" "8341" "8342" "8343"
## [8344] "8344" "8345" "8346" "8347" "8348" "8349" "8350" "8351" "8352"
## [8353] "8353" "8354" "8355" "8356" "8357" "8358" "8359" "8360" "8361"
## [8362] "8362" "8363" "8364" "8365" "8366" "8367" "8368" "8369" "8370"
## [8371] "8371" "8372" "8373" "8374" "8375" "8376" "8377" "8378" "8379"
## [8380] "8380" "8381" "8382" "8383" "8384" "8385" "8386" "8387" "8388"
## [8389] "8389" "8390" "8391" "8392" "8393" "8394" "8395" "8396" "8397"
## [8398] "8398" "8399" "8400" "8401" "8402" "8403" "8404" "8405" "8406"
## [8407] "8407" "8408" "8409" "8410" "8411" "8412" "8413" "8414" "8415"
## [8416] "8416" "8417" "8418" "8419" "8420" "8421" "8422" "8423" "8424"
## [8425] "8425" "8426" "8427" "8428" "8429" "8430" "8431" "8432" "8433"
## [8434] "8434" "8435" "8436" "8437" "8438" "8439" "8440" "8441" "8442"
## [8443] "8443" "8444" "8445" "8446" "8447" "8448" "8449" "8450" "8451"
## [8452] "8452" "8453" "8454" "8455" "8456" "8457" "8458" "8459" "8460"
## [8461] "8461" "8462" "8463" "8464" "8465" "8466" "8467" "8468" "8469"
## [8470] "8470" "8471" "8472" "8473" "8474" "8475" "8476" "8477" "8478"
## [8479] "8479" "8480" "8481" "8482" "8483" "8484" "8485" "8486" "8487"
## [8488] "8488" "8489" "8490" "8491" "8492" "8493" "8494" "8495" "8496"
## [8497] "8497" "8498" "8499" "8500" "8501" "8502" "8503" "8504" "8505"
## [8506] "8506" "8507" "8508" "8509" "8510" "8511" "8512" "8513" "8514"
## [8515] "8515" "8516" "8517" "8518" "8519" "8520" "8521" "8522" "8523"
## [8524] "8524" "8525" "8526" "8527" "8528" "8529" "8530" "8531" "8532"
## [8533] "8533" "8534" "8535" "8536" "8537" "8538" "8539" "8540" "8541"
## [8542] "8542" "8543" "8544" "8545" "8546" "8547" "8548" "8549" "8550"
## [8551] "8551" "8552" "8553" "8554" "8555" "8556" "8557" "8558" "8559"
## [8560] "8560" "8561" "8562" "8563" "8564" "8565" "8566" "8567" "8568"
## [8569] "8569" "8570" "8571" "8572" "8573" "8574" "8575" "8576" "8577"
## [8578] "8578" "8579" "8580" "8581" "8582" "8583" "8584" "8585" "8586"
## [8587] "8587" "8588" "8589" "8590" "8591" "8592" "8593" "8594" "8595"
## [8596] "8596" "8597" "8598" "8599" "8600" "8601" "8602" "8603" "8604"
## [8605] "8605" "8606" "8607" "8608" "8609" "8610" "8611" "8612" "8613"
## [8614] "8614" "8615" "8616" "8617" "8618" "8619" "8620" "8621" "8622"
## [8623] "8623" "8624" "8625" "8626" "8627" "8628" "8629" "8630" "8631"
## [8632] "8632" "8633" "8634" "8635" "8636" "8637" "8638" "8639" "8640"
## [8641] "8641" "8642" "8643" "8644" "8645" "8646" "8647" "8648" "8649"
## [8650] "8650" "8651" "8652" "8653" "8654" "8655" "8656" "8657" "8658"
## [8659] "8659" "8660" "8661" "8662" "8663" "8664" "8665" "8666" "8667"
## [8668] "8668" "8669" "8670" "8671" "8672" "8673" "8674" "8675" "8676"
## [8677] "8677" "8678" "8679" "8680" "8681" "8682" "8683" "8684" "8685"
## [8686] "8686" "8687" "8688" "8689" "8690" "8691" "8692" "8693" "8694"
## [8695] "8695" "8696" "8697" "8698" "8699" "8700" "8701" "8702" "8703"
## [8704] "8704" "8705" "8706" "8707" "8708" "8709" "8710" "8711" "8712"
## [8713] "8713" "8714" "8715" "8716" "8717" "8718" "8719" "8720" "8721"
## [8722] "8722" "8723" "8724" "8725" "8726" "8727" "8728" "8729" "8730"
## [8731] "8731" "8732" "8733" "8734" "8735" "8736" "8737" "8738" "8739"
## [8740] "8740" "8741" "8742" "8743" "8744" "8745" "8746" "8747" "8748"
## [8749] "8749" "8750" "8751" "8752" "8753" "8754" "8755" "8756" "8757"
## [8758] "8758" "8759" "8760" "8761" "8762" "8763" "8764" "8765" "8766"
## [8767] "8767" "8768" "8769" "8770" "8771" "8772" "8773" "8774" "8775"
## [8776] "8776" "8777" "8778" "8779" "8780" "8781" "8782" "8783" "8784"
## [8785] "8785" "8786" "8787" "8788" "8789" "8790" "8791" "8792" "8793"
## [8794] "8794" "8795" "8796" "8797" "8798" "8799" "8800" "8801" "8802"
## [8803] "8803" "8804" "8805" "8806" "8807" "8808" "8809" "8810" "8811"
## [8812] "8812" "8813" "8814" "8815" "8816" "8817" "8818" "8819" "8820"
## [8821] "8821" "8822" "8823" "8824" "8825" "8826" "8827" "8828" "8829"
## [8830] "8830" "8831" "8832" "8833" "8834" "8835" "8836" "8837" "8838"
## [8839] "8839" "8840" "8841" "8842" "8843" "8844" "8845" "8846" "8847"
## [8848] "8848" "8849" "8850" "8851" "8852" "8853" "8854" "8855" "8856"
## [8857] "8857" "8858" "8859" "8860" "8861" "8862" "8863" "8864" "8865"
## [8866] "8866" "8867" "8868" "8869" "8870" "8871" "8872" "8873" "8874"
## [8875] "8875" "8876" "8877" "8878" "8879" "8880" "8881" "8882" "8883"
## [8884] "8884" "8885" "8886" "8887" "8888" "8889" "8890" "8891" "8892"
## [8893] "8893" "8894" "8895" "8896" "8897" "8898" "8899" "8900" "8901"
## [8902] "8902" "8903" "8904" "8905" "8906" "8907" "8908" "8909" "8910"
## [8911] "8911" "8912" "8913" "8914" "8915" "8916" "8917" "8918" "8919"
## [8920] "8920" "8921" "8922" "8923" "8924" "8925" "8926" "8927" "8928"
## [8929] "8929" "8930" "8931" "8932" "8933" "8934" "8935" "8936" "8937"
## [8938] "8938" "8939" "8940" "8941" "8942" "8943" "8944" "8945" "8946"
## [8947] "8947" "8948" "8949" "8950" "8951" "8952" "8953" "8954" "8955"
## [8956] "8956" "8957" "8958" "8959" "8960" "8961" "8962" "8963" "8964"
## [8965] "8965" "8966" "8967" "8968" "8969" "8970" "8971" "8972" "8973"
## [8974] "8974" "8975" "8976" "8977" "8978" "8979" "8980" "8981" "8982"
## [8983] "8983" "8984" "8985" "8986" "8987" "8988" "8989" "8990" "8991"
## [8992] "8992" "8993" "8994" "8995" "8996" "8997" "8998" "8999" "9000"
## [9001] "9001" "9002" "9003" "9004" "9005" "9006" "9007" "9008" "9009"
## [9010] "9010" "9011" "9012" "9013" "9014" "9015" "9016" "9017" "9018"
## [9019] "9019" "9020" "9021" "9022" "9023" "9024" "9025" "9026" "9027"
## [9028] "9028" "9029" "9030" "9031" "9032" "9033" "9034" "9035" "9036"
## [9037] "9037" "9038" "9039" "9040" "9041" "9042" "9043" "9044" "9045"
## [9046] "9046" "9047" "9048" "9049" "9050" "9051" "9052" "9053" "9054"
## [9055] "9055" "9056" "9057" "9058" "9059" "9060" "9061" "9062" "9063"
## [9064] "9064" "9065" "9066" "9067" "9068" "9069" "9070" "9071" "9072"
## [9073] "9073" "9074" "9075" "9076" "9077" "9078" "9079" "9080" "9081"
## [9082] "9082" "9083" "9084" "9085" "9086" "9087" "9088" "9089" "9090"
## [9091] "9091" "9092" "9093" "9094" "9095" "9096" "9097" "9098" "9099"
## [9100] "9100" "9101" "9102" "9103" "9104" "9105" "9106" "9107" "9108"
## [9109] "9109" "9110" "9111" "9112" "9113" "9114" "9115" "9116" "9117"
## [9118] "9118" "9119" "9120" "9121" "9122" "9123" "9124" "9125" "9126"
## [9127] "9127" "9128" "9129" "9130" "9131" "9132" "9133" "9134" "9135"
## [9136] "9136" "9137" "9138" "9139" "9140" "9141" "9142" "9143" "9144"
## [9145] "9145" "9146" "9147" "9148" "9149" "9150" "9151" "9152" "9153"
## [9154] "9154" "9155" "9156" "9157" "9158" "9159" "9160" "9161" "9162"
## [9163] "9163" "9164" "9165" "9166" "9167" "9168" "9169" "9170" "9171"
## [9172] "9172" "9173" "9174" "9175" "9176" "9177" "9178" "9179" "9180"
## [9181] "9181" "9182" "9183" "9184" "9185" "9186" "9187" "9188" "9189"
## [9190] "9190" "9191" "9192" "9193" "9194" "9195" "9196" "9197" "9198"
## [9199] "9199" "9200" "9201" "9202" "9203" "9204" "9205" "9206" "9207"
## [9208] "9208" "9209" "9210" "9211" "9212" "9213" "9214" "9215" "9216"
## [9217] "9217" "9218" "9219" "9220" "9221" "9222" "9223" "9224" "9225"
## [9226] "9226" "9227" "9228" "9229" "9230" "9231" "9232" "9233" "9234"
## [9235] "9235" "9236" "9237" "9238" "9239" "9240" "9241" "9242" "9243"
## [9244] "9244" "9245" "9246" "9247" "9248" "9249" "9250" "9251" "9252"
## [9253] "9253" "9254" "9255" "9256" "9257" "9258" "9259" "9260" "9261"
## [9262] "9262" "9263" "9264" "9265" "9266" "9267" "9268" "9269" "9270"
## [9271] "9271" "9272" "9273" "9274" "9275" "9276" "9277" "9278" "9279"
## [9280] "9280" "9281" "9282" "9283" "9284" "9285" "9286" "9287" "9288"
## [9289] "9289" "9290" "9291" "9292" "9293" "9294" "9295" "9296" "9297"
## [9298] "9298" "9299" "9300" "9301" "9302" "9303" "9304" "9305" "9306"
## [9307] "9307" "9308" "9309" "9310" "9311" "9312" "9313" "9314" "9315"
## [9316] "9316" "9317" "9318" "9319" "9320" "9321" "9322" "9323" "9324"
## [9325] "9325" "9326" "9327" "9328" "9329" "9330" "9331" "9332" "9333"
## [9334] "9334" "9335" "9336" "9337" "9338" "9339" "9340" "9341" "9342"
## [9343] "9343" "9344" "9345" "9346" "9347" "9348" "9349" "9350" "9351"
## [9352] "9352" "9353" "9354" "9355" "9356" "9357" "9358" "9359" "9360"
## [9361] "9361" "9362" "9363" "9364" "9365" "9366" "9367" "9368" "9369"
## [9370] "9370" "9371" "9372" "9373" "9374" "9375" "9376" "9377" "9378"
## [9379] "9379" "9380" "9381" "9382" "9383" "9384" "9385" "9386" "9387"
## [9388] "9388" "9389" "9390" "9391" "9392" "9393" "9394" "9395" "9396"
## [9397] "9397" "9398" "9399" "9400" "9401" "9402" "9403" "9404" "9405"
## [9406] "9406" "9407" "9408" "9409" "9410" "9411" "9412" "9413" "9414"
## [9415] "9415" "9416" "9417" "9418" "9419" "9420" "9421" "9422" "9423"
## [9424] "9424" "9425" "9426" "9427" "9428" "9429" "9430" "9431" "9432"
## [9433] "9433" "9434" "9435" "9436" "9437" "9438" "9439" "9440" "9441"
## [9442] "9442" "9443" "9444" "9445" "9446" "9447" "9448" "9449" "9450"
## [9451] "9451" "9452" "9453" "9454" "9455" "9456" "9457" "9458" "9459"
## [9460] "9460" "9461" "9462" "9463" "9464" "9465" "9466" "9467" "9468"
## [9469] "9469" "9470" "9471" "9472" "9473" "9474" "9475" "9476" "9477"
## [9478] "9478" "9479" "9480" "9481" "9482" "9483" "9484" "9485" "9486"
## [9487] "9487" "9488" "9489" "9490" "9491" "9492" "9493" "9494" "9495"
## [9496] "9496" "9497" "9498" "9499" "9500" "9501" "9502" "9503" "9504"
## [9505] "9505" "9506" "9507" "9508" "9509" "9510" "9511" "9512" "9513"
## [9514] "9514" "9515" "9516" "9517" "9518" "9519" "9520" "9521" "9522"
## [9523] "9523" "9524" "9525" "9526" "9527" "9528" "9529" "9530" "9531"
## [9532] "9532" "9533" "9534" "9535" "9536" "9537" "9538" "9539" "9540"
## [9541] "9541" "9542" "9543" "9544" "9545" "9546" "9547" "9548" "9549"
## [9550] "9550" "9551" "9552" "9553" "9554" "9555" "9556" "9557" "9558"
## [9559] "9559" "9560" "9561" "9562" "9563" "9564" "9565" "9566" "9567"
## [9568] "9568" "9569" "9570" "9571" "9572" "9573" "9574" "9575" "9576"
## [9577] "9577" "9578" "9579" "9580" "9581" "9582" "9583" "9584" "9585"
## [9586] "9586" "9587" "9588" "9589" "9590" "9591" "9592" "9593" "9594"
## [9595] "9595" "9596" "9597" "9598" "9599" "9600" "9601" "9602" "9603"
## [9604] "9604" "9605" "9606" "9607" "9608" "9609" "9610" "9611" "9612"
## [9613] "9613" "9614" "9615" "9616" "9617" "9618" "9619" "9620" "9621"
## [9622] "9622" "9623" "9624" "9625" "9626" "9627" "9628" "9629" "9630"
## [9631] "9631" "9632" "9633" "9634" "9635" "9636" "9637" "9638" "9639"
## [9640] "9640" "9641" "9642" "9643" "9644" "9645" "9646" "9647" "9648"
## [9649] "9649" "9650" "9651" "9652" "9653" "9654" "9655" "9656" "9657"
## [9658] "9658" "9659" "9660" "9661" "9662" "9663" "9664" "9665" "9666"
## [9667] "9667" "9668" "9669" "9670" "9671" "9672" "9673" "9674" "9675"
## [9676] "9676" "9677" "9678" "9679" "9680" "9681" "9682" "9683" "9684"
## [9685] "9685" "9686" "9687" "9688" "9689" "9690" "9691" "9692" "9693"
## [9694] "9694" "9695" "9696" "9697" "9698" "9699" "9700" "9701" "9702"
## [9703] "9703" "9704" "9705" "9706" "9707" "9708" "9709" "9710" "9711"
## [9712] "9712" "9713" "9714" "9715" "9716" "9717" "9718" "9719" "9720"
## [9721] "9721" "9722" "9723" "9724" "9725" "9726" "9727" "9728" "9729"
## [9730] "9730" "9731" "9732" "9733" "9734" "9735" "9736" "9737" "9738"
## [9739] "9739" "9740" "9741" "9742" "9743" "9744" "9745" "9746" "9747"
## [9748] "9748" "9749" "9750" "9751" "9752" "9753" "9754" "9755" "9756"
## [9757] "9757" "9758" "9759" "9760" "9761" "9762" "9763" "9764" "9765"
## [9766] "9766" "9767" "9768" "9769" "9770" "9771" "9772" "9773" "9774"
## [9775] "9775" "9776" "9777" "9778" "9779" "9780" "9781" "9782" "9783"
## [9784] "9784" "9785" "9786" "9787" "9788" "9789" "9790" "9791" "9792"
## [9793] "9793" "9794" "9795" "9796" "9797" "9798" "9799" "9800" "9801"
## [9802] "9802" "9803" "9804" "9805" "9806" "9807" "9808" "9809" "9810"
## [9811] "9811" "9812" "9813" "9814" "9815" "9816" "9817" "9818" "9819"
## [9820] "9820" "9821" "9822" "9823" "9824" "9825" "9826" "9827" "9828"
## [9829] "9829" "9830" "9831" "9832" "9833" "9834" "9835" "9836" "9837"
## [9838] "9838" "9839" "9840" "9841" "9842" "9843" "9844" "9845" "9846"
## [9847] "9847" "9848" "9849" "9850" "9851" "9852" "9853" "9854" "9855"
## [9856] "9856" "9857" "9858" "9859" "9860" "9861" "9862" "9863" "9864"
## [9865] "9865" "9866" "9867" "9868" "9869" "9870" "9871" "9872" "9873"
## [9874] "9874" "9875" "9876" "9877" "9878" "9879" "9880" "9881" "9882"
## [9883] "9883" "9884" "9885" "9886" "9887" "9888" "9889" "9890" "9891"
## [9892] "9892" "9893" "9894" "9895" "9896" "9897" "9898" "9899" "9900"
## [9901] "9901" "9902" "9903" "9904" "9905" "9906" "9907" "9908" "9909"
## [9910] "9910" "9911" "9912" "9913" "9914" "9915" "9916" "9917" "9918"
## [9919] "9919" "9920" "9921" "9922" "9923" "9924" "9925" "9926" "9927"
## [9928] "9928" "9929" "9930" "9931" "9932" "9933" "9934" "9935" "9936"
## [9937] "9937" "9938" "9939" "9940" "9941" "9942" "9943" "9944" "9945"
## [9946] "9946" "9947" "9948" "9949" "9950" "9951" "9952" "9953" "9954"
## [9955] "9955" "9956" "9957" "9958" "9959" "9960" "9961" "9962" "9963"
## [9964] "9964" "9965" "9966" "9967" "9968" "9969" "9970" "9971" "9972"
## [9973] "9973" "9974" "9975" "9976" "9977" "9978" "9979" "9980" "9981"
## [9982] "9982" "9983" "9984" "9985" "9986" "9987" "9988" "9989" "9990"
## [9991] "9991" "9992" "9993" "9994" "9995" "9996" "9997" "9998" "9999"
## [10000] "10000" "10001" "10002" "10003" "10004" "10005" "10006" "10007" "10008"
## [10009] "10009" "10010" "10011" "10012" "10013" "10014" "10015" "10016" "10017"
## [10018] "10018" "10019" "10020" "10021" "10022" "10023" "10024" "10025" "10026"
## [10027] "10027" "10028" "10029" "10030" "10031" "10032" "10033" "10034" "10035"
## [10036] "10036" "10037" "10038" "10039" "10040" "10041" "10042" "10043" "10044"
## [10045] "10045" "10046" "10047" "10048" "10049" "10050" "10051" "10052" "10053"
## [10054] "10054" "10055" "10056" "10057" "10058" "10059" "10060" "10061" "10062"
## [10063] "10063" "10064" "10065" "10066" "10067" "10068" "10069" "10070" "10071"
## [10072] "10072" "10073" "10074" "10075" "10076" "10077" "10078" "10079" "10080"
## [10081] "10081" "10082" "10083" "10084" "10085" "10086" "10087" "10088" "10089"
## [10090] "10090" "10091" "10092" "10093" "10094" "10095" "10096" "10097" "10098"
## [10099] "10099" "10100" "10101" "10102" "10103" "10104" "10105" "10106" "10107"
## [10108] "10108" "10109" "10110" "10111" "10112" "10113" "10114" "10115" "10116"
## [10117] "10117" "10118" "10119" "10120" "10121" "10122" "10123" "10124" "10125"
## [10126] "10126" "10127" "10128" "10129" "10130" "10131" "10132" "10133" "10134"
## [10135] "10135" "10136" "10137" "10138" "10139" "10140" "10141" "10142" "10143"
## [10144] "10144" "10145" "10146" "10147" "10148" "10149" "10150" "10151" "10152"
## [10153] "10153" "10154" "10155" "10156" "10157" "10158" "10159" "10160" "10161"
## [10162] "10162" "10163" "10164" "10165" "10166" "10167" "10168" "10169" "10170"
## [10171] "10171" "10172" "10173" "10174" "10175" "10176" "10177" "10178" "10179"
## [10180] "10180" "10181" "10182" "10183" "10184" "10185" "10186" "10187" "10188"
## [10189] "10189" "10190" "10191" "10192" "10193" "10194" "10195" "10196" "10197"
## [10198] "10198" "10199" "10200" "10201" "10202" "10203" "10204" "10205" "10206"
## [10207] "10207" "10208" "10209" "10210" "10211" "10212" "10213" "10214" "10215"
## [10216] "10216" "10217" "10218" "10219" "10220" "10221" "10222" "10223" "10224"
## [10225] "10225" "10226" "10227" "10228" "10229" "10230" "10231" "10232" "10233"
## [10234] "10234" "10235" "10236" "10237" "10238" "10239" "10240" "10241" "10242"
## [10243] "10243" "10244" "10245" "10246" "10247" "10248" "10249" "10250" "10251"
## [10252] "10252" "10253" "10254" "10255" "10256" "10257" "10258" "10259" "10260"
## [10261] "10261" "10262" "10263" "10264" "10265" "10266" "10267" "10268" "10269"
## [10270] "10270" "10271" "10272" "10273" "10274" "10275" "10276" "10277" "10278"
## [10279] "10279" "10280" "10281" "10282" "10283" "10284" "10285" "10286" "10287"
## [10288] "10288" "10289" "10290" "10291" "10292" "10293" "10294" "10295" "10296"
## [10297] "10297" "10298" "10299" "10300" "10301" "10302" "10303" "10304" "10305"
## [10306] "10306" "10307" "10308" "10309" "10310" "10311" "10312" "10313" "10314"
## [10315] "10315" "10316" "10317" "10318" "10319" "10320" "10321" "10322" "10323"
## [10324] "10324" "10325" "10326" "10327" "10328" "10329" "10330" "10331" "10332"
## [10333] "10333" "10334" "10335" "10336" "10337" "10338" "10339" "10340" "10341"
## [10342] "10342" "10343" "10344" "10345" "10346" "10347" "10348" "10349" "10350"
## [10351] "10351" "10352" "10353" "10354" "10355" "10356" "10357" "10358" "10359"
## [10360] "10360" "10361" "10362" "10363" "10364" "10365" "10366" "10367" "10368"
## [10369] "10369" "10370" "10371" "10372" "10373" "10374" "10375" "10376" "10377"
## [10378] "10378" "10379" "10380" "10381" "10382" "10383" "10384" "10385" "10386"
## [10387] "10387" "10388" "10389" "10390" "10391" "10392" "10393" "10394" "10395"
## [10396] "10396" "10397" "10398" "10399" "10400" "10401" "10402" "10403" "10404"
## [10405] "10405" "10406" "10407" "10408" "10409" "10410" "10411" "10412" "10413"
## [10414] "10414" "10415" "10416" "10417" "10418" "10419" "10420" "10421" "10422"
## [10423] "10423" "10424" "10425" "10426" "10427" "10428" "10429" "10430" "10431"
## [10432] "10432" "10433" "10434" "10435" "10436" "10437" "10438" "10439" "10440"
## [10441] "10441" "10442" "10443" "10444" "10445" "10446" "10447" "10448" "10449"
## [10450] "10450" "10451" "10452" "10453" "10454" "10455" "10456" "10457" "10458"
## [10459] "10459" "10460" "10461" "10462" "10463" "10464" "10465" "10466" "10467"
## [10468] "10468" "10469" "10470" "10471" "10472" "10473" "10474" "10475" "10476"
## [10477] "10477" "10478" "10479" "10480" "10481" "10482" "10483" "10484" "10485"
## [10486] "10486" "10487" "10488" "10489" "10490" "10491" "10492" "10493" "10494"
## [10495] "10495" "10496" "10497" "10498" "10499" "10500" "10501" "10502" "10503"
## [10504] "10504" "10505" "10506" "10507" "10508" "10509" "10510" "10511" "10512"
## [10513] "10513" "10514" "10515" "10516" "10517" "10518" "10519" "10520" "10521"
## [10522] "10522" "10523" "10524" "10525" "10526" "10527" "10528" "10529" "10530"
## [10531] "10531" "10532" "10533" "10534" "10535" "10536" "10537" "10538" "10539"
## [10540] "10540" "10541" "10542" "10543" "10544" "10545" "10546" "10547" "10548"
## [10549] "10549" "10550" "10551" "10552" "10553" "10554" "10555" "10556" "10557"
## [10558] "10558" "10559" "10560" "10561" "10562" "10563" "10564" "10565" "10566"
## [10567] "10567" "10568" "10569" "10570" "10571" "10572" "10573" "10574" "10575"
## [10576] "10576" "10577" "10578" "10579" "10580" "10581" "10582" "10583" "10584"
## [10585] "10585" "10586" "10587" "10588" "10589" "10590" "10591" "10592" "10593"
## [10594] "10594" "10595" "10596" "10597" "10598" "10599" "10600" "10601" "10602"
## [10603] "10603" "10604" "10605" "10606" "10607" "10608" "10609" "10610" "10611"
## [10612] "10612" "10613" "10614" "10615" "10616" "10617" "10618" "10619" "10620"
## [10621] "10621" "10622" "10623" "10624" "10625" "10626" "10627" "10628" "10629"
## [10630] "10630" "10631" "10632" "10633" "10634" "10635" "10636" "10637" "10638"
## [10639] "10639" "10640" "10641" "10642" "10643" "10644" "10645" "10646" "10647"
## [10648] "10648" "10649" "10650" "10651" "10652" "10653" "10654" "10655" "10656"
## [10657] "10657" "10658" "10659" "10660" "10661" "10662" "10663" "10664" "10665"
## [10666] "10666" "10667" "10668" "10669" "10670" "10671" "10672" "10673" "10674"
## [10675] "10675" "10676" "10677" "10678" "10679" "10680" "10681" "10682" "10683"
## [10684] "10684" "10685" "10686" "10687" "10688" "10689" "10690" "10691" "10692"
## [10693] "10693" "10694" "10695" "10696" "10697" "10698" "10699" "10700" "10701"
## [10702] "10702" "10703" "10704" "10705" "10706" "10707" "10708" "10709" "10710"
## [10711] "10711" "10712" "10713" "10714" "10715" "10716" "10717" "10718" "10719"
## [10720] "10720" "10721" "10722" "10723" "10724" "10725" "10726" "10727" "10728"
## [10729] "10729" "10730" "10731" "10732" "10733" "10734" "10735" "10736" "10737"
## [10738] "10738" "10739" "10740" "10741" "10742" "10743" "10744" "10745" "10746"
## [10747] "10747" "10748" "10749" "10750" "10751" "10752" "10753" "10754" "10755"
## [10756] "10756" "10757" "10758" "10759" "10760" "10761" "10762" "10763" "10764"
## [10765] "10765" "10766" "10767" "10768" "10769" "10770" "10771" "10772" "10773"
## [10774] "10774" "10775" "10776" "10777" "10778" "10779" "10780" "10781" "10782"
## [10783] "10783" "10784" "10785" "10786" "10787" "10788" "10789" "10790" "10791"
## [10792] "10792" "10793" "10794" "10795" "10796" "10797" "10798" "10799" "10800"
## [10801] "10801" "10802" "10803" "10804" "10805" "10806" "10807" "10808" "10809"
## [10810] "10810" "10811" "10812" "10813" "10814" "10815" "10816" "10817" "10818"
## [10819] "10819" "10820" "10821" "10822" "10823" "10824" "10825" "10826" "10827"
## [10828] "10828" "10829" "10830" "10831" "10832" "10833" "10834" "10835" "10836"
## [10837] "10837" "10838" "10839" "10840" "10841" "10842" "10843" "10844" "10845"
## [10846] "10846" "10847" "10848" "10849" "10850" "10851" "10852" "10853" "10854"
## [10855] "10855" "10856" "10857" "10858" "10859" "10860" "10861" "10862" "10863"
## [10864] "10864" "10865" "10866" "10867" "10868" "10869" "10870" "10871" "10872"
## [10873] "10873" "10874" "10875" "10876" "10877" "10878" "10879" "10880" "10881"
## [10882] "10882" "10883" "10884" "10885" "10886" "10887" "10888" "10889" "10890"
## [10891] "10891" "10892" "10893" "10894" "10895" "10896" "10897" "10898" "10899"
## [10900] "10900" "10901" "10902" "10903" "10904" "10905" "10906" "10907" "10908"
## [10909] "10909" "10910" "10911" "10912" "10913" "10914" "10915" "10916" "10917"
## [10918] "10918" "10919" "10920" "10921" "10922" "10923" "10924" "10925" "10926"
## [10927] "10927" "10928" "10929" "10930" "10931" "10932" "10933" "10934" "10935"
## [10936] "10936" "10937" "10938" "10939" "10940" "10941" "10942" "10943" "10944"
## [10945] "10945" "10946" "10947" "10948" "10949" "10950" "10951" "10952" "10953"
## [10954] "10954" "10955" "10956" "10957" "10958" "10959" "10960" "10961" "10962"
## [10963] "10963" "10964" "10965" "10966" "10967" "10968" "10969" "10970" "10971"
## [10972] "10972" "10973" "10974" "10975" "10976" "10977" "10978" "10979" "10980"
## [10981] "10981" "10982" "10983" "10984" "10985" "10986" "10987" "10988" "10989"
## [10990] "10990" "10991" "10992" "10993" "10994" "10995" "10996" "10997" "10998"
## [10999] "10999" "11000" "11001" "11002" "11003" "11004" "11005" "11006" "11007"
## [11008] "11008" "11009" "11010" "11011" "11012" "11013" "11014" "11015" "11016"
## [11017] "11017" "11018" "11019" "11020" "11021" "11022" "11023" "11024" "11025"
## [11026] "11026" "11027" "11028" "11029" "11030" "11031" "11032" "11033" "11034"
## [11035] "11035" "11036" "11037" "11038" "11039" "11040" "11041" "11042" "11043"
## [11044] "11044" "11045" "11046" "11047" "11048" "11049" "11050" "11051" "11052"
## [11053] "11053" "11054" "11055" "11056" "11057" "11058" "11059" "11060" "11061"
## [11062] "11062" "11063" "11064" "11065" "11066" "11067" "11068" "11069" "11070"
## [11071] "11071" "11072" "11073" "11074" "11075" "11076" "11077" "11078" "11079"
## [11080] "11080" "11081" "11082" "11083" "11084" "11085" "11086" "11087" "11088"
## [11089] "11089" "11090" "11091" "11092" "11093" "11094" "11095" "11096" "11097"
## [11098] "11098" "11099" "11100" "11101" "11102" "11103" "11104" "11105" "11106"
## [11107] "11107" "11108" "11109" "11110" "11111" "11112" "11113" "11114" "11115"
## [11116] "11116" "11117" "11118" "11119" "11120" "11121" "11122" "11123" "11124"
## [11125] "11125" "11126" "11127" "11128" "11129" "11130" "11131" "11132" "11133"
## [11134] "11134" "11135" "11136" "11137" "11138" "11139" "11140" "11141" "11142"
## [11143] "11143" "11144" "11145" "11146" "11147" "11148" "11149" "11150" "11151"
## [11152] "11152" "11153" "11154" "11155" "11156" "11157" "11158" "11159" "11160"
## [11161] "11161" "11162" "11163" "11164" "11165" "11166" "11167" "11168" "11169"
## [11170] "11170" "11171" "11172" "11173" "11174" "11175" "11176" "11177" "11178"
## [11179] "11179" "11180" "11181" "11182" "11183" "11184" "11185" "11186" "11187"
## [11188] "11188" "11189" "11190" "11191" "11192" "11193" "11194" "11195" "11196"
## [11197] "11197" "11198" "11199" "11200" "11201" "11202" "11203" "11204" "11205"
## [11206] "11206" "11207" "11208" "11209" "11210" "11211" "11212" "11213" "11214"
## [11215] "11215" "11216" "11217" "11218" "11219" "11220" "11221" "11222" "11223"
## [11224] "11224" "11225" "11226" "11227" "11228" "11229" "11230" "11231" "11232"
## [11233] "11233" "11234" "11235" "11236" "11237" "11238" "11239" "11240" "11241"
## [11242] "11242" "11243" "11244" "11245" "11246" "11247" "11248" "11249" "11250"
## [11251] "11251" "11252" "11253" "11254" "11255" "11256" "11257" "11258" "11259"
## [11260] "11260" "11261" "11262" "11263" "11264" "11265" "11266" "11267" "11268"
## [11269] "11269" "11270" "11271" "11272" "11273" "11274" "11275" "11276" "11277"
## [11278] "11278" "11279" "11280" "11281" "11282" "11283" "11284" "11285" "11286"
## [11287] "11287" "11288" "11289" "11290" "11291" "11292" "11293" "11294" "11295"
## [11296] "11296" "11297" "11298" "11299" "11300" "11301" "11302" "11303" "11304"
## [11305] "11305" "11306" "11307" "11308" "11309" "11310" "11311" "11312" "11313"
## [11314] "11314" "11315" "11316" "11317" "11318" "11319" "11320" "11321" "11322"
## [11323] "11323" "11324" "11325" "11326" "11327" "11328" "11329" "11330" "11331"
## [11332] "11332" "11333" "11334" "11335" "11336" "11337" "11338" "11339" "11340"
## [11341] "11341" "11342" "11343" "11344" "11345" "11346" "11347" "11348" "11349"
## [11350] "11350" "11351" "11352" "11353" "11354" "11355" "11356" "11357" "11358"
## [11359] "11359" "11360" "11361" "11362" "11363" "11364" "11365" "11366" "11367"
## [11368] "11368" "11369" "11370" "11371" "11372" "11373" "11374" "11375" "11376"
## [11377] "11377" "11378" "11379" "11380" "11381" "11382" "11383" "11384" "11385"
## [11386] "11386" "11387" "11388" "11389" "11390" "11391" "11392" "11393" "11394"
## [11395] "11395" "11396" "11397" "11398" "11399" "11400" "11401" "11402" "11403"
## [11404] "11404" "11405" "11406" "11407" "11408" "11409" "11410" "11411" "11412"
## [11413] "11413" "11414" "11415" "11416" "11417" "11418" "11419" "11420" "11421"
## [11422] "11422" "11423" "11424" "11425" "11426" "11427" "11428" "11429" "11430"
## [11431] "11431" "11432" "11433" "11434" "11435" "11436" "11437" "11438" "11439"
## [11440] "11440" "11441" "11442" "11443" "11444" "11445" "11446" "11447" "11448"
## [11449] "11449" "11450" "11451" "11452" "11453" "11454" "11455" "11456" "11457"
## [11458] "11458" "11459" "11460" "11461" "11462" "11463" "11464" "11465" "11466"
## [11467] "11467" "11468" "11469" "11470" "11471" "11472" "11473" "11474" "11475"
## [11476] "11476" "11477" "11478" "11479" "11480" "11481" "11482" "11483" "11484"
## [11485] "11485" "11486" "11487" "11488" "11489" "11490" "11491" "11492" "11493"
## [11494] "11494" "11495" "11496" "11497" "11498" "11499" "11500" "11501" "11502"
## [11503] "11503" "11504" "11505" "11506" "11507" "11508" "11509" "11510" "11511"
## [11512] "11512" "11513" "11514" "11515" "11516" "11517" "11518" "11519" "11520"
## [11521] "11521" "11522" "11523" "11524" "11525" "11526" "11527" "11528" "11529"
## [11530] "11530" "11531" "11532" "11533" "11534" "11535" "11536" "11537" "11538"
## [11539] "11539" "11540" "11541" "11542" "11543" "11544" "11545" "11546" "11547"
## [11548] "11548" "11549" "11550" "11551" "11552" "11553" "11554" "11555" "11556"
## [11557] "11557" "11558" "11559" "11560" "11561" "11562" "11563" "11564" "11565"
## [11566] "11566" "11567" "11568" "11569" "11570" "11571" "11572" "11573" "11574"
## [11575] "11575" "11576" "11577" "11578" "11579" "11580" "11581" "11582" "11583"
## [11584] "11584" "11585" "11586" "11587" "11588" "11589" "11590" "11591" "11592"
## [11593] "11593" "11594" "11595" "11596" "11597" "11598" "11599" "11600" "11601"
## [11602] "11602" "11603" "11604" "11605" "11606" "11607" "11608" "11609" "11610"
## [11611] "11611" "11612" "11613" "11614" "11615" "11616" "11617" "11618" "11619"
## [11620] "11620" "11621" "11622" "11623" "11624" "11625" "11626" "11627" "11628"
## [11629] "11629" "11630" "11631" "11632" "11633" "11634" "11635" "11636" "11637"
## [11638] "11638" "11639" "11640" "11641" "11642" "11643" "11644" "11645" "11646"
## [11647] "11647" "11648" "11649" "11650" "11651" "11652" "11653" "11654" "11655"
## [11656] "11656" "11657" "11658" "11659" "11660" "11661" "11662" "11663" "11664"
## [11665] "11665" "11666" "11667" "11668" "11669" "11670" "11671" "11672" "11673"
## [11674] "11674" "11675" "11676" "11677" "11678" "11679" "11680" "11681" "11682"
## [11683] "11683" "11684" "11685" "11686" "11687" "11688" "11689" "11690" "11691"
## [11692] "11692" "11693" "11694" "11695" "11696" "11697" "11698" "11699" "11700"
## [11701] "11701" "11702" "11703" "11704" "11705" "11706" "11707" "11708" "11709"
## [11710] "11710" "11711" "11712" "11713" "11714" "11715" "11716" "11717" "11718"
## [11719] "11719" "11720" "11721" "11722" "11723" "11724" "11725" "11726" "11727"
## [11728] "11728" "11729" "11730" "11731" "11732" "11733" "11734" "11735" "11736"
## [11737] "11737" "11738" "11739" "11740" "11741" "11742" "11743" "11744" "11745"
## [11746] "11746" "11747" "11748" "11749" "11750" "11751" "11752" "11753" "11754"
## [11755] "11755" "11756" "11757" "11758" "11759" "11760" "11761" "11762" "11763"
## [11764] "11764" "11765" "11766" "11767" "11768" "11769" "11770" "11771" "11772"
## [11773] "11773" "11774" "11775" "11776" "11777" "11778" "11779" "11780" "11781"
## [11782] "11782" "11783" "11784" "11785" "11786" "11787" "11788" "11789" "11790"
## [11791] "11791" "11792" "11793" "11794" "11795" "11796" "11797" "11798" "11799"
## [11800] "11800" "11801" "11802" "11803" "11804" "11805" "11806" "11807" "11808"
## [11809] "11809" "11810" "11811" "11812" "11813" "11814" "11815" "11816" "11817"
## [11818] "11818" "11819" "11820" "11821" "11822" "11823" "11824" "11825" "11826"
## [11827] "11827" "11828" "11829" "11830" "11831" "11832" "11833" "11834" "11835"
## [11836] "11836" "11837" "11838" "11839" "11840" "11841" "11842" "11843" "11844"
## [11845] "11845" "11846" "11847" "11848" "11849" "11850" "11851" "11852" "11853"
## [11854] "11854" "11855" "11856" "11857" "11858" "11859" "11860" "11861" "11862"
## [11863] "11863" "11864" "11865" "11866" "11867" "11868" "11869" "11870" "11871"
## [11872] "11872" "11873" "11874" "11875" "11876" "11877" "11878" "11879" "11880"
## [11881] "11881" "11882" "11883" "11884" "11885" "11886" "11887" "11888" "11889"
## [11890] "11890" "11891" "11892" "11893" "11894" "11895" "11896" "11897" "11898"
## [11899] "11899" "11900" "11901" "11902" "11903" "11904" "11905" "11906" "11907"
## [11908] "11908" "11909" "11910" "11911" "11912" "11913" "11914" "11915" "11916"
## [11917] "11917" "11918" "11919" "11920" "11921" "11922" "11923" "11924" "11925"
## [11926] "11926" "11927" "11928" "11929" "11930" "11931" "11932" "11933" "11934"
## [11935] "11935" "11936" "11937" "11938" "11939" "11940" "11941" "11942" "11943"
## [11944] "11944" "11945" "11946" "11947" "11948" "11949" "11950" "11951" "11952"
## [11953] "11953" "11954" "11955" "11956" "11957" "11958" "11959" "11960" "11961"
## [11962] "11962" "11963" "11964" "11965" "11966" "11967" "11968" "11969" "11970"
## [11971] "11971" "11972" "11973" "11974" "11975" "11976" "11977" "11978" "11979"
## [11980] "11980" "11981" "11982" "11983" "11984" "11985" "11986" "11987" "11988"
## [11989] "11989" "11990" "11991" "11992" "11993" "11994" "11995" "11996" "11997"
## [11998] "11998" "11999" "12000" "12001" "12002" "12003" "12004" "12005" "12006"
## [12007] "12007" "12008" "12009" "12010" "12011" "12012" "12013" "12014" "12015"
## [12016] "12016" "12017" "12018" "12019" "12020" "12021" "12022" "12023" "12024"
## [12025] "12025" "12026" "12027" "12028" "12029" "12030" "12031" "12032" "12033"
## [12034] "12034" "12035" "12036" "12037" "12038" "12039" "12040" "12041" "12042"
## [12043] "12043" "12044" "12045" "12046" "12047" "12048" "12049" "12050" "12051"
## [12052] "12052" "12053" "12054" "12055" "12056" "12057" "12058" "12059" "12060"
## [12061] "12061" "12062" "12063" "12064" "12065" "12066" "12067" "12068" "12069"
## [12070] "12070" "12071" "12072" "12073" "12074" "12075" "12076" "12077" "12078"
## [12079] "12079" "12080" "12081" "12082" "12083" "12084" "12085" "12086" "12087"
## [12088] "12088" "12089" "12090" "12091" "12092" "12093" "12094" "12095" "12096"
## [12097] "12097" "12098" "12099" "12100" "12101" "12102" "12103" "12104" "12105"
## [12106] "12106" "12107" "12108" "12109" "12110" "12111" "12112" "12113" "12114"
## [12115] "12115" "12116" "12117" "12118" "12119" "12120" "12121" "12122" "12123"
## [12124] "12124" "12125" "12126" "12127" "12128" "12129" "12130" "12131" "12132"
## [12133] "12133" "12134" "12135" "12136" "12137" "12138" "12139" "12140" "12141"
## [12142] "12142" "12143" "12144" "12145" "12146" "12147" "12148" "12149" "12150"
## [12151] "12151" "12152" "12153" "12154" "12155" "12156" "12157" "12158" "12159"
## [12160] "12160" "12161" "12162" "12163" "12164" "12165" "12166" "12167" "12168"
## [12169] "12169" "12170" "12171" "12172" "12173" "12174" "12175" "12176" "12177"
## [12178] "12178" "12179" "12180" "12181" "12182" "12183" "12184" "12185" "12186"
## [12187] "12187" "12188" "12189" "12190" "12191" "12192" "12193" "12194" "12195"
## [12196] "12196" "12197" "12198" "12199" "12200" "12201" "12202" "12203" "12204"
## [12205] "12205" "12206" "12207" "12208" "12209" "12210" "12211" "12212" "12213"
## [12214] "12214" "12215" "12216" "12217" "12218" "12219" "12220" "12221" "12222"
## [12223] "12223" "12224" "12225" "12226" "12227" "12228" "12229" "12230" "12231"
## [12232] "12232" "12233" "12234" "12235" "12236" "12237" "12238" "12239" "12240"
## [12241] "12241" "12242" "12243" "12244" "12245" "12246" "12247" "12248" "12249"
## [12250] "12250" "12251" "12252" "12253" "12254" "12255" "12256" "12257" "12258"
## [12259] "12259" "12260" "12261" "12262" "12263" "12264" "12265" "12266" "12267"
## [12268] "12268" "12269" "12270" "12271" "12272" "12273" "12274" "12275" "12276"
## [12277] "12277" "12278" "12279" "12280" "12281" "12282" "12283" "12284" "12285"
## [12286] "12286" "12287" "12288" "12289" "12290" "12291" "12292" "12293" "12294"
## [12295] "12295" "12296" "12297" "12298" "12299" "12300" "12301" "12302" "12303"
## [12304] "12304" "12305" "12306" "12307" "12308" "12309" "12310" "12311" "12312"
## [12313] "12313" "12314" "12315" "12316" "12317" "12318" "12319" "12320" "12321"
## [12322] "12322" "12323" "12324" "12325" "12326" "12327" "12328" "12329" "12330"
## [12331] "12331" "12332" "12333" "12334" "12335" "12336" "12337" "12338" "12339"
## [12340] "12340" "12341" "12342" "12343" "12344" "12345" "12346" "12347" "12348"
## [12349] "12349" "12350" "12351" "12352" "12353" "12354" "12355" "12356" "12357"
## [12358] "12358" "12359" "12360" "12361" "12362" "12363" "12364" "12365" "12366"
## [12367] "12367" "12368" "12369" "12370" "12371" "12372" "12373" "12374" "12375"
## [12376] "12376" "12377" "12378" "12379" "12380" "12381" "12382" "12383" "12384"
## [12385] "12385" "12386" "12387" "12388" "12389" "12390" "12391" "12392" "12393"
## [12394] "12394" "12395" "12396" "12397" "12398" "12399" "12400" "12401" "12402"
## [12403] "12403" "12404" "12405" "12406" "12407" "12408" "12409" "12410" "12411"
## [12412] "12412" "12413" "12414" "12415" "12416" "12417" "12418" "12419" "12420"
## [12421] "12421" "12422" "12423" "12424" "12425" "12426" "12427" "12428" "12429"
## [12430] "12430" "12431" "12432" "12433" "12434" "12435" "12436" "12437" "12438"
## [12439] "12439" "12440" "12441" "12442" "12443" "12444" "12445" "12446" "12447"
## [12448] "12448" "12449" "12450" "12451" "12452" "12453" "12454" "12455" "12456"
## [12457] "12457" "12458" "12459" "12460" "12461" "12462" "12463" "12464" "12465"
## [12466] "12466" "12467" "12468" "12469" "12470" "12471" "12472" "12473" "12474"
## [12475] "12475" "12476" "12477" "12478" "12479" "12480" "12481" "12482" "12483"
## [12484] "12484" "12485" "12486" "12487" "12488" "12489" "12490" "12491" "12492"
## [12493] "12493" "12494" "12495" "12496" "12497" "12498" "12499" "12500" "12501"
## [12502] "12502" "12503" "12504" "12505" "12506" "12507" "12508" "12509" "12510"
## [12511] "12511" "12512" "12513" "12514" "12515" "12516" "12517" "12518" "12519"
## [12520] "12520" "12521" "12522" "12523" "12524" "12525" "12526" "12527" "12528"
## [12529] "12529" "12530" "12531" "12532" "12533" "12534" "12535" "12536" "12537"
## [12538] "12538" "12539" "12540" "12541" "12542" "12543" "12544" "12545" "12546"
## [12547] "12547" "12548" "12549" "12550" "12551" "12552" "12553" "12554" "12555"
## [12556] "12556" "12557" "12558" "12559" "12560" "12561" "12562" "12563" "12564"
## [12565] "12565" "12566" "12567" "12568" "12569" "12570" "12571" "12572" "12573"
## [12574] "12574" "12575" "12576" "12577" "12578" "12579" "12580" "12581" "12582"
## [12583] "12583" "12584" "12585" "12586" "12587" "12588" "12589" "12590" "12591"
## [12592] "12592" "12593" "12594" "12595" "12596" "12597" "12598" "12599" "12600"
## [12601] "12601" "12602" "12603" "12604" "12605" "12606" "12607" "12608" "12609"
## [12610] "12610" "12611" "12612" "12613" "12614" "12615" "12616" "12617" "12618"
## [12619] "12619" "12620" "12621" "12622" "12623" "12624" "12625" "12626" "12627"
## [12628] "12628" "12629" "12630" "12631" "12632" "12633" "12634" "12635" "12636"
## [12637] "12637" "12638" "12639" "12640" "12641" "12642" "12643" "12644" "12645"
## [12646] "12646" "12647" "12648" "12649" "12650" "12651" "12652" "12653" "12654"
## [12655] "12655" "12656" "12657" "12658" "12659" "12660" "12661" "12662" "12663"
## [12664] "12664" "12665" "12666" "12667" "12668" "12669" "12670" "12671" "12672"
## [12673] "12673" "12674" "12675" "12676" "12677" "12678" "12679" "12680" "12681"
## [12682] "12682" "12683" "12684" "12685" "12686" "12687" "12688" "12689" "12690"
## [12691] "12691" "12692" "12693" "12694" "12695" "12696" "12697" "12698" "12699"
## [12700] "12700" "12701" "12702" "12703" "12704" "12705" "12706" "12707" "12708"
## [12709] "12709" "12710" "12711" "12712" "12713" "12714" "12715" "12716" "12717"
## [12718] "12718" "12719" "12720" "12721" "12722" "12723" "12724" "12725" "12726"
## [12727] "12727" "12728" "12729" "12730" "12731" "12732" "12733" "12734" "12735"
## [12736] "12736" "12737" "12738" "12739" "12740" "12741" "12742" "12743" "12744"
## [12745] "12745" "12746" "12747" "12748" "12749" "12750" "12751" "12752" "12753"
## [12754] "12754" "12755" "12756" "12757" "12758" "12759" "12760" "12761" "12762"
## [12763] "12763" "12764" "12765" "12766" "12767" "12768" "12769" "12770" "12771"
## [12772] "12772" "12773" "12774" "12775" "12776" "12777" "12778" "12779" "12780"
## [12781] "12781" "12782" "12783" "12784" "12785" "12786" "12787" "12788" "12789"
## [12790] "12790" "12791" "12792" "12793" "12794" "12795" "12796" "12797" "12798"
## [12799] "12799" "12800" "12801" "12802" "12803" "12804" "12805" "12806" "12807"
## [12808] "12808" "12809" "12810" "12811" "12812" "12813" "12814" "12815" "12816"
## [12817] "12817" "12818" "12819" "12820" "12821" "12822" "12823" "12824" "12825"
## [12826] "12826" "12827" "12828" "12829" "12830" "12831" "12832" "12833" "12834"
## [12835] "12835" "12836" "12837" "12838" "12839" "12840" "12841" "12842" "12843"
## [12844] "12844" "12845" "12846" "12847" "12848" "12849" "12850" "12851" "12852"
## [12853] "12853" "12854" "12855" "12856" "12857" "12858" "12859" "12860" "12861"
## [12862] "12862" "12863" "12864" "12865" "12866" "12867" "12868" "12869" "12870"
## [12871] "12871" "12872" "12873" "12874" "12875" "12876" "12877" "12878" "12879"
## [12880] "12880" "12881" "12882" "12883" "12884" "12885" "12886" "12887" "12888"
## [12889] "12889" "12890" "12891" "12892" "12893" "12894" "12895" "12896" "12897"
## [12898] "12898" "12899" "12900" "12901" "12902" "12903" "12904" "12905" "12906"
## [12907] "12907" "12908" "12909" "12910" "12911" "12912" "12913" "12914" "12915"
## [12916] "12916" "12917" "12918" "12919" "12920" "12921" "12922" "12923" "12924"
## [12925] "12925" "12926" "12927" "12928" "12929" "12930" "12931" "12932" "12933"
## [12934] "12934" "12935" "12936" "12937" "12938" "12939" "12940" "12941" "12942"
## [12943] "12943" "12944" "12945" "12946" "12947" "12948" "12949" "12950" "12951"
## [12952] "12952" "12953" "12954" "12955" "12956" "12957" "12958" "12959" "12960"
## [12961] "12961" "12962" "12963" "12964" "12965" "12966" "12967" "12968" "12969"
## [12970] "12970" "12971" "12972" "12973" "12974" "12975" "12976" "12977" "12978"
## [12979] "12979" "12980" "12981" "12982" "12983" "12984" "12985" "12986" "12987"
## [12988] "12988" "12989" "12990" "12991" "12992" "12993" "12994" "12995" "12996"
## [12997] "12997" "12998" "12999" "13000" "13001" "13002" "13003" "13004" "13005"
## [13006] "13006" "13007" "13008" "13009" "13010" "13011" "13012" "13013" "13014"
## [13015] "13015" "13016" "13017" "13018" "13019" "13020" "13021" "13022" "13023"
## [13024] "13024" "13025" "13026" "13027" "13028" "13029" "13030" "13031" "13032"
## [13033] "13033" "13034" "13035" "13036" "13037" "13038" "13039" "13040" "13041"
## [13042] "13042" "13043" "13044" "13045" "13046" "13047" "13048" "13049" "13050"
## [13051] "13051" "13052" "13053" "13054" "13055" "13056" "13057" "13058" "13059"
## [13060] "13060" "13061" "13062" "13063" "13064" "13065" "13066" "13067" "13068"
## [13069] "13069" "13070" "13071" "13072" "13073" "13074" "13075" "13076" "13077"
## [13078] "13078" "13079" "13080" "13081" "13082" "13083" "13084" "13085" "13086"
## [13087] "13087" "13088" "13089" "13090" "13091" "13092" "13093" "13094" "13095"
## [13096] "13096" "13097" "13098" "13099" "13100" "13101" "13102" "13103" "13104"
## [13105] "13105" "13106" "13107" "13108" "13109" "13110" "13111" "13112" "13113"
## [13114] "13114" "13115" "13116" "13117" "13118" "13119" "13120" "13121" "13122"
## [13123] "13123" "13124" "13125" "13126" "13127" "13128" "13129" "13130" "13131"
## [13132] "13132" "13133" "13134" "13135" "13136" "13137" "13138" "13139" "13140"
## [13141] "13141" "13142" "13143" "13144" "13145" "13146" "13147" "13148" "13149"
## [13150] "13150" "13151" "13152" "13153" "13154" "13155" "13156" "13157" "13158"
## [13159] "13159" "13160" "13161" "13162" "13163" "13164" "13165" "13166" "13167"
## [13168] "13168" "13169" "13170" "13171" "13172" "13173" "13174" "13175" "13176"
## [13177] "13177" "13178" "13179" "13180" "13181" "13182" "13183" "13184" "13185"
## [13186] "13186" "13187" "13188" "13189" "13190" "13191" "13192" "13193" "13194"
## [13195] "13195" "13196" "13197" "13198" "13199" "13200" "13201" "13202" "13203"
## [13204] "13204" "13205" "13206" "13207" "13208" "13209" "13210" "13211" "13212"
## [13213] "13213" "13214" "13215" "13216" "13217" "13218" "13219" "13220" "13221"
## [13222] "13222" "13223" "13224" "13225" "13226" "13227" "13228" "13229" "13230"
## [13231] "13231" "13232" "13233" "13234" "13235" "13236" "13237" "13238" "13239"
## [13240] "13240" "13241" "13242" "13243" "13244" "13245" "13246" "13247" "13248"
## [13249] "13249" "13250" "13251" "13252" "13253" "13254" "13255" "13256" "13257"
## [13258] "13258" "13259" "13260" "13261" "13262" "13263" "13264" "13265" "13266"
## [13267] "13267" "13268" "13269" "13270" "13271" "13272" "13273" "13274" "13275"
## [13276] "13276" "13277" "13278" "13279" "13280" "13281" "13282" "13283" "13284"
## [13285] "13285" "13286" "13287" "13288" "13289" "13290" "13291" "13292" "13293"
## [13294] "13294" "13295" "13296" "13297" "13298" "13299" "13300" "13301" "13302"
## [13303] "13303" "13304" "13305" "13306" "13307" "13308" "13309" "13310" "13311"
## [13312] "13312" "13313" "13314" "13315" "13316" "13317" "13318" "13319" "13320"
## [13321] "13321" "13322" "13323" "13324" "13325" "13326" "13327" "13328" "13329"
## [13330] "13330" "13331" "13332" "13333" "13334" "13335" "13336" "13337" "13338"
## [13339] "13339" "13340" "13341" "13342" "13343" "13344" "13345" "13346" "13347"
## [13348] "13348" "13349" "13350" "13351" "13352" "13353" "13354" "13355" "13356"
## [13357] "13357" "13358" "13359" "13360" "13361" "13362" "13363" "13364" "13365"
## [13366] "13366" "13367" "13368" "13369" "13370" "13371" "13372" "13373" "13374"
## [13375] "13375" "13376" "13377" "13378" "13379" "13380" "13381" "13382" "13383"
## [13384] "13384" "13385" "13386" "13387" "13388" "13389" "13390" "13391" "13392"
## [13393] "13393" "13394" "13395" "13396" "13397" "13398" "13399" "13400" "13401"
## [13402] "13402" "13403" "13404" "13405" "13406" "13407" "13408" "13409" "13410"
## [13411] "13411" "13412" "13413" "13414" "13415" "13416" "13417" "13418" "13419"
## [13420] "13420" "13421" "13422" "13423" "13424" "13425" "13426" "13427" "13428"
## [13429] "13429" "13430" "13431" "13432" "13433" "13434" "13435" "13436" "13437"
## [13438] "13438" "13439" "13440" "13441" "13442" "13443" "13444" "13445" "13446"
## [13447] "13447" "13448" "13449" "13450" "13451" "13452" "13453" "13454" "13455"
## [13456] "13456" "13457" "13458" "13459" "13460" "13461" "13462" "13463" "13464"
## [13465] "13465" "13466" "13467" "13468" "13469" "13470" "13471" "13472" "13473"
## [13474] "13474" "13475" "13476" "13477" "13478" "13479" "13480" "13481" "13482"
## [13483] "13483" "13484" "13485" "13486" "13487" "13488" "13489" "13490" "13491"
## [13492] "13492" "13493" "13494" "13495" "13496" "13497" "13498" "13499" "13500"
## [13501] "13501" "13502" "13503" "13504" "13505" "13506" "13507" "13508" "13509"
## [13510] "13510" "13511" "13512" "13513" "13514" "13515" "13516" "13517" "13518"
## [13519] "13519" "13520" "13521" "13522" "13523" "13524" "13525" "13526" "13527"
## [13528] "13528" "13529" "13530" "13531" "13532" "13533" "13534" "13535" "13536"
## [13537] "13537" "13538" "13539" "13540" "13541" "13542" "13543" "13544" "13545"
## [13546] "13546" "13547" "13548" "13549" "13550" "13551" "13552" "13553" "13554"
## [13555] "13555" "13556" "13557" "13558" "13559" "13560" "13561" "13562" "13563"
## [13564] "13564" "13565" "13566" "13567" "13568" "13569" "13570" "13571" "13572"
## [13573] "13573" "13574" "13575" "13576" "13577" "13578" "13579" "13580" "13581"
## [13582] "13582" "13583" "13584" "13585" "13586" "13587" "13588" "13589" "13590"
## [13591] "13591" "13592" "13593" "13594" "13595" "13596" "13597" "13598" "13599"
## [13600] "13600" "13601" "13602" "13603" "13604" "13605" "13606" "13607" "13608"
## [13609] "13609" "13610" "13611" "13612" "13613" "13614" "13615" "13616" "13617"
## [13618] "13618" "13619" "13620" "13621" "13622" "13623" "13624" "13625" "13626"
## [13627] "13627" "13628" "13629" "13630" "13631" "13632" "13633" "13634" "13635"
## [13636] "13636" "13637" "13638" "13639" "13640" "13641" "13642" "13643" "13644"
## [13645] "13645" "13646" "13647" "13648" "13649" "13650" "13651" "13652" "13653"
## [13654] "13654" "13655" "13656" "13657" "13658" "13659" "13660" "13661" "13662"
## [13663] "13663" "13664" "13665" "13666" "13667" "13668" "13669" "13670" "13671"
## [13672] "13672" "13673" "13674" "13675" "13676" "13677" "13678" "13679" "13680"
## [13681] "13681" "13682" "13683" "13684" "13685" "13686" "13687" "13688" "13689"
## [13690] "13690" "13691" "13692" "13693" "13694" "13695" "13696" "13697" "13698"
## [13699] "13699" "13700" "13701" "13702" "13703" "13704" "13705" "13706" "13707"
## [13708] "13708" "13709" "13710" "13711" "13712" "13713" "13714" "13715" "13716"
## [13717] "13717" "13718" "13719" "13720" "13721" "13722" "13723" "13724" "13725"
## [13726] "13726" "13727" "13728" "13729" "13730" "13731" "13732" "13733" "13734"
## [13735] "13735" "13736" "13737" "13738" "13739" "13740" "13741" "13742" "13743"
## [13744] "13744" "13745" "13746" "13747" "13748" "13749" "13750" "13751" "13752"
## [13753] "13753" "13754" "13755" "13756" "13757" "13758" "13759" "13760" "13761"
## [13762] "13762" "13763" "13764" "13765" "13766" "13767" "13768" "13769" "13770"
## [13771] "13771" "13772" "13773" "13774" "13775" "13776" "13777" "13778" "13779"
## [13780] "13780" "13781" "13782" "13783" "13784" "13785" "13786" "13787" "13788"
## [13789] "13789" "13790" "13791" "13792" "13793" "13794" "13795" "13796" "13797"
## [13798] "13798" "13799" "13800" "13801" "13802" "13803" "13804" "13805" "13806"
## [13807] "13807" "13808" "13809" "13810" "13811" "13812" "13813" "13814" "13815"
## [13816] "13816" "13817" "13818" "13819" "13820" "13821" "13822" "13823" "13824"
## [13825] "13825" "13826" "13827" "13828" "13829" "13830" "13831" "13832" "13833"
## [13834] "13834" "13835" "13836" "13837" "13838" "13839" "13840" "13841" "13842"
## [13843] "13843" "13844" "13845" "13846" "13847" "13848" "13849" "13850" "13851"
## [13852] "13852" "13853" "13854" "13855" "13856" "13857" "13858" "13859" "13860"
## [13861] "13861" "13862" "13863" "13864" "13865" "13866" "13867" "13868" "13869"
## [13870] "13870" "13871" "13872" "13873" "13874" "13875" "13876" "13877" "13878"
## [13879] "13879" "13880" "13881" "13882" "13883" "13884" "13885" "13886" "13887"
## [13888] "13888" "13889" "13890" "13891" "13892" "13893" "13894" "13895" "13896"
## [13897] "13897" "13898" "13899" "13900" "13901" "13902" "13903" "13904" "13905"
## [13906] "13906" "13907" "13908" "13909" "13910" "13911" "13912" "13913" "13914"
## [13915] "13915" "13916" "13917" "13918" "13919" "13920" "13921" "13922" "13923"
## [13924] "13924" "13925" "13926" "13927" "13928" "13929" "13930" "13931" "13932"
## [13933] "13933" "13934" "13935" "13936" "13937" "13938" "13939" "13940" "13941"
## [13942] "13942" "13943" "13944" "13945" "13946" "13947" "13948" "13949" "13950"
## [13951] "13951" "13952" "13953" "13954" "13955" "13956" "13957" "13958" "13959"
## [13960] "13960" "13961" "13962" "13963" "13964" "13965" "13966" "13967" "13968"
## [13969] "13969" "13970" "13971" "13972" "13973" "13974" "13975" "13976" "13977"
## [13978] "13978" "13979" "13980" "13981" "13982" "13983" "13984" "13985" "13986"
## [13987] "13987" "13988" "13989" "13990" "13991" "13992" "13993" "13994" "13995"
## [13996] "13996" "13997" "13998" "13999" "14000" "14001" "14002" "14003" "14004"
## [14005] "14005" "14006" "14007" "14008" "14009" "14010" "14011" "14012" "14013"
## [14014] "14014" "14015" "14016" "14017" "14018" "14019" "14020" "14021" "14022"
## [14023] "14023" "14024" "14025" "14026" "14027" "14028" "14029" "14030" "14031"
## [14032] "14032" "14033" "14034" "14035" "14036" "14037" "14038" "14039" "14040"
## [14041] "14041" "14042" "14043" "14044" "14045" "14046" "14047" "14048" "14049"
## [14050] "14050" "14051" "14052" "14053" "14054" "14055" "14056" "14057" "14058"
## [14059] "14059" "14060" "14061" "14062" "14063" "14064" "14065" "14066" "14067"
## [14068] "14068" "14069" "14070" "14071" "14072" "14073" "14074" "14075" "14076"
## [14077] "14077" "14078" "14079" "14080" "14081" "14082" "14083" "14084" "14085"
## [14086] "14086" "14087" "14088" "14089" "14090" "14091" "14092" "14093" "14094"
## [14095] "14095" "14096" "14097" "14098" "14099" "14100" "14101" "14102" "14103"
## [14104] "14104" "14105" "14106" "14107" "14108" "14109" "14110" "14111" "14112"
## [14113] "14113" "14114" "14115" "14116" "14117" "14118" "14119" "14120" "14121"
## [14122] "14122" "14123" "14124" "14125" "14126" "14127" "14128" "14129" "14130"
## [14131] "14131" "14132" "14133" "14134" "14135" "14136" "14137" "14138" "14139"
## [14140] "14140" "14141" "14142" "14143" "14144" "14145" "14146" "14147" "14148"
## [14149] "14149" "14150" "14151" "14152" "14153" "14154" "14155" "14156" "14157"
## [14158] "14158" "14159" "14160" "14161" "14162" "14163" "14164" "14165" "14166"
## [14167] "14167" "14168" "14169" "14170" "14171" "14172" "14173" "14174" "14175"
## [14176] "14176" "14177" "14178" "14179" "14180" "14181" "14182" "14183" "14184"
## [14185] "14185" "14186" "14187" "14188" "14189" "14190" "14191" "14192" "14193"
## [14194] "14194" "14195" "14196" "14197" "14198" "14199" "14200" "14201" "14202"
## [14203] "14203" "14204" "14205" "14206" "14207" "14208" "14209" "14210" "14211"
## [14212] "14212" "14213" "14214" "14215" "14216" "14217" "14218" "14219" "14220"
## [14221] "14221" "14222" "14223" "14224" "14225" "14226" "14227" "14228" "14229"
## [14230] "14230" "14231" "14232" "14233" "14234" "14235" "14236" "14237" "14238"
## [14239] "14239" "14240" "14241" "14242" "14243" "14244" "14245" "14246" "14247"
## [14248] "14248" "14249" "14250" "14251" "14252" "14253" "14254" "14255" "14256"
## [14257] "14257" "14258" "14259" "14260" "14261" "14262" "14263" "14264" "14265"
## [14266] "14266" "14267" "14268" "14269" "14270" "14271" "14272" "14273" "14274"
## [14275] "14275" "14276" "14277" "14278" "14279" "14280" "14281" "14282" "14283"
## [14284] "14284" "14285" "14286" "14287" "14288" "14289" "14290" "14291" "14292"
## [14293] "14293" "14294" "14295" "14296" "14297" "14298" "14299" "14300" "14301"
## [14302] "14302" "14303" "14304" "14305" "14306" "14307" "14308" "14309" "14310"
## [14311] "14311" "14312" "14313" "14314" "14315" "14316" "14317" "14318" "14319"
## [14320] "14320" "14321" "14322" "14323" "14324" "14325" "14326" "14327" "14328"
## [14329] "14329" "14330" "14331" "14332" "14333" "14334" "14335" "14336" "14337"
## [14338] "14338" "14339" "14340" "14341" "14342" "14343" "14344" "14345" "14346"
## [14347] "14347" "14348" "14349" "14350" "14351" "14352" "14353" "14354" "14355"
## [14356] "14356" "14357" "14358" "14359" "14360" "14361" "14362" "14363" "14364"
## [14365] "14365" "14366" "14367" "14368" "14369" "14370" "14371" "14372" "14373"
## [14374] "14374" "14375" "14376" "14377" "14378" "14379" "14380" "14381" "14382"
## [14383] "14383" "14384" "14385" "14386" "14387" "14388" "14389" "14390" "14391"
## [14392] "14392" "14393" "14394" "14395" "14396" "14397" "14398" "14399" "14400"
## [14401] "14401" "14402" "14403" "14404" "14405" "14406" "14407" "14408" "14409"
## [14410] "14410" "14411" "14412" "14413" "14414" "14415" "14416" "14417" "14418"
## [14419] "14419" "14420" "14421" "14422" "14423" "14424" "14425" "14426" "14427"
## [14428] "14428" "14429" "14430" "14431" "14432" "14433" "14434" "14435" "14436"
## [14437] "14437" "14438" "14439" "14440" "14441" "14442" "14443" "14444" "14445"
## [14446] "14446" "14447" "14448" "14449" "14450" "14451" "14452" "14453" "14454"
## [14455] "14455" "14456" "14457" "14458" "14459" "14460" "14461" "14462" "14463"
## [14464] "14464" "14465" "14466" "14467" "14468" "14469" "14470" "14471" "14472"
## [14473] "14473" "14474" "14475" "14476" "14477" "14478" "14479" "14480" "14481"
## [14482] "14482" "14483" "14484" "14485" "14486" "14487" "14488" "14489" "14490"
## [14491] "14491" "14492" "14493" "14494" "14495" "14496" "14497" "14498" "14499"
## [14500] "14500" "14501" "14502" "14503" "14504" "14505" "14506" "14507" "14508"
## [14509] "14509" "14510" "14511" "14512" "14513" "14514" "14515" "14516" "14517"
## [14518] "14518" "14519" "14520" "14521" "14522" "14523" "14524" "14525" "14526"
## [14527] "14527" "14528" "14529" "14530" "14531" "14532" "14533" "14534" "14535"
## [14536] "14536" "14537" "14538" "14539" "14540" "14541" "14542" "14543" "14544"
## [14545] "14545" "14546" "14547" "14548" "14549" "14550" "14551" "14552" "14553"
## [14554] "14554" "14555" "14556" "14557" "14558" "14559" "14560" "14561" "14562"
## [14563] "14563" "14564" "14565" "14566" "14567" "14568" "14569" "14570" "14571"
## [14572] "14572" "14573" "14574" "14575" "14576" "14577" "14578" "14579" "14580"
## [14581] "14581" "14582" "14583" "14584" "14585" "14586" "14587" "14588" "14589"
## [14590] "14590" "14591" "14592" "14593" "14594" "14595" "14596" "14597" "14598"
## [14599] "14599" "14600" "14601" "14602" "14603" "14604" "14605" "14606" "14607"
## [14608] "14608" "14609" "14610" "14611" "14612" "14613" "14614" "14615" "14616"
## [14617] "14617" "14618" "14619" "14620" "14621" "14622" "14623" "14624" "14625"
## [14626] "14626" "14627" "14628" "14629" "14630" "14631" "14632" "14633" "14634"
## [14635] "14635" "14636" "14637" "14638" "14639" "14640" "14641" "14642" "14643"
## [14644] "14644" "14645" "14646" "14647" "14648" "14649" "14650" "14651" "14652"
## [14653] "14653" "14654" "14655" "14656" "14657" "14658" "14659" "14660" "14661"
## [14662] "14662" "14663" "14664" "14665" "14666" "14667" "14668" "14669" "14670"
## [14671] "14671" "14672" "14673" "14674" "14675" "14676" "14677" "14678" "14679"
## [14680] "14680" "14681" "14682" "14683" "14684" "14685" "14686" "14687" "14688"
## [14689] "14689" "14690" "14691" "14692" "14693" "14694" "14695" "14696" "14697"
## [14698] "14698" "14699" "14700" "14701" "14702" "14703" "14704" "14705" "14706"
## [14707] "14707" "14708" "14709" "14710" "14711" "14712" "14713" "14714" "14715"
## [14716] "14716" "14717" "14718" "14719" "14720" "14721" "14722" "14723" "14724"
## [14725] "14725" "14726" "14727" "14728" "14729" "14730" "14731" "14732" "14733"
## [14734] "14734" "14735" "14736" "14737" "14738" "14739" "14740" "14741" "14742"
## [14743] "14743" "14744" "14745" "14746" "14747" "14748" "14749" "14750" "14751"
## [14752] "14752" "14753" "14754" "14755" "14756" "14757" "14758" "14759" "14760"
## [14761] "14761" "14762" "14763" "14764" "14765" "14766" "14767" "14768" "14769"
## [14770] "14770" "14771" "14772" "14773" "14774" "14775" "14776" "14777" "14778"
## [14779] "14779" "14780" "14781" "14782" "14783" "14784" "14785" "14786" "14787"
## [14788] "14788" "14789" "14790" "14791" "14792" "14793" "14794" "14795" "14796"
## [14797] "14797" "14798" "14799" "14800" "14801" "14802" "14803" "14804" "14805"
## [14806] "14806" "14807" "14808" "14809" "14810" "14811" "14812" "14813" "14814"
## [14815] "14815" "14816" "14817" "14818" "14819" "14820" "14821" "14822" "14823"
## [14824] "14824" "14825" "14826" "14827" "14828" "14829" "14830" "14831" "14832"
## [14833] "14833" "14834" "14835" "14836" "14837" "14838" "14839" "14840" "14841"
## [14842] "14842" "14843" "14844" "14845" "14846" "14847" "14848" "14849" "14850"
## [14851] "14851" "14852" "14853" "14854" "14855" "14856" "14857" "14858" "14859"
## [14860] "14860" "14861" "14862" "14863" "14864" "14865" "14866" "14867" "14868"
## [14869] "14869" "14870" "14871" "14872" "14873" "14874" "14875" "14876" "14877"
## [14878] "14878" "14879" "14880" "14881" "14882" "14883" "14884" "14885" "14886"
## [14887] "14887" "14888" "14889" "14890" "14891" "14892" "14893" "14894" "14895"
## [14896] "14896" "14897" "14898" "14899" "14900" "14901" "14902" "14903" "14904"
## [14905] "14905" "14906" "14907" "14908" "14909" "14910" "14911" "14912" "14913"
## [14914] "14914" "14915" "14916" "14917" "14918" "14919" "14920" "14921" "14922"
## [14923] "14923" "14924" "14925" "14926" "14927" "14928" "14929" "14930" "14931"
## [14932] "14932" "14933" "14934" "14935" "14936" "14937" "14938" "14939" "14940"
## [14941] "14941" "14942" "14943" "14944" "14945" "14946" "14947" "14948" "14949"
## [14950] "14950" "14951" "14952" "14953" "14954" "14955" "14956" "14957" "14958"
## [14959] "14959" "14960" "14961" "14962" "14963" "14964" "14965" "14966" "14967"
## [14968] "14968" "14969" "14970" "14971" "14972" "14973" "14974" "14975" "14976"
## [14977] "14977" "14978" "14979" "14980" "14981" "14982" "14983" "14984" "14985"
## [14986] "14986" "14987" "14988" "14989" "14990" "14991" "14992" "14993" "14994"
## [14995] "14995" "14996" "14997" "14998" "14999" "15000" "15001" "15002" "15003"
## [15004] "15004" "15005" "15006" "15007" "15008" "15009" "15010" "15011" "15012"
## [15013] "15013" "15014" "15015" "15016" "15017" "15018" "15019" "15020" "15021"
## [15022] "15022" "15023" "15024" "15025" "15026" "15027" "15028" "15029" "15030"
## [15031] "15031" "15032" "15033" "15034" "15035" "15036" "15037" "15038" "15039"
## [15040] "15040" "15041" "15042" "15043" "15044" "15045" "15046" "15047" "15048"
## [15049] "15049" "15050" "15051" "15052" "15053" "15054" "15055" "15056" "15057"
## [15058] "15058" "15059" "15060" "15061" "15062" "15063" "15064" "15065" "15066"
## [15067] "15067" "15068" "15069" "15070" "15071" "15072" "15073" "15074" "15075"
## [15076] "15076" "15077" "15078" "15079" "15080" "15081" "15082" "15083" "15084"
## [15085] "15085" "15086" "15087" "15088" "15089" "15090" "15091" "15092" "15093"
## [15094] "15094" "15095" "15096" "15097" "15098" "15099" "15100" "15101" "15102"
## [15103] "15103" "15104" "15105" "15106" "15107" "15108" "15109" "15110" "15111"
## [15112] "15112" "15113" "15114" "15115" "15116" "15117" "15118" "15119" "15120"
## [15121] "15121" "15122" "15123" "15124" "15125" "15126" "15127" "15128" "15129"
## [15130] "15130" "15131" "15132" "15133" "15134" "15135" "15136" "15137" "15138"
## [15139] "15139" "15140" "15141" "15142" "15143" "15144" "15145" "15146" "15147"
## [15148] "15148" "15149" "15150" "15151" "15152" "15153" "15154" "15155" "15156"
## [15157] "15157" "15158" "15159" "15160" "15161" "15162" "15163" "15164" "15165"
## [15166] "15166" "15167" "15168" "15169" "15170" "15171" "15172" "15173" "15174"
## [15175] "15175" "15176" "15177" "15178" "15179" "15180" "15181" "15182" "15183"
## [15184] "15184" "15185" "15186" "15187" "15188" "15189" "15190" "15191" "15192"
## [15193] "15193" "15194" "15195" "15196" "15197" "15198" "15199" "15200" "15201"
## [15202] "15202" "15203" "15204" "15205" "15206" "15207" "15208" "15209" "15210"
## [15211] "15211" "15212" "15213" "15214" "15215" "15216" "15217" "15218" "15219"
## [15220] "15220" "15221" "15222" "15223" "15224" "15225" "15226" "15227" "15228"
## [15229] "15229" "15230" "15231" "15232" "15233" "15234" "15235" "15236" "15237"
## [15238] "15238" "15239" "15240" "15241" "15242" "15243" "15244" "15245" "15246"
## [15247] "15247" "15248" "15249" "15250" "15251" "15252" "15253" "15254" "15255"
## [15256] "15256" "15257" "15258" "15259" "15260" "15261" "15262" "15263" "15264"
## [15265] "15265" "15266" "15267" "15268" "15269" "15270" "15271" "15272" "15273"
## [15274] "15274" "15275" "15276" "15277" "15278" "15279" "15280" "15281" "15282"
## [15283] "15283" "15284" "15285" "15286" "15287" "15288" "15289" "15290" "15291"
## [15292] "15292" "15293" "15294" "15295" "15296" "15297" "15298" "15299" "15300"
## [15301] "15301" "15302" "15303" "15304" "15305" "15306" "15307" "15308" "15309"
## [15310] "15310" "15311" "15312" "15313" "15314" "15315" "15316" "15317" "15318"
## [15319] "15319" "15320" "15321" "15322" "15323" "15324" "15325" "15326" "15327"
## [15328] "15328" "15329" "15330" "15331" "15332" "15333" "15334" "15335" "15336"
## [15337] "15337" "15338" "15339" "15340" "15341" "15342" "15343" "15344" "15345"
## [15346] "15346" "15347" "15348" "15349" "15350" "15351" "15352" "15353" "15354"
## [15355] "15355" "15356" "15357" "15358" "15359" "15360" "15361" "15362" "15363"
## [15364] "15364" "15365" "15366" "15367" "15368" "15369" "15370" "15371" "15372"
## [15373] "15373" "15374" "15375" "15376" "15377" "15378" "15379" "15380" "15381"
## [15382] "15382" "15383" "15384" "15385" "15386" "15387" "15388" "15389" "15390"
## [15391] "15391" "15392" "15393" "15394" "15395" "15396" "15397" "15398" "15399"
## [15400] "15400" "15401" "15402" "15403" "15404" "15405" "15406" "15407" "15408"
## [15409] "15409" "15410" "15411" "15412" "15413" "15414" "15415" "15416" "15417"
## [15418] "15418" "15419" "15420" "15421" "15422" "15423" "15424" "15425" "15426"
## [15427] "15427" "15428" "15429" "15430" "15431" "15432" "15433" "15434" "15435"
## [15436] "15436" "15437" "15438" "15439" "15440" "15441" "15442" "15443" "15444"
## [15445] "15445" "15446" "15447" "15448" "15449" "15450" "15451" "15452" "15453"
## [15454] "15454" "15455" "15456" "15457" "15458" "15459" "15460" "15461" "15462"
## [15463] "15463" "15464" "15465" "15466" "15467" "15468" "15469" "15470" "15471"
## [15472] "15472" "15473" "15474" "15475" "15476" "15477" "15478" "15479" "15480"
## [15481] "15481" "15482" "15483" "15484" "15485" "15486" "15487" "15488" "15489"
## [15490] "15490" "15491" "15492" "15493" "15494" "15495" "15496" "15497" "15498"
## [15499] "15499" "15500" "15501" "15502" "15503" "15504" "15505" "15506" "15507"
## [15508] "15508" "15509" "15510" "15511" "15512" "15513" "15514" "15515" "15516"
## [15517] "15517" "15518" "15519" "15520" "15521" "15522" "15523" "15524" "15525"
## [15526] "15526" "15527" "15528" "15529" "15530" "15531" "15532" "15533" "15534"
## [15535] "15535" "15536" "15537" "15538" "15539" "15540" "15541" "15542" "15543"
## [15544] "15544" "15545" "15546" "15547" "15548" "15549" "15550" "15551" "15552"
## [15553] "15553" "15554" "15555" "15556" "15557" "15558" "15559" "15560" "15561"
## [15562] "15562" "15563" "15564" "15565" "15566" "15567" "15568" "15569" "15570"
## [15571] "15571" "15572" "15573" "15574" "15575" "15576" "15577" "15578" "15579"
## [15580] "15580" "15581" "15582" "15583" "15584" "15585" "15586" "15587" "15588"
## [15589] "15589" "15590" "15591" "15592" "15593" "15594" "15595" "15596" "15597"
## [15598] "15598" "15599" "15600" "15601" "15602" "15603" "15604" "15605" "15606"
## [15607] "15607" "15608" "15609" "15610" "15611" "15612" "15613" "15614" "15615"
## [15616] "15616" "15617" "15618" "15619" "15620" "15621" "15622" "15623" "15624"
## [15625] "15625" "15626" "15627" "15628" "15629" "15630" "15631" "15632" "15633"
## [15634] "15634" "15635" "15636" "15637" "15638" "15639" "15640" "15641" "15642"
## [15643] "15643" "15644" "15645" "15646" "15647" "15648" "15649" "15650" "15651"
## [15652] "15652" "15653" "15654" "15655" "15656" "15657" "15658" "15659" "15660"
## [15661] "15661" "15662" "15663" "15664" "15665" "15666" "15667" "15668" "15669"
## [15670] "15670" "15671" "15672" "15673" "15674" "15675" "15676" "15677" "15678"
## [15679] "15679" "15680" "15681" "15682" "15683" "15684" "15685" "15686" "15687"
## [15688] "15688" "15689" "15690" "15691" "15692" "15693" "15694" "15695" "15696"
## [15697] "15697" "15698" "15699" "15700" "15701" "15702" "15703" "15704" "15705"
## [15706] "15706" "15707" "15708" "15709" "15710" "15711" "15712" "15713" "15714"
## [15715] "15715" "15716" "15717" "15718" "15719" "15720" "15721" "15722" "15723"
## [15724] "15724" "15725" "15726" "15727" "15728" "15729" "15730" "15731" "15732"
## [15733] "15733" "15734" "15735" "15736" "15737" "15738" "15739" "15740" "15741"
## [15742] "15742" "15743" "15744" "15745" "15746" "15747" "15748" "15749" "15750"
## [15751] "15751" "15752" "15753" "15754" "15755" "15756" "15757" "15758" "15759"
## [15760] "15760" "15761" "15762" "15763" "15764" "15765" "15766" "15767" "15768"
## [15769] "15769" "15770" "15771" "15772" "15773" "15774" "15775" "15776" "15777"
## [15778] "15778" "15779" "15780" "15781" "15782" "15783" "15784" "15785" "15786"
## [15787] "15787" "15788" "15789" "15790" "15791" "15792" "15793" "15794" "15795"
## [15796] "15796" "15797" "15798" "15799" "15800" "15801" "15802" "15803" "15804"
## [15805] "15805" "15806" "15807" "15808" "15809" "15810" "15811" "15812" "15813"
## [15814] "15814" "15815" "15816" "15817" "15818" "15819" "15820" "15821" "15822"
## [15823] "15823" "15824" "15825" "15826" "15827" "15828" "15829" "15830" "15831"
## [15832] "15832" "15833" "15834" "15835" "15836" "15837" "15838" "15839" "15840"
## [15841] "15841" "15842" "15843" "15844" "15845" "15846" "15847" "15848" "15849"
## [15850] "15850" "15851" "15852" "15853" "15854" "15855" "15856" "15857" "15858"
## [15859] "15859" "15860" "15861" "15862" "15863" "15864" "15865" "15866" "15867"
## [15868] "15868" "15869" "15870" "15871" "15872" "15873" "15874" "15875" "15876"
## [15877] "15877" "15878" "15879" "15880" "15881" "15882" "15883" "15884" "15885"
## [15886] "15886" "15887" "15888" "15889" "15890" "15891" "15892" "15893" "15894"
## [15895] "15895" "15896" "15897" "15898" "15899" "15900" "15901" "15902" "15903"
## [15904] "15904" "15905" "15906" "15907" "15908" "15909" "15910" "15911" "15912"
## [15913] "15913" "15914" "15915" "15916" "15917" "15918" "15919" "15920" "15921"
## [15922] "15922" "15923" "15924" "15925" "15926" "15927" "15928" "15929" "15930"
## [15931] "15931" "15932" "15933" "15934" "15935" "15936" "15937" "15938" "15939"
## [15940] "15940" "15941" "15942" "15943" "15944" "15945" "15946" "15947" "15948"
## [15949] "15949" "15950" "15951" "15952" "15953" "15954" "15955" "15956" "15957"
## [15958] "15958" "15959" "15960" "15961" "15962" "15963" "15964" "15965" "15966"
## [15967] "15967" "15968" "15969" "15970" "15971" "15972" "15973" "15974" "15975"
## [15976] "15976" "15977" "15978" "15979" "15980" "15981" "15982" "15983" "15984"
## [15985] "15985" "15986" "15987" "15988" "15989" "15990" "15991" "15992" "15993"
## [15994] "15994" "15995" "15996" "15997" "15998" "15999" "16000" "16001" "16002"
## [16003] "16003" "16004" "16005" "16006" "16007" "16008" "16009" "16010" "16011"
## [16012] "16012" "16013" "16014" "16015" "16016" "16017" "16018" "16019" "16020"
## [16021] "16021" "16022" "16023" "16024" "16025" "16026" "16027" "16028" "16029"
## [16030] "16030" "16031" "16032" "16033" "16034" "16035" "16036" "16037" "16038"
## [16039] "16039" "16040" "16041" "16042" "16043" "16044" "16045" "16046" "16047"
## [16048] "16048" "16049" "16050" "16051" "16052" "16053" "16054" "16055" "16056"
## [16057] "16057" "16058" "16059" "16060" "16061" "16062" "16063" "16064" "16065"
## [16066] "16066" "16067" "16068" "16069" "16070" "16071" "16072" "16073" "16074"
## [16075] "16075" "16076" "16077" "16078" "16079" "16080" "16081" "16082" "16083"
## [16084] "16084" "16085" "16086" "16087" "16088" "16089" "16090" "16091" "16092"
## [16093] "16093" "16094" "16095" "16096" "16097" "16098" "16099" "16100" "16101"
## [16102] "16102" "16103" "16104" "16105" "16106" "16107" "16108" "16109" "16110"
## [16111] "16111" "16112" "16113" "16114" "16115" "16116" "16117" "16118" "16119"
## [16120] "16120" "16121" "16122" "16123" "16124" "16125" "16126" "16127" "16128"
## [16129] "16129" "16130" "16131" "16132" "16133" "16134" "16135" "16136" "16137"
## [16138] "16138" "16139" "16140" "16141" "16142" "16143" "16144" "16145" "16146"
## [16147] "16147" "16148" "16149" "16150" "16151" "16152" "16153" "16154" "16155"
## [16156] "16156" "16157" "16158" "16159" "16160" "16161" "16162" "16163" "16164"
## [16165] "16165" "16166" "16167" "16168" "16169" "16170" "16171" "16172" "16173"
## [16174] "16174" "16175" "16176" "16177" "16178" "16179" "16180" "16181" "16182"
## [16183] "16183" "16184" "16185" "16186" "16187" "16188" "16189" "16190" "16191"
## [16192] "16192" "16193" "16194" "16195" "16196" "16197" "16198" "16199" "16200"
## [16201] "16201" "16202" "16203" "16204" "16205" "16206" "16207" "16208" "16209"
## [16210] "16210" "16211" "16212" "16213" "16214" "16215" "16216" "16217" "16218"
## [16219] "16219" "16220" "16221" "16222" "16223" "16224" "16225" "16226" "16227"
## [16228] "16228" "16229" "16230" "16231" "16232" "16233" "16234" "16235" "16236"
## [16237] "16237" "16238" "16239" "16240" "16241" "16242" "16243" "16244" "16245"
## [16246] "16246" "16247" "16248" "16249" "16250" "16251" "16252" "16253" "16254"
## [16255] "16255" "16256" "16257" "16258" "16259" "16260" "16261" "16262" "16263"
## [16264] "16264" "16265" "16266" "16267" "16268" "16269" "16270" "16271" "16272"
## [16273] "16273" "16274" "16275" "16276" "16277" "16278" "16279" "16280" "16281"
## [16282] "16282" "16283" "16284" "16285" "16286" "16287" "16288" "16289" "16290"
## [16291] "16291" "16292" "16293" "16294" "16295" "16296" "16297" "16298" "16299"
## [16300] "16300" "16301" "16302" "16303" "16304" "16305" "16306" "16307" "16308"
## [16309] "16309" "16310" "16311" "16312" "16313" "16314" "16315" "16316" "16317"
## [16318] "16318" "16319" "16320" "16321" "16322" "16323" "16324" "16325" "16326"
## [16327] "16327" "16328" "16329" "16330" "16331" "16332" "16333" "16334" "16335"
## [16336] "16336" "16337" "16338" "16339" "16340" "16341" "16342" "16343" "16344"
## [16345] "16345" "16346" "16347" "16348" "16349" "16350" "16351" "16352" "16353"
## [16354] "16354" "16355" "16356" "16357" "16358" "16359" "16360" "16361" "16362"
## [16363] "16363" "16364" "16365" "16366" "16367" "16368" "16369" "16370" "16371"
## [16372] "16372" "16373" "16374" "16375" "16376" "16377" "16378" "16379" "16380"
## [16381] "16381" "16382" "16383" "16384" "16385" "16386" "16387" "16388" "16389"
## [16390] "16390" "16391" "16392" "16393" "16394" "16395" "16396" "16397" "16398"
## [16399] "16399" "16400" "16401" "16402" "16403" "16404" "16405" "16406" "16407"
## [16408] "16408" "16409" "16410" "16411" "16412" "16413" "16414" "16415" "16416"
## [16417] "16417" "16418" "16419" "16420" "16421" "16422" "16423" "16424" "16425"
## [16426] "16426" "16427" "16428" "16429" "16430" "16431" "16432" "16433" "16434"
## [16435] "16435" "16436" "16437" "16438" "16439" "16440" "16441" "16442" "16443"
## [16444] "16444" "16445" "16446" "16447" "16448" "16449" "16450" "16451" "16452"
## [16453] "16453" "16454" "16455" "16456" "16457" "16458" "16459" "16460" "16461"
## [16462] "16462" "16463" "16464" "16465" "16466" "16467" "16468" "16469" "16470"
## [16471] "16471" "16472" "16473" "16474" "16475" "16476" "16477" "16478" "16479"
## [16480] "16480" "16481" "16482" "16483" "16484" "16485" "16486" "16487" "16488"
## [16489] "16489" "16490" "16491" "16492" "16493" "16494" "16495" "16496" "16497"
## [16498] "16498" "16499" "16500" "16501" "16502" "16503" "16504" "16505" "16506"
## [16507] "16507" "16508" "16509" "16510" "16511" "16512" "16513" "16514" "16515"
## [16516] "16516" "16517" "16518" "16519" "16520" "16521" "16522" "16523" "16524"
## [16525] "16525" "16526" "16527" "16528" "16529" "16530" "16531" "16532" "16533"
## [16534] "16534" "16535" "16536" "16537" "16538" "16539" "16540" "16541" "16542"
## [16543] "16543" "16544" "16545" "16546" "16547" "16548" "16549" "16550" "16551"
## [16552] "16552" "16553" "16554" "16555" "16556" "16557" "16558" "16559" "16560"
## [16561] "16561" "16562" "16563" "16564" "16565" "16566" "16567" "16568" "16569"
## [16570] "16570" "16571" "16572" "16573" "16574" "16575" "16576" "16577" "16578"
## [16579] "16579" "16580" "16581" "16582" "16583" "16584" "16585" "16586" "16587"
## [16588] "16588" "16589" "16590" "16591" "16592" "16593" "16594" "16595" "16596"
## [16597] "16597" "16598" "16599" "16600" "16601" "16602" "16603" "16604" "16605"
## [16606] "16606" "16607" "16608" "16609" "16610" "16611" "16612" "16613" "16614"
## [16615] "16615" "16616" "16617" "16618" "16619" "16620" "16621" "16622" "16623"
## [16624] "16624" "16625" "16626" "16627" "16628" "16629" "16630" "16631" "16632"
## [16633] "16633" "16634" "16635" "16636" "16637" "16638" "16639" "16640" "16641"
## [16642] "16642" "16643" "16644" "16645" "16646" "16647" "16648" "16649" "16650"
## [16651] "16651" "16652" "16653" "16654" "16655" "16656" "16657" "16658" "16659"
## [16660] "16660" "16661" "16662" "16663" "16664" "16665" "16666" "16667" "16668"
## [16669] "16669" "16670" "16671" "16672" "16673" "16674" "16675" "16676" "16677"
## [16678] "16678" "16679" "16680" "16681" "16682" "16683" "16684" "16685" "16686"
## [16687] "16687" "16688" "16689" "16690" "16691" "16692" "16693" "16694" "16695"
## [16696] "16696" "16697" "16698" "16699" "16700" "16701" "16702" "16703" "16704"
## [16705] "16705" "16706" "16707" "16708" "16709" "16710" "16711" "16712" "16713"
## [16714] "16714" "16715" "16716" "16717" "16718" "16719" "16720" "16721" "16722"
## [16723] "16723" "16724" "16725" "16726" "16727" "16728" "16729" "16730" "16731"
## [16732] "16732" "16733" "16734" "16735" "16736" "16737" "16738" "16739" "16740"
## [16741] "16741" "16742" "16743" "16744" "16745" "16746" "16747" "16748" "16749"
## [16750] "16750" "16751" "16752" "16753" "16754" "16755" "16756" "16757" "16758"
## [16759] "16759" "16760" "16761" "16762" "16763" "16764" "16765" "16766" "16767"
## [16768] "16768" "16769" "16770" "16771" "16772" "16773" "16774" "16775" "16776"
## [16777] "16777" "16778" "16779" "16780" "16781" "16782" "16783" "16784" "16785"
## [16786] "16786" "16787" "16788" "16789" "16790" "16791" "16792" "16793" "16794"
## [16795] "16795" "16796" "16797" "16798" "16799" "16800" "16801" "16802" "16803"
## [16804] "16804" "16805" "16806" "16807" "16808" "16809" "16810" "16811" "16812"
## [16813] "16813" "16814" "16815" "16816" "16817" "16818" "16819" "16820" "16821"
## [16822] "16822" "16823" "16824" "16825" "16826" "16827" "16828" "16829" "16830"
## [16831] "16831" "16832" "16833" "16834" "16835" "16836" "16837" "16838" "16839"
## [16840] "16840" "16841" "16842" "16843" "16844" "16845" "16846" "16847" "16848"
## [16849] "16849" "16850" "16851" "16852" "16853" "16854" "16855" "16856" "16857"
## [16858] "16858" "16859" "16860" "16861" "16862" "16863" "16864" "16865" "16866"
## [16867] "16867" "16868" "16869" "16870" "16871" "16872" "16873" "16874" "16875"
## [16876] "16876" "16877" "16878" "16879" "16880" "16881" "16882" "16883" "16884"
## [16885] "16885" "16886" "16887" "16888" "16889" "16890" "16891" "16892" "16893"
## [16894] "16894" "16895" "16896" "16897" "16898" "16899" "16900" "16901" "16902"
## [16903] "16903" "16904" "16905" "16906" "16907" "16908" "16909" "16910" "16911"
## [16912] "16912" "16913" "16914" "16915" "16916" "16917" "16918" "16919" "16920"
## [16921] "16921" "16922" "16923" "16924" "16925" "16926" "16927" "16928" "16929"
## [16930] "16930" "16931" "16932" "16933" "16934" "16935" "16936" "16937" "16938"
## [16939] "16939" "16940" "16941" "16942" "16943" "16944" "16945" "16946" "16947"
## [16948] "16948" "16949" "16950" "16951" "16952" "16953" "16954" "16955" "16956"
## [16957] "16957" "16958" "16959" "16960" "16961" "16962" "16963" "16964" "16965"
## [16966] "16966" "16967" "16968" "16969" "16970" "16971" "16972" "16973" "16974"
## [16975] "16975" "16976" "16977" "16978" "16979" "16980" "16981" "16982" "16983"
## [16984] "16984" "16985" "16986" "16987" "16988" "16989" "16990" "16991" "16992"
## [16993] "16993" "16994" "16995" "16996" "16997" "16998" "16999" "17000" "17001"
## [17002] "17002" "17003" "17004" "17005" "17006" "17007" "17008" "17009" "17010"
## [17011] "17011" "17012" "17013" "17014" "17015" "17016" "17017" "17018" "17019"
## [17020] "17020" "17021" "17022" "17023" "17024" "17025" "17026" "17027" "17028"
## [17029] "17029" "17030" "17031" "17032" "17033" "17034" "17035" "17036" "17037"
## [17038] "17038" "17039" "17040" "17041" "17042" "17043" "17044" "17045" "17046"
## [17047] "17047" "17048" "17049" "17050" "17051" "17052" "17053" "17054" "17055"
## [17056] "17056" "17057" "17058" "17059" "17060" "17061" "17062" "17063" "17064"
## [17065] "17065" "17066" "17067" "17068" "17069" "17070" "17071" "17072" "17073"
## [17074] "17074" "17075" "17076" "17077" "17078" "17079" "17080" "17081" "17082"
## [17083] "17083" "17084" "17085" "17086" "17087" "17088" "17089" "17090" "17091"
## [17092] "17092" "17093" "17094" "17095" "17096" "17097" "17098" "17099" "17100"
## [17101] "17101" "17102" "17103" "17104" "17105" "17106" "17107" "17108" "17109"
## [17110] "17110" "17111" "17112" "17113" "17114" "17115" "17116" "17117" "17118"
## [17119] "17119" "17120" "17121" "17122" "17123" "17124" "17125" "17126" "17127"
## [17128] "17128" "17129" "17130" "17131" "17132" "17133" "17134" "17135" "17136"
## [17137] "17137" "17138" "17139" "17140" "17141" "17142" "17143" "17144" "17145"
## [17146] "17146" "17147" "17148" "17149" "17150" "17151" "17152" "17153" "17154"
## [17155] "17155" "17156" "17157" "17158" "17159" "17160" "17161" "17162" "17163"
## [17164] "17164" "17165" "17166" "17167" "17168" "17169" "17170" "17171" "17172"
## [17173] "17173" "17174" "17175" "17176" "17177" "17178" "17179" "17180" "17181"
## [17182] "17182" "17183" "17184" "17185" "17186" "17187" "17188" "17189" "17190"
## [17191] "17191" "17192" "17193" "17194" "17195" "17196" "17197" "17198" "17199"
## [17200] "17200" "17201" "17202" "17203" "17204" "17205" "17206" "17207" "17208"
## [17209] "17209" "17210" "17211" "17212" "17213" "17214" "17215" "17216" "17217"
## [17218] "17218" "17219" "17220" "17221" "17222" "17223" "17224" "17225" "17226"
## [17227] "17227" "17228" "17229" "17230" "17231" "17232" "17233" "17234" "17235"
## [17236] "17236" "17237" "17238" "17239" "17240" "17241" "17242" "17243" "17244"
## [17245] "17245" "17246" "17247" "17248" "17249" "17250" "17251" "17252" "17253"
## [17254] "17254" "17255" "17256" "17257" "17258" "17259" "17260" "17261" "17262"
## [17263] "17263" "17264" "17265" "17266" "17267" "17268" "17269" "17270" "17271"
## [17272] "17272" "17273" "17274" "17275" "17276" "17277" "17278" "17279" "17280"
## [17281] "17281" "17282" "17283" "17284" "17285" "17286" "17287" "17288" "17289"
## [17290] "17290" "17291" "17292" "17293" "17294" "17295" "17296" "17297" "17298"
## [17299] "17299" "17300" "17301" "17302" "17303" "17304" "17305" "17306" "17307"
## [17308] "17308" "17309" "17310" "17311" "17312" "17313" "17314" "17315" "17316"
## [17317] "17317" "17318" "17319" "17320" "17321" "17322" "17323" "17324" "17325"
## [17326] "17326" "17327" "17328" "17329" "17330" "17331" "17332" "17333" "17334"
## [17335] "17335" "17336" "17337" "17338" "17339" "17340" "17341" "17342" "17343"
## [17344] "17344" "17345" "17346" "17347" "17348" "17349" "17350" "17351" "17352"
## [17353] "17353" "17354" "17355" "17356" "17357" "17358" "17359" "17360" "17361"
## [17362] "17362" "17363" "17364" "17365" "17366" "17367" "17368" "17369" "17370"
## [17371] "17371" "17372" "17373" "17374" "17375" "17376" "17377" "17378" "17379"
## [17380] "17380" "17381" "17382" "17383" "17384" "17385" "17386" "17387" "17388"
## [17389] "17389" "17390" "17391" "17392" "17393" "17394" "17395" "17396" "17397"
## [17398] "17398" "17399" "17400" "17401" "17402" "17403" "17404" "17405" "17406"
## [17407] "17407" "17408" "17409" "17410" "17411" "17412" "17413" "17414" "17415"
## [17416] "17416" "17417" "17418" "17419" "17420" "17421" "17422" "17423" "17424"
## [17425] "17425" "17426" "17427" "17428" "17429" "17430" "17431" "17432" "17433"
## [17434] "17434" "17435" "17436" "17437" "17438" "17439" "17440" "17441" "17442"
## [17443] "17443" "17444" "17445" "17446" "17447" "17448" "17449" "17450" "17451"
## [17452] "17452" "17453" "17454" "17455" "17456" "17457" "17458" "17459" "17460"
## [17461] "17461" "17462" "17463" "17464" "17465" "17466" "17467" "17468" "17469"
## [17470] "17470" "17471" "17472" "17473" "17474" "17475" "17476" "17477" "17478"
## [17479] "17479" "17480" "17481" "17482" "17483" "17484" "17485" "17486" "17487"
## [17488] "17488" "17489" "17490" "17491" "17492" "17493" "17494" "17495" "17496"
## [17497] "17497" "17498" "17499" "17500" "17501" "17502" "17503" "17504" "17505"
## [17506] "17506" "17507" "17508" "17509" "17510" "17511" "17512" "17513" "17514"
## [17515] "17515" "17516" "17517" "17518" "17519" "17520" "17521" "17522" "17523"
## [17524] "17524" "17525" "17526" "17527" "17528" "17529" "17530" "17531" "17532"
## [17533] "17533" "17534" "17535" "17536" "17537" "17538" "17539" "17540" "17541"
## [17542] "17542" "17543" "17544" "17545" "17546" "17547" "17548" "17549" "17550"
## [17551] "17551" "17552" "17553" "17554" "17555" "17556" "17557" "17558" "17559"
## [17560] "17560" "17561" "17562" "17563" "17564" "17565" "17566" "17567" "17568"
## [17569] "17569" "17570" "17571" "17572" "17573" "17574" "17575" "17576" "17577"
## [17578] "17578" "17579" "17580" "17581" "17582" "17583" "17584" "17585" "17586"
## [17587] "17587" "17588" "17589" "17590" "17591" "17592" "17593" "17594" "17595"
## [17596] "17596" "17597" "17598" "17599" "17600" "17601" "17602" "17603" "17604"
## [17605] "17605" "17606" "17607" "17608" "17609" "17610" "17611" "17612" "17613"
## [17614] "17614" "17615" "17616" "17617" "17618" "17619" "17620" "17621" "17622"
## [17623] "17623" "17624" "17625" "17626" "17627" "17628" "17629" "17630" "17631"
## [17632] "17632" "17633" "17634" "17635" "17636" "17637" "17638" "17639" "17640"
## [17641] "17641" "17642" "17643" "17644" "17645" "17646" "17647" "17648" "17649"
## [17650] "17650" "17651" "17652" "17653" "17654" "17655" "17656" "17657" "17658"
## [17659] "17659" "17660" "17661" "17662" "17663" "17664" "17665" "17666" "17667"
## [17668] "17668" "17669" "17670" "17671" "17672" "17673" "17674" "17675" "17676"
## [17677] "17677" "17678" "17679" "17680" "17681" "17682" "17683" "17684" "17685"
## [17686] "17686" "17687" "17688" "17689" "17690" "17691" "17692" "17693" "17694"
## [17695] "17695" "17696" "17697" "17698" "17699" "17700" "17701" "17702" "17703"
## [17704] "17704" "17705" "17706" "17707" "17708" "17709" "17710" "17711" "17712"
## [17713] "17713" "17714" "17715" "17716" "17717" "17718" "17719" "17720" "17721"
## [17722] "17722" "17723" "17724" "17725" "17726" "17727" "17728" "17729" "17730"
## [17731] "17731" "17732" "17733" "17734" "17735" "17736" "17737" "17738" "17739"
## [17740] "17740" "17741" "17742" "17743" "17744" "17745" "17746" "17747" "17748"
## [17749] "17749" "17750" "17751" "17752" "17753" "17754" "17755" "17756" "17757"
## [17758] "17758" "17759" "17760" "17761" "17762" "17763" "17764" "17765" "17766"
## [17767] "17767" "17768" "17769" "17770" "17771" "17772" "17773" "17774" "17775"
## [17776] "17776" "17777" "17778" "17779" "17780" "17781" "17782" "17783" "17784"
## [17785] "17785" "17786" "17787" "17788" "17789" "17790" "17791" "17792" "17793"
## [17794] "17794" "17795" "17796" "17797" "17798" "17799" "17800" "17801" "17802"
## [17803] "17803" "17804" "17805" "17806" "17807" "17808" "17809" "17810" "17811"
## [17812] "17812" "17813" "17814" "17815" "17816" "17817" "17818" "17819" "17820"
## [17821] "17821" "17822" "17823" "17824" "17825" "17826" "17827" "17828" "17829"
## [17830] "17830" "17831" "17832" "17833" "17834" "17835" "17836" "17837" "17838"
## [17839] "17839" "17840" "17841" "17842" "17843" "17844" "17845" "17846" "17847"
## [17848] "17848" "17849" "17850" "17851" "17852" "17853" "17854" "17855" "17856"
## [17857] "17857" "17858" "17859" "17860" "17861" "17862" "17863" "17864" "17865"
## [17866] "17866" "17867" "17868" "17869" "17870" "17871" "17872" "17873" "17874"
## [17875] "17875" "17876" "17877" "17878" "17879" "17880" "17881" "17882" "17883"
## [17884] "17884" "17885" "17886" "17887" "17888" "17889" "17890" "17891" "17892"
## [17893] "17893" "17894" "17895" "17896" "17897" "17898" "17899" "17900" "17901"
## [17902] "17902" "17903" "17904" "17905" "17906" "17907" "17908" "17909" "17910"
## [17911] "17911" "17912" "17913" "17914" "17915" "17916" "17917" "17918" "17919"
## [17920] "17920" "17921" "17922" "17923" "17924" "17925" "17926" "17927" "17928"
## [17929] "17929" "17930" "17931" "17932" "17933" "17934" "17935" "17936" "17937"
## [17938] "17938" "17939" "17940" "17941" "17942" "17943" "17944" "17945" "17946"
## [17947] "17947" "17948" "17949" "17950" "17951" "17952" "17953" "17954" "17955"
## [17956] "17956" "17957" "17958" "17959" "17960" "17961" "17962" "17963" "17964"
## [17965] "17965" "17966" "17967" "17968" "17969" "17970" "17971" "17972" "17973"
## [17974] "17974" "17975" "17976" "17977" "17978" "17979" "17980" "17981" "17982"
## [17983] "17983" "17984" "17985" "17986" "17987" "17988" "17989" "17990" "17991"
## [17992] "17992" "17993" "17994" "17995" "17996" "17997" "17998" "17999" "18000"
## [18001] "18001" "18002" "18003" "18004" "18005" "18006" "18007" "18008" "18009"
## [18010] "18010" "18011" "18012" "18013" "18014" "18015" "18016" "18017" "18018"
## [18019] "18019" "18020" "18021" "18022" "18023" "18024" "18025" "18026" "18027"
## [18028] "18028" "18029" "18030" "18031" "18032" "18033" "18034" "18035" "18036"
## [18037] "18037" "18038" "18039" "18040" "18041" "18042" "18043" "18044" "18045"
## [18046] "18046" "18047" "18048" "18049" "18050" "18051" "18052" "18053" "18054"
## [18055] "18055" "18056" "18057" "18058" "18059" "18060" "18061" "18062" "18063"
## [18064] "18064" "18065" "18066" "18067" "18068" "18069" "18070" "18071" "18072"
## [18073] "18073" "18074" "18075" "18076" "18077" "18078" "18079" "18080" "18081"
## [18082] "18082" "18083" "18084" "18085" "18086" "18087" "18088" "18089" "18090"
## [18091] "18091" "18092" "18093" "18094" "18095" "18096" "18097" "18098" "18099"
## [18100] "18100" "18101" "18102" "18103" "18104" "18105" "18106" "18107" "18108"
## [18109] "18109" "18110" "18111" "18112" "18113" "18114" "18115" "18116" "18117"
## [18118] "18118" "18119" "18120" "18121" "18122" "18123" "18124" "18125" "18126"
## [18127] "18127" "18128" "18129" "18130" "18131" "18132" "18133" "18134" "18135"
## [18136] "18136" "18137" "18138" "18139" "18140" "18141" "18142" "18143" "18144"
## [18145] "18145" "18146" "18147" "18148" "18149" "18150" "18151" "18152" "18153"
## [18154] "18154" "18155" "18156" "18157" "18158" "18159" "18160" "18161" "18162"
## [18163] "18163" "18164" "18165" "18166" "18167" "18168" "18169" "18170" "18171"
## [18172] "18172" "18173" "18174" "18175" "18176" "18177" "18178" "18179" "18180"
## [18181] "18181" "18182" "18183" "18184" "18185" "18186" "18187" "18188" "18189"
## [18190] "18190" "18191" "18192" "18193" "18194" "18195" "18196" "18197" "18198"
## [18199] "18199" "18200" "18201" "18202" "18203" "18204" "18205" "18206" "18207"
## [18208] "18208" "18209" "18210" "18211" "18212" "18213" "18214" "18215" "18216"
## [18217] "18217" "18218" "18219" "18220" "18221" "18222" "18223" "18224" "18225"
## [18226] "18226" "18227" "18228" "18229" "18230" "18231" "18232" "18233" "18234"
## [18235] "18235" "18236" "18237" "18238" "18239" "18240" "18241" "18242" "18243"
## [18244] "18244" "18245" "18246" "18247" "18248" "18249" "18250" "18251" "18252"
## [18253] "18253" "18254" "18255" "18256" "18257" "18258" "18259" "18260" "18261"
## [18262] "18262" "18263" "18264" "18265" "18266" "18267" "18268" "18269" "18270"
## [18271] "18271" "18272" "18273" "18274" "18275" "18276" "18277" "18278" "18279"
## [18280] "18280" "18281" "18282" "18283" "18284" "18285" "18286" "18287" "18288"
## [18289] "18289" "18290" "18291" "18292" "18293" "18294" "18295" "18296" "18297"
## [18298] "18298" "18299" "18300" "18301" "18302" "18303" "18304" "18305" "18306"
## [18307] "18307" "18308" "18309" "18310" "18311" "18312" "18313" "18314" "18315"
## [18316] "18316" "18317" "18318" "18319" "18320" "18321" "18322" "18323" "18324"
## [18325] "18325" "18326" "18327" "18328" "18329" "18330" "18331" "18332" "18333"
## [18334] "18334" "18335" "18336" "18337" "18338" "18339" "18340" "18341" "18342"
## [18343] "18343" "18344" "18345" "18346" "18347" "18348" "18349" "18350" "18351"
## [18352] "18352" "18353" "18354" "18355" "18356" "18357" "18358" "18359" "18360"
## [18361] "18361" "18362" "18363" "18364" "18365" "18366" "18367" "18368" "18369"
## [18370] "18370" "18371" "18372" "18373" "18374" "18375" "18376" "18377" "18378"
## [18379] "18379" "18380" "18381" "18382" "18383" "18384" "18385" "18386" "18387"
## [18388] "18388" "18389" "18390" "18391" "18392" "18393" "18394" "18395" "18396"
## [18397] "18397" "18398" "18399" "18400" "18401" "18402" "18403" "18404" "18405"
## [18406] "18406" "18407" "18408" "18409" "18410" "18411" "18412" "18413" "18414"
## [18415] "18415" "18416" "18417" "18418" "18419" "18420" "18421" "18422" "18423"
## [18424] "18424" "18425" "18426" "18427" "18428" "18429" "18430" "18431" "18432"
## [18433] "18433" "18434" "18435" "18436" "18437" "18438" "18439" "18440" "18441"
## [18442] "18442" "18443" "18444" "18445" "18446" "18447" "18448" "18449" "18450"
## [18451] "18451" "18452" "18453" "18454" "18455" "18456" "18457" "18458" "18459"
## [18460] "18460" "18461" "18462" "18463" "18464" "18465" "18466" "18467" "18468"
## [18469] "18469" "18470" "18471" "18472" "18473" "18474" "18475" "18476" "18477"
## [18478] "18478" "18479" "18480" "18481" "18482" "18483" "18484" "18485" "18486"
## [18487] "18487" "18488" "18489" "18490" "18491" "18492" "18493" "18494" "18495"
## [18496] "18496" "18497" "18498" "18499" "18500" "18501" "18502" "18503" "18504"
## [18505] "18505" "18506" "18507" "18508" "18509" "18510" "18511" "18512" "18513"
## [18514] "18514" "18515" "18516" "18517" "18518" "18519" "18520" "18521" "18522"
## [18523] "18523" "18524" "18525" "18526" "18527" "18528" "18529" "18530" "18531"
## [18532] "18532" "18533" "18534" "18535" "18536" "18537" "18538" "18539" "18540"
## [18541] "18541" "18542" "18543" "18544" "18545" "18546" "18547" "18548" "18549"
## [18550] "18550" "18551" "18552" "18553" "18554" "18555" "18556" "18557" "18558"
## [18559] "18559" "18560" "18561" "18562" "18563" "18564" "18565" "18566" "18567"
## [18568] "18568" "18569" "18570" "18571" "18572" "18573" "18574" "18575" "18576"
## [18577] "18577" "18578" "18579" "18580" "18581" "18582" "18583" "18584" "18585"
## [18586] "18586" "18587" "18588" "18589" "18590" "18591" "18592" "18593" "18594"
## [18595] "18595" "18596" "18597" "18598" "18599" "18600" "18601" "18602" "18603"
## [18604] "18604" "18605" "18606" "18607" "18608" "18609" "18610" "18611" "18612"
## [18613] "18613" "18614" "18615" "18616" "18617" "18618" "18619" "18620" "18621"
## [18622] "18622" "18623" "18624" "18625" "18626" "18627" "18628" "18629" "18630"
## [18631] "18631" "18632" "18633" "18634" "18635" "18636" "18637" "18638" "18639"
## [18640] "18640" "18641" "18642" "18643" "18644" "18645" "18646" "18647" "18648"
## [18649] "18649" "18650" "18651" "18652" "18653" "18654" "18655" "18656" "18657"
## [18658] "18658" "18659" "18660" "18661" "18662" "18663" "18664" "18665" "18666"
## [18667] "18667" "18668" "18669" "18670" "18671" "18672" "18673" "18674" "18675"
## [18676] "18676" "18677" "18678" "18679" "18680" "18681" "18682" "18683" "18684"
## [18685] "18685" "18686" "18687" "18688" "18689" "18690" "18691" "18692" "18693"
## [18694] "18694" "18695" "18696" "18697" "18698" "18699" "18700" "18701" "18702"
## [18703] "18703" "18704" "18705" "18706" "18707" "18708" "18709" "18710" "18711"
## [18712] "18712" "18713" "18714" "18715" "18716" "18717" "18718" "18719" "18720"
## [18721] "18721" "18722" "18723" "18724" "18725" "18726" "18727" "18728" "18729"
## [18730] "18730" "18731" "18732" "18733" "18734" "18735" "18736" "18737" "18738"
## [18739] "18739" "18740" "18741" "18742" "18743" "18744" "18745" "18746" "18747"
## [18748] "18748" "18749" "18750" "18751" "18752" "18753" "18754" "18755" "18756"
## [18757] "18757" "18758" "18759" "18760" "18761" "18762" "18763" "18764" "18765"
## [18766] "18766" "18767" "18768" "18769" "18770" "18771" "18772" "18773" "18774"
## [18775] "18775" "18776" "18777" "18778" "18779" "18780" "18781" "18782" "18783"
## [18784] "18784" "18785" "18786" "18787" "18788" "18789" "18790" "18791" "18792"
## [18793] "18793" "18794" "18795" "18796" "18797" "18798" "18799" "18800" "18801"
## [18802] "18802" "18803" "18804" "18805" "18806" "18807" "18808" "18809" "18810"
## [18811] "18811" "18812" "18813" "18814" "18815" "18816" "18817" "18818" "18819"
## [18820] "18820" "18821" "18822" "18823" "18824" "18825" "18826" "18827" "18828"
## [18829] "18829" "18830" "18831" "18832" "18833" "18834" "18835" "18836" "18837"
## [18838] "18838" "18839" "18840" "18841" "18842" "18843" "18844" "18845" "18846"
## [18847] "18847" "18848" "18849" "18850" "18851" "18852" "18853" "18854" "18855"
## [18856] "18856" "18857" "18858" "18859" "18860" "18861" "18862" "18863" "18864"
## [18865] "18865" "18866" "18867" "18868" "18869" "18870" "18871" "18872" "18873"
## [18874] "18874" "18875" "18876" "18877" "18878" "18879" "18880" "18881" "18882"
## [18883] "18883" "18884" "18885" "18886" "18887" "18888" "18889" "18890" "18891"
## [18892] "18892" "18893" "18894" "18895" "18896" "18897" "18898" "18899" "18900"
## [18901] "18901" "18902" "18903" "18904" "18905" "18906" "18907" "18908" "18909"
## [18910] "18910" "18911" "18912" "18913" "18914" "18915" "18916" "18917" "18918"
## [18919] "18919" "18920" "18921" "18922" "18923" "18924" "18925" "18926" "18927"
## [18928] "18928" "18929" "18930" "18931" "18932" "18933" "18934" "18935" "18936"
## [18937] "18937" "18938" "18939" "18940" "18941" "18942" "18943" "18944" "18945"
## [18946] "18946" "18947" "18948" "18949" "18950" "18951" "18952" "18953" "18954"
## [18955] "18955" "18956" "18957" "18958" "18959" "18960" "18961" "18962" "18963"
## [18964] "18964" "18965" "18966" "18967" "18968" "18969" "18970" "18971" "18972"
## [18973] "18973" "18974" "18975" "18976" "18977" "18978" "18979" "18980" "18981"
## [18982] "18982" "18983" "18984" "18985" "18986" "18987" "18988" "18989" "18990"
## [18991] "18991" "18992" "18993" "18994" "18995" "18996" "18997" "18998" "18999"
## [19000] "19000" "19001" "19002" "19003" "19004" "19005" "19006" "19007" "19008"
## [19009] "19009" "19010" "19011" "19012" "19013" "19014" "19015" "19016" "19017"
## [19018] "19018" "19019" "19020" "19021" "19022" "19023" "19024" "19025" "19026"
## [19027] "19027" "19028" "19029" "19030" "19031" "19032" "19033" "19034" "19035"
## [19036] "19036" "19037" "19038" "19039" "19040" "19041" "19042" "19043" "19044"
## [19045] "19045" "19046" "19047" "19048" "19049" "19050" "19051" "19052" "19053"
## [19054] "19054" "19055" "19056" "19057" "19058" "19059" "19060" "19061" "19062"
## [19063] "19063" "19064" "19065" "19066" "19067" "19068" "19069" "19070" "19071"
## [19072] "19072" "19073" "19074" "19075" "19076" "19077" "19078" "19079" "19080"
## [19081] "19081" "19082" "19083" "19084" "19085" "19086" "19087" "19088" "19089"
## [19090] "19090" "19091" "19092" "19093" "19094" "19095" "19096" "19097" "19098"
## [19099] "19099" "19100" "19101" "19102" "19103" "19104" "19105" "19106" "19107"
## [19108] "19108" "19109" "19110" "19111" "19112" "19113" "19114" "19115" "19116"
## [19117] "19117" "19118" "19119" "19120" "19121" "19122" "19123" "19124" "19125"
## [19126] "19126" "19127" "19128" "19129" "19130" "19131" "19132" "19133" "19134"
## [19135] "19135" "19136" "19137" "19138" "19139" "19140" "19141" "19142" "19143"
## [19144] "19144" "19145" "19146" "19147" "19148" "19149" "19150" "19151" "19152"
## [19153] "19153" "19154" "19155" "19156" "19157" "19158" "19159" "19160" "19161"
## [19162] "19162" "19163" "19164" "19165" "19166" "19167" "19168" "19169" "19170"
## [19171] "19171" "19172" "19173" "19174" "19175" "19176" "19177" "19178" "19179"
## [19180] "19180" "19181" "19182" "19183" "19184" "19185" "19186" "19187" "19188"
## [19189] "19189" "19190" "19191" "19192" "19193" "19194" "19195" "19196" "19197"
## [19198] "19198" "19199" "19200" "19201" "19202" "19203" "19204" "19205" "19206"
## [19207] "19207" "19208" "19209" "19210" "19211" "19212" "19213" "19214" "19215"
## [19216] "19216" "19217" "19218" "19219" "19220" "19221" "19222" "19223" "19224"
## [19225] "19225" "19226" "19227" "19228" "19229" "19230" "19231" "19232" "19233"
## [19234] "19234" "19235" "19236" "19237" "19238" "19239" "19240" "19241" "19242"
## [19243] "19243" "19244" "19245" "19246" "19247" "19248" "19249" "19250" "19251"
## [19252] "19252" "19253" "19254" "19255" "19256" "19257" "19258" "19259" "19260"
## [19261] "19261" "19262" "19263" "19264" "19265" "19266" "19267" "19268" "19269"
## [19270] "19270" "19271" "19272" "19273" "19274" "19275" "19276" "19277" "19278"
## [19279] "19279" "19280" "19281" "19282" "19283" "19284" "19285" "19286" "19287"
## [19288] "19288" "19289" "19290" "19291" "19292" "19293" "19294" "19295" "19296"
## [19297] "19297" "19298" "19299" "19300" "19301" "19302" "19303" "19304" "19305"
## [19306] "19306" "19307" "19308" "19309" "19310" "19311" "19312" "19313" "19314"
## [19315] "19315" "19316" "19317" "19318" "19319" "19320" "19321" "19322" "19323"
## [19324] "19324" "19325" "19326" "19327" "19328" "19329" "19330" "19331" "19332"
## [19333] "19333" "19334" "19335" "19336" "19337" "19338" "19339" "19340" "19341"
## [19342] "19342" "19343" "19344" "19345" "19346" "19347" "19348" "19349" "19350"
## [19351] "19351" "19352" "19353" "19354" "19355" "19356" "19357" "19358" "19359"
## [19360] "19360" "19361" "19362" "19363" "19364" "19365" "19366" "19367" "19368"
## [19369] "19369" "19370" "19371" "19372" "19373" "19374" "19375" "19376" "19377"
## [19378] "19378" "19379" "19380" "19381" "19382" "19383" "19384" "19385" "19386"
## [19387] "19387" "19388" "19389" "19390" "19391" "19392" "19393" "19394" "19395"
## [19396] "19396" "19397" "19398" "19399" "19400" "19401" "19402" "19403" "19404"
## [19405] "19405" "19406" "19407" "19408" "19409" "19410" "19411" "19412" "19413"
## [19414] "19414" "19415" "19416" "19417" "19418" "19419" "19420" "19421" "19422"
## [19423] "19423" "19424" "19425" "19426" "19427" "19428" "19429" "19430" "19431"
## [19432] "19432" "19433" "19434" "19435" "19436" "19437" "19438" "19439" "19440"
## [19441] "19441" "19442" "19443" "19444" "19445" "19446" "19447" "19448" "19449"
## [19450] "19450" "19451" "19452" "19453" "19454" "19455" "19456" "19457" "19458"
## [19459] "19459" "19460" "19461" "19462" "19463" "19464" "19465" "19466" "19467"
## [19468] "19468" "19469" "19470" "19471" "19472" "19473" "19474" "19475" "19476"
## [19477] "19477" "19478" "19479" "19480" "19481" "19482" "19483" "19484" "19485"
## [19486] "19486" "19487" "19488" "19489" "19490" "19491" "19492" "19493" "19494"
## [19495] "19495" "19496" "19497" "19498" "19499" "19500" "19501" "19502" "19503"
## [19504] "19504" "19505" "19506" "19507" "19508" "19509" "19510" "19511" "19512"
## [19513] "19513" "19514" "19515" "19516" "19517" "19518" "19519" "19520" "19521"
## [19522] "19522" "19523" "19524" "19525" "19526" "19527" "19528" "19529" "19530"
## [19531] "19531" "19532" "19533" "19534" "19535" "19536" "19537" "19538" "19539"
## [19540] "19540" "19541" "19542" "19543" "19544" "19545" "19546" "19547" "19548"
## [19549] "19549" "19550" "19551" "19552" "19553" "19554" "19555" "19556" "19557"
## [19558] "19558" "19559" "19560" "19561" "19562" "19563" "19564" "19565" "19566"
## [19567] "19567" "19568" "19569" "19570" "19571" "19572" "19573" "19574" "19575"
## [19576] "19576" "19577" "19578" "19579" "19580" "19581" "19582" "19583" "19584"
## [19585] "19585" "19586" "19587" "19588" "19589" "19590" "19591" "19592" "19593"
## [19594] "19594" "19595" "19596" "19597" "19598" "19599" "19600" "19601" "19602"
## [19603] "19603" "19604" "19605" "19606" "19607" "19608" "19609" "19610" "19611"
## [19612] "19612" "19613" "19614" "19615" "19616" "19617" "19618" "19619" "19620"
## [19621] "19621" "19622" "19623" "19624" "19625" "19626" "19627" "19628" "19629"
## [19630] "19630" "19631" "19632" "19633" "19634" "19635" "19636" "19637" "19638"
## [19639] "19639" "19640" "19641" "19642" "19643" "19644" "19645" "19646" "19647"
## [19648] "19648" "19649" "19650" "19651" "19652" "19653" "19654" "19655" "19656"
## [19657] "19657" "19658" "19659" "19660" "19661" "19662" "19663" "19664" "19665"
## [19666] "19666" "19667" "19668" "19669" "19670" "19671" "19672" "19673" "19674"
## [19675] "19675" "19676" "19677" "19678" "19679" "19680" "19681" "19682" "19683"
## [19684] "19684" "19685" "19686" "19687" "19688" "19689" "19690" "19691" "19692"
## [19693] "19693" "19694" "19695" "19696" "19697" "19698" "19699" "19700" "19701"
## [19702] "19702" "19703" "19704" "19705" "19706" "19707" "19708" "19709" "19710"
## [19711] "19711" "19712" "19713" "19714" "19715" "19716" "19717" "19718" "19719"
## [19720] "19720" "19721" "19722" "19723" "19724" "19725" "19726" "19727" "19728"
## [19729] "19729" "19730" "19731" "19732" "19733" "19734" "19735" "19736" "19737"
## [19738] "19738" "19739" "19740" "19741" "19742" "19743" "19744" "19745" "19746"
## [19747] "19747" "19748" "19749" "19750" "19751" "19752" "19753" "19754" "19755"
## [19756] "19756" "19757" "19758" "19759" "19760" "19761" "19762" "19763" "19764"
## [19765] "19765" "19766" "19767" "19768" "19769" "19770" "19771" "19772" "19773"
## [19774] "19774" "19775" "19776" "19777" "19778" "19779" "19780" "19781" "19782"
## [19783] "19783" "19784" "19785" "19786" "19787" "19788" "19789" "19790" "19791"
## [19792] "19792" "19793" "19794" "19795" "19796" "19797" "19798" "19799" "19800"
## [19801] "19801" "19802" "19803" "19804" "19805" "19806" "19807" "19808" "19809"
## [19810] "19810" "19811" "19812" "19813" "19814" "19815" "19816" "19817" "19818"
## [19819] "19819" "19820" "19821" "19822" "19823" "19824" "19825" "19826" "19827"
## [19828] "19828" "19829" "19830" "19831" "19832" "19833" "19834" "19835" "19836"
## [19837] "19837" "19838" "19839" "19840" "19841" "19842" "19843" "19844" "19845"
## [19846] "19846" "19847" "19848" "19849" "19850" "19851" "19852" "19853" "19854"
## [19855] "19855" "19856" "19857" "19858" "19859" "19860" "19861" "19862" "19863"
## [19864] "19864" "19865" "19866" "19867" "19868" "19869" "19870" "19871" "19872"
## [19873] "19873" "19874" "19875" "19876" "19877" "19878" "19879" "19880" "19881"
## [19882] "19882" "19883" "19884" "19885" "19886" "19887" "19888" "19889" "19890"
## [19891] "19891" "19892" "19893" "19894" "19895" "19896" "19897" "19898" "19899"
## [19900] "19900" "19901" "19902" "19903" "19904" "19905" "19906" "19907" "19908"
## [19909] "19909" "19910" "19911" "19912" "19913" "19914" "19915" "19916" "19917"
## [19918] "19918" "19919" "19920" "19921" "19922" "19923" "19924" "19925" "19926"
## [19927] "19927" "19928" "19929" "19930" "19931" "19932" "19933" "19934" "19935"
## [19936] "19936" "19937" "19938" "19939" "19940" "19941" "19942" "19943" "19944"
## [19945] "19945" "19946" "19947" "19948" "19949" "19950" "19951" "19952" "19953"
## [19954] "19954" "19955" "19956" "19957" "19958" "19959" "19960" "19961" "19962"
## [19963] "19963" "19964" "19965" "19966" "19967" "19968" "19969" "19970" "19971"
## [19972] "19972" "19973" "19974" "19975" "19976" "19977" "19978" "19979" "19980"
## [19981] "19981" "19982" "19983" "19984" "19985" "19986" "19987" "19988" "19989"
## [19990] "19990" "19991" "19992" "19993" "19994" "19995" "19996" "19997" "19998"
## [19999] "19999" "20000"mod1 <- tam.mml(score_ch2)## ....................................................
## Processing Data 2021-07-06 17:54:59
## * Response Data: 20000 Persons and 45 Items
## * Numerical integration with 21 nodes
## * Created Design Matrices ( 2021-07-06 17:54:59 )
## * Calculated Sufficient Statistics ( 2021-07-06 17:54:59 )
## ....................................................
## Iteration 1 2021-07-06 17:54:59
## E Step
## M Step Intercepts |---
## Deviance = 1093819.6228
## Maximum item intercept parameter change: 0.152202
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.466564
## ....................................................
## Iteration 2 2021-07-06 17:54:59
## E Step
## M Step Intercepts |--
## Deviance = 1089097.3929 | Absolute change: 4722.23 | Relative change: 0.00433591
## Maximum item intercept parameter change: 0.020631
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.070068
## ....................................................
## Iteration 3 2021-07-06 17:54:59
## E Step
## M Step Intercepts |--
## Deviance = 1088815.7625 | Absolute change: 281.6305 | Relative change: 0.00025866
## Maximum item intercept parameter change: 0.009255
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.024663
## ....................................................
## Iteration 4 2021-07-06 17:54:59
## E Step
## M Step Intercepts |--
## Deviance = 1088769.3046 | Absolute change: 46.4579 | Relative change: 4.267e-05
## Maximum item intercept parameter change: 0.00493
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.009745
## ....................................................
## Iteration 5 2021-07-06 17:55:00
## E Step
## M Step Intercepts |--
## Deviance = 1088759.9457 | Absolute change: 9.3589 | Relative change: 8.6e-06
## Maximum item intercept parameter change: 0.002975
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.004014
## ....................................................
## Iteration 6 2021-07-06 17:55:00
## E Step
## M Step Intercepts |--
## Deviance = 1088757.4146 | Absolute change: 2.5311 | Relative change: 2.32e-06
## Maximum item intercept parameter change: 0.001973
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001673
## ....................................................
## Iteration 7 2021-07-06 17:55:00
## E Step
## M Step Intercepts |--
## Deviance = 1088756.4125 | Absolute change: 1.002 | Relative change: 9.2e-07
## Maximum item intercept parameter change: 0.001401
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000695
## ....................................................
## Iteration 8 2021-07-06 17:55:00
## E Step
## M Step Intercepts |--
## Deviance = 1088755.8874 | Absolute change: 0.5251 | Relative change: 4.8e-07
## Maximum item intercept parameter change: 0.001041
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000282
## ....................................................
## Iteration 9 2021-07-06 17:55:00
## E Step
## M Step Intercepts |--
## Deviance = 1088755.5759 | Absolute change: 0.3115 | Relative change: 2.9e-07
## Maximum item intercept parameter change: 0.000796
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.00011
## ....................................................
## Iteration 10 2021-07-06 17:55:00
## E Step
## M Step Intercepts |--
## Deviance = 1088755.3834 | Absolute change: 0.1925 | Relative change: 1.8e-07
## Maximum item intercept parameter change: 0.000618
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 3.8e-05
## ....................................................
## Iteration 11 2021-07-06 17:55:00
## E Step
## M Step Intercepts |--
## Deviance = 1088755.2629 | Absolute change: 0.1205 | Relative change: 1.1e-07
## Maximum item intercept parameter change: 0.000485
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 9e-06
## ....................................................
## Iteration 12 2021-07-06 17:55:00
## E Step
## M Step Intercepts |--
## Deviance = 1088755.1872 | Absolute change: 0.0757 | Relative change: 7e-08
## Maximum item intercept parameter change: 0.000383
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 2e-06
## ....................................................
## Iteration 13 2021-07-06 17:55:00
## E Step
## M Step Intercepts |--
## Deviance = 1088755.1397 | Absolute change: 0.0476 | Relative change: 4e-08
## Maximum item intercept parameter change: 0.000304
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 5e-06
## ....................................................
## Iteration 14 2021-07-06 17:55:00
## E Step
## M Step Intercepts |--
## Deviance = 1088755.1098 | Absolute change: 0.0299 | Relative change: 3e-08
## Maximum item intercept parameter change: 0.000242
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 6e-06
## ....................................................
## Iteration 15 2021-07-06 17:55:00
## E Step
## M Step Intercepts |--
## Deviance = 1088755.091 | Absolute change: 0.0188 | Relative change: 2e-08
## Maximum item intercept parameter change: 0.000192
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 5e-06
## ....................................................
## Iteration 16 2021-07-06 17:55:00
## E Step
## M Step Intercepts |--
## Deviance = 1088755.0791 | Absolute change: 0.0118 | Relative change: 1e-08
## Maximum item intercept parameter change: 0.000152
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 4e-06
## ....................................................
## Iteration 17 2021-07-06 17:55:00
## E Step
## M Step Intercepts |--
## Deviance = 1088755.0717 | Absolute change: 0.0074 | Relative change: 1e-08
## Maximum item intercept parameter change: 0.000121
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 4e-06
## ....................................................
## Iteration 18 2021-07-06 17:55:00
## E Step
## M Step Intercepts |-
## Deviance = 1088755.067 | Absolute change: 0.0047 | Relative change: 0
## Maximum item intercept parameter change: 9.6e-05
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 3e-06
## ....................................................
## Iteration 19 2021-07-06 17:55:00
## E Step
## M Step Intercepts |-
## Deviance = 1088755.0641 | Absolute change: 0.0029 | Relative change: 0
## Maximum item intercept parameter change: 7.6e-05
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 2e-06
## ....................................................
## Iteration 20 2021-07-06 17:55:00
## E Step
## M Step Intercepts |-
## Deviance = 1088755.0622 | Absolute change: 0.0018 | Relative change: 0
## Maximum item intercept parameter change: 6e-05
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 2e-06
## ....................................................
## Iteration 21 2021-07-06 17:55:00
## E Step
## M Step Intercepts |-
## Deviance = 1088755.0611 | Absolute change: 0.0012 | Relative change: 0
## Maximum item intercept parameter change: 4.8e-05
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 2e-06
## ....................................................
## Iteration 22 2021-07-06 17:55:00
## E Step
## M Step Intercepts |-
## Deviance = 1088755.0604 | Absolute change: 7e-04 | Relative change: 0
## Maximum item intercept parameter change: 3.8e-05
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 1e-06
## ....................................................
## Item Parameters
## xsi.index xsi.label est
## 1 1 ch_1 0.1447
## 2 2 ch_2 -0.7542
## 3 3 ch_3 0.4091
## 4 4 ch_4 -0.6464
## 5 5 ch_5 1.6399
## 6 6 ch_6 0.4793
## 7 7 ch_7 1.4012
## 8 8 ch_8 0.1381
## 9 9 ch_9 -1.1684
## 10 10 ch_10 1.6059
## 11 11 ch_11 -1.0966
## 12 12 ch_12 0.0320
## 13 13 ch_13 0.5380
## 14 14 ch_14 0.1121
## 15 15 ch_15 0.7619
## 16 16 ch_16 1.2452
## 17 17 ch_17 -0.1462
## 18 18 ch_18 0.1110
## 19 19 ch_19 -0.1785
## 20 20 ch_20 1.8449
## 21 21 ch_21 -0.9990
## 22 22 ch_22 0.5162
## 23 23 ch_23 1.3103
## 24 24 ch_24 1.4476
## 25 25 ch_25 0.0092
## 26 26 ch_26 -0.4489
## 27 27 ch_27 -0.0345
## 28 28 ch_28 0.9492
## 29 29 ch_29 -0.0838
## 30 30 ch_30 1.0588
## 31 31 ch_31 0.5504
## 32 32 ch_32 0.5616
## 33 33 ch_33 0.1357
## 34 34 ch_34 0.6592
## 35 35 ch_35 1.5274
## 36 36 ch_36 0.4433
## 37 37 ch_37 0.2638
## 38 38 ch_38 0.5019
## 39 39 ch_39 0.7782
## 40 40 ch_40 0.9579
## 41 41 ch_41 0.7364
## 42 42 ch_42 -0.9822
## 43 43 ch_43 0.4004
## 44 44 ch_44 -0.7943
## 45 45 ch_45 0.3690
## ...................................
## Regression Coefficients
## [,1]
## [1,] 0
##
## Variance:
## [,1]
## [1,] 0.4222
##
##
## EAP Reliability:
## [1] 0.791
##
## -----------------------------
## Start: 2021-07-06 17:54:59
## End: 2021-07-06 17:55:01
## Time difference of 1.659583 secssummary(mod1)## ------------------------------------------------------------
## TAM 3.7-16 (2021-06-24 14:31:37)
## R version 4.0.2 (2020-06-22) x86_64, mingw32 | nodename=DESKTOP-U0L65SJ | login=araec
##
## Date of Analysis: 2021-07-06 17:55:01
## Time difference of 1.659583 secs
## Computation time: 1.659583
##
## Multidimensional Item Response Model in TAM
##
## IRT Model: 1PL
## Call:
## tam.mml(resp = score_ch2)
##
## ------------------------------------------------------------
## Number of iterations = 22
## Numeric integration with 21 integration points
##
## Deviance = 1088755
## Log likelihood = -544377.5
## Number of persons = 20000
## Number of persons used = 20000
## Number of items = 45
## Number of estimated parameters = 46
## Item threshold parameters = 45
## Item slope parameters = 0
## Regression parameters = 0
## Variance/covariance parameters = 1
##
## AIC = 1088847 | penalty=92 | AIC=-2*LL + 2*p
## AIC3 = 1088893 | penalty=138 | AIC3=-2*LL + 3*p
## BIC = 1089211 | penalty=455.56 | BIC=-2*LL + log(n)*p
## aBIC = 1089064 | penalty=309.37 | aBIC=-2*LL + log((n-2)/24)*p (adjusted BIC)
## CAIC = 1089257 | penalty=501.56 | CAIC=-2*LL + [log(n)+1]*p (consistent AIC)
## AICc = 1088847 | penalty=92.22 | AICc=-2*LL + 2*p + 2*p*(p+1)/(n-p-1) (bias corrected AIC)
## GHP = 0.60492 | GHP=( -LL + p ) / (#Persons * #Items) (Gilula-Haberman log penalty)
##
## ------------------------------------------------------------
## EAP Reliability
## [1] 0.791
## ------------------------------------------------------------
## Covariances and Variances
## [,1]
## [1,] 0.422
## ------------------------------------------------------------
## Correlations and Standard Deviations (in the diagonal)
## [,1]
## [1,] 0.65
## ------------------------------------------------------------
## Regression Coefficients
## [,1]
## [1,] 0
## ------------------------------------------------------------
## Item Parameters -A*Xsi
## item N M xsi.item AXsi_.Cat1 B.Cat1.Dim1
## 1 ch_1 20000 0.466 0.145 0.145 1
## 2 ch_2 20000 0.665 -0.754 -0.754 1
## 3 ch_3 20000 0.406 0.409 0.409 1
## 4 ch_4 20000 0.642 -0.646 -0.646 1
## 5 ch_5 20000 0.181 1.640 1.640 1
## 6 ch_6 20000 0.391 0.479 0.479 1
## 7 ch_7 20000 0.216 1.401 1.401 1
## 8 ch_8 20000 0.467 0.138 0.138 1
## 9 ch_9 20000 0.745 -1.168 -1.168 1
## 10 ch_10 20000 0.185 1.606 1.606 1
## 11 ch_11 20000 0.732 -1.097 -1.097 1
## 12 ch_12 20000 0.491 0.032 0.032 1
## 13 ch_13 20000 0.378 0.538 0.538 1
## 14 ch_14 20000 0.473 0.112 0.112 1
## 15 ch_15 20000 0.332 0.762 0.762 1
## 16 ch_16 20000 0.241 1.245 1.245 1
## 17 ch_17 20000 0.532 -0.146 -0.146 1
## 18 ch_18 20000 0.473 0.111 0.111 1
## 19 ch_19 20000 0.539 -0.179 -0.179 1
## 20 ch_20 20000 0.154 1.845 1.845 1
## 21 ch_21 20000 0.714 -0.999 -0.999 1
## 22 ch_22 20000 0.383 0.516 0.516 1
## 23 ch_23 20000 0.230 1.310 1.310 1
## 24 ch_24 20000 0.209 1.448 1.448 1
## 25 ch_25 20000 0.496 0.009 0.009 1
## 26 ch_26 20000 0.600 -0.449 -0.449 1
## 27 ch_27 20000 0.506 -0.034 -0.034 1
## 28 ch_28 20000 0.295 0.949 0.949 1
## 29 ch_29 20000 0.518 -0.084 -0.084 1
## 30 ch_30 20000 0.274 1.059 1.059 1
## 31 ch_31 20000 0.376 0.550 0.550 1
## 32 ch_32 20000 0.373 0.562 0.562 1
## 33 ch_33 20000 0.468 0.136 0.136 1
## 34 ch_34 20000 0.353 0.659 0.659 1
## 35 ch_35 20000 0.197 1.527 1.527 1
## 36 ch_36 20000 0.399 0.443 0.443 1
## 37 ch_37 20000 0.439 0.264 0.264 1
## 38 ch_38 20000 0.386 0.502 0.502 1
## 39 ch_39 20000 0.328 0.778 0.778 1
## 40 ch_40 20000 0.293 0.958 0.958 1
## 41 ch_41 20000 0.337 0.736 0.736 1
## 42 ch_42 20000 0.710 -0.982 -0.982 1
## 43 ch_43 20000 0.408 0.400 0.400 1
## 44 ch_44 20000 0.673 -0.794 -0.794 1
## 45 ch_45 20000 0.415 0.369 0.369 1
##
## Item Parameters in IRT parameterization
## item alpha beta
## 1 ch_1 1 0.145
## 2 ch_2 1 -0.754
## 3 ch_3 1 0.409
## 4 ch_4 1 -0.646
## 5 ch_5 1 1.640
## 6 ch_6 1 0.479
## 7 ch_7 1 1.401
## 8 ch_8 1 0.138
## 9 ch_9 1 -1.168
## 10 ch_10 1 1.606
## 11 ch_11 1 -1.097
## 12 ch_12 1 0.032
## 13 ch_13 1 0.538
## 14 ch_14 1 0.112
## 15 ch_15 1 0.762
## 16 ch_16 1 1.245
## 17 ch_17 1 -0.146
## 18 ch_18 1 0.111
## 19 ch_19 1 -0.179
## 20 ch_20 1 1.845
## 21 ch_21 1 -0.999
## 22 ch_22 1 0.516
## 23 ch_23 1 1.310
## 24 ch_24 1 1.448
## 25 ch_25 1 0.009
## 26 ch_26 1 -0.449
## 27 ch_27 1 -0.034
## 28 ch_28 1 0.949
## 29 ch_29 1 -0.084
## 30 ch_30 1 1.059
## 31 ch_31 1 0.550
## 32 ch_32 1 0.562
## 33 ch_33 1 0.136
## 34 ch_34 1 0.659
## 35 ch_35 1 1.527
## 36 ch_36 1 0.443
## 37 ch_37 1 0.264
## 38 ch_38 1 0.502
## 39 ch_39 1 0.778
## 40 ch_40 1 0.958
## 41 ch_41 1 0.736
## 42 ch_42 1 -0.982
## 43 ch_43 1 0.400
## 44 ch_44 1 -0.794
## 45 ch_45 1 0.369plot(mod1, items = 1:8, ngroups=10)## Iteration in WLE/MLE estimation 1 | Maximal change 0.6178
## Iteration in WLE/MLE estimation 2 | Maximal change 0.1747
## Iteration in WLE/MLE estimation 3 | Maximal change 0.0084
## Iteration in WLE/MLE estimation 4 | Maximal change 2e-04
## Iteration in WLE/MLE estimation 5 | Maximal change 0
## ----
## WLE Reliability= 0.784
## ....................................................
## Plots exported in png format into folder:
## C:/Users/araec/Documents/Doutorado/Disciplinas/1 semestre/TRI/Exercicios/Ex5/Plotshist(mod1$person$EAP)
hist(mod1$xsi$xsi)
fit <- tam.fit(mod1)## Item fit calculation based on 5 simulations
## |**********|
## |----------|fit$itemfit %>% viewCalibrando o modelo de dois parâmetros
dev.new()
mod2 <- tam.mml.2pl(score_ch2, irtmodel = "2PL")## ....................................................
## Processing Data 2021-07-06 17:55:08
## * Response Data: 20000 Persons and 45 Items
## * Numerical integration with 21 nodes
## * Created Design Matrices ( 2021-07-06 17:55:08 )
## * Calculated Sufficient Statistics ( 2021-07-06 17:55:08 )
## ....................................................
## Iteration 1 2021-07-06 17:55:08
## E Step
## M Step Intercepts |---
## M Step Slopes |----
## Deviance = 1093819.6228
## Maximum item intercept parameter change: 0.152202
## Maximum item slope parameter change: 0.679662
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 2 2021-07-06 17:55:08
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## Deviance = 1082677.1237 | Absolute change: 11142.5 | Relative change: 0.01029162
## Maximum item intercept parameter change: 0.143751
## Maximum item slope parameter change: 0.154405
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 3 2021-07-06 17:55:08
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## Deviance = 1080828.3119 | Absolute change: 1848.812 | Relative change: 0.00171055
## Maximum item intercept parameter change: 0.039215
## Maximum item slope parameter change: 0.070602
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 4 2021-07-06 17:55:08
## E Step
## M Step Intercepts |--
## M Step Slopes |---
## Deviance = 1080234.0128 | Absolute change: 594.2991 | Relative change: 0.00055016
## Maximum item intercept parameter change: 0.010473
## Maximum item slope parameter change: 0.056602
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 5 2021-07-06 17:55:09
## E Step
## M Step Intercepts |--
## M Step Slopes |---
## Deviance = 1079938.3147 | Absolute change: 295.6981 | Relative change: 0.00027381
## Maximum item intercept parameter change: 0.006863
## Maximum item slope parameter change: 0.044512
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 6 2021-07-06 17:55:09
## E Step
## M Step Intercepts |--
## M Step Slopes |---
## Deviance = 1079785.6568 | Absolute change: 152.6579 | Relative change: 0.00014138
## Maximum item intercept parameter change: 0.006707
## Maximum item slope parameter change: 0.032113
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 7 2021-07-06 17:55:09
## E Step
## M Step Intercepts |--
## M Step Slopes |---
## Deviance = 1079708.8865 | Absolute change: 76.7703 | Relative change: 7.11e-05
## Maximum item intercept parameter change: 0.005848
## Maximum item slope parameter change: 0.0226
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 8 2021-07-06 17:55:09
## E Step
## M Step Intercepts |--
## M Step Slopes |---
## Deviance = 1079671.2807 | Absolute change: 37.6058 | Relative change: 3.483e-05
## Maximum item intercept parameter change: 0.004929
## Maximum item slope parameter change: 0.016008
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 9 2021-07-06 17:55:09
## E Step
## M Step Intercepts |--
## M Step Slopes |--
## Deviance = 1079653.2003 | Absolute change: 18.0804 | Relative change: 1.675e-05
## Maximum item intercept parameter change: 0.003893
## Maximum item slope parameter change: 0.011112
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 10 2021-07-06 17:55:09
## E Step
## M Step Intercepts |--
## M Step Slopes |--
## Deviance = 1079644.6036 | Absolute change: 8.5968 | Relative change: 7.96e-06
## Maximum item intercept parameter change: 0.002987
## Maximum item slope parameter change: 0.007624
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 11 2021-07-06 17:55:09
## E Step
## M Step Intercepts |--
## M Step Slopes |--
## Deviance = 1079640.5342 | Absolute change: 4.0693 | Relative change: 3.77e-06
## Maximum item intercept parameter change: 0.002264
## Maximum item slope parameter change: 0.005194
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 12 2021-07-06 17:55:09
## E Step
## M Step Intercepts |--
## M Step Slopes |--
## Deviance = 1079638.6051 | Absolute change: 1.9292 | Relative change: 1.79e-06
## Maximum item intercept parameter change: 0.001712
## Maximum item slope parameter change: 0.003524
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 13 2021-07-06 17:55:09
## E Step
## M Step Intercepts |--
## M Step Slopes |--
## Deviance = 1079637.6838 | Absolute change: 0.9213 | Relative change: 8.5e-07
## Maximum item intercept parameter change: 0.001299
## Maximum item slope parameter change: 0.002386
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 14 2021-07-06 17:55:09
## E Step
## M Step Intercepts |--
## M Step Slopes |--
## Deviance = 1079637.2379 | Absolute change: 0.4458 | Relative change: 4.1e-07
## Maximum item intercept parameter change: 0.00099
## Maximum item slope parameter change: 0.001614
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 15 2021-07-06 17:55:09
## E Step
## M Step Intercepts |--
## M Step Slopes |--
## Deviance = 1079637.0179 | Absolute change: 0.22 | Relative change: 2e-07
## Maximum item intercept parameter change: 0.000761
## Maximum item slope parameter change: 0.001091
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 16 2021-07-06 17:55:09
## E Step
## M Step Intercepts |--
## M Step Slopes |--
## Deviance = 1079636.9065 | Absolute change: 0.1114 | Relative change: 1e-07
## Maximum item intercept parameter change: 0.000589
## Maximum item slope parameter change: 0.000738
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 17 2021-07-06 17:55:09
## E Step
## M Step Intercepts |--
## M Step Slopes |--
## Deviance = 1079636.8483 | Absolute change: 0.0582 | Relative change: 5e-08
## Maximum item intercept parameter change: 0.000459
## Maximum item slope parameter change: 5e-04
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 18 2021-07-06 17:55:09
## E Step
## M Step Intercepts |--
## M Step Slopes |--
## Deviance = 1079636.8168 | Absolute change: 0.0315 | Relative change: 3e-08
## Maximum item intercept parameter change: 0.00036
## Maximum item slope parameter change: 0.000339
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 19 2021-07-06 17:55:10
## E Step
## M Step Intercepts |--
## M Step Slopes |--
## Deviance = 1079636.7991 | Absolute change: 0.0177 | Relative change: 2e-08
## Maximum item intercept parameter change: 0.000285
## Maximum item slope parameter change: 0.00023
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 20 2021-07-06 17:55:10
## E Step
## M Step Intercepts |--
## M Step Slopes |--
## Deviance = 1079636.7887 | Absolute change: 0.0103 | Relative change: 1e-08
## Maximum item intercept parameter change: 0.000227
## Maximum item slope parameter change: 0.000157
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 21 2021-07-06 17:55:10
## E Step
## M Step Intercepts |--
## M Step Slopes |--
## Deviance = 1079636.7825 | Absolute change: 0.0062 | Relative change: 1e-08
## Maximum item intercept parameter change: 0.000181
## Maximum item slope parameter change: 0.000107
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 22 2021-07-06 17:55:10
## E Step
## M Step Intercepts |--
## M Step Slopes |-
## Deviance = 1079636.7786 | Absolute change: 0.0039 | Relative change: 0
## Maximum item intercept parameter change: 0.000145
## Maximum item slope parameter change: 7.3e-05
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 23 2021-07-06 17:55:10
## E Step
## M Step Intercepts |--
## M Step Slopes |-
## Deviance = 1079636.7761 | Absolute change: 0.0025 | Relative change: 0
## Maximum item intercept parameter change: 0.000117
## Maximum item slope parameter change: 5e-05
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 24 2021-07-06 17:55:10
## E Step
## M Step Intercepts |-
## M Step Slopes |-
## Deviance = 1079636.7746 | Absolute change: 0.0016 | Relative change: 0
## Maximum item intercept parameter change: 9.5e-05
## Maximum item slope parameter change: 3.5e-05
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 25 2021-07-06 17:55:10
## E Step
## M Step Intercepts |-
## M Step Slopes |-
## Deviance = 1079636.7735 | Absolute change: 0.001 | Relative change: 0
## Maximum item intercept parameter change: 7.7e-05
## Maximum item slope parameter change: 2.4e-05
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Iteration 26 2021-07-06 17:55:10
## E Step
## M Step Intercepts |-
## M Step Slopes |-
## Deviance = 1079636.7728 | Absolute change: 7e-04 | Relative change: 0
## Maximum item intercept parameter change: 6.3e-05
## Maximum item slope parameter change: 1.7e-05
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0
## ....................................................
## Item Parameters
## xsi.index xsi.label est
## 1 1 ch_1 0.1444
## 2 2 ch_2 -0.8857
## 3 3 ch_3 0.4286
## 4 4 ch_4 -0.6556
## 5 5 ch_5 1.8251
## 6 6 ch_6 0.4858
## 7 7 ch_7 1.3692
## 8 8 ch_8 0.1374
## 9 9 ch_9 -1.1780
## 10 10 ch_10 1.5787
## 11 11 ch_11 -1.0348
## 12 12 ch_12 0.0126
## 13 13 ch_13 0.6129
## 14 14 ch_14 0.1096
## 15 15 ch_15 0.8006
## 16 16 ch_16 1.1820
## 17 17 ch_17 -0.1379
## 18 18 ch_18 0.1095
## 19 19 ch_19 -0.2113
## 20 20 ch_20 1.7314
## 21 21 ch_21 -0.9801
## 22 22 ch_22 0.5257
## 23 23 ch_23 1.2225
## 24 24 ch_24 1.5778
## 25 25 ch_25 0.0064
## 26 26 ch_26 -0.4142
## 27 27 ch_27 -0.0609
## 28 28 ch_28 0.9612
## 29 29 ch_29 -0.1128
## 30 30 ch_30 1.0405
## 31 31 ch_31 0.5285
## 32 32 ch_32 0.5392
## 33 33 ch_33 0.1317
## 34 34 ch_34 0.6471
## 35 35 ch_35 1.5844
## 36 36 ch_36 0.4226
## 37 37 ch_37 0.2509
## 38 38 ch_38 0.5030
## 39 39 ch_39 0.8630
## 40 40 ch_40 0.8832
## 41 41 ch_41 0.7244
## 42 42 ch_42 -1.0664
## 43 43 ch_43 0.3986
## 44 44 ch_44 -0.7842
## 45 45 ch_45 0.3499
## ...................................
## Regression Coefficients
## [,1]
## [1,] 0
##
## Variance:
## [,1]
## [1,] 1
##
##
## EAP Reliability:
## [1] 0.819
##
## -----------------------------
## Start: 2021-07-06 17:55:08
## End: 2021-07-06 17:55:10
## Time difference of 2.268469 secssummary(mod2)## ------------------------------------------------------------
## TAM 3.7-16 (2021-06-24 14:31:37)
## R version 4.0.2 (2020-06-22) x86_64, mingw32 | nodename=DESKTOP-U0L65SJ | login=araec
##
## Date of Analysis: 2021-07-06 17:55:10
## Time difference of 2.268469 secs
## Computation time: 2.268469
##
## Multidimensional Item Response Model in TAM
##
## IRT Model: 2PL
## Call:
## tam.mml.2pl(resp = score_ch2, irtmodel = "2PL")
##
## ------------------------------------------------------------
## Number of iterations = 26
## Numeric integration with 21 integration points
##
## Deviance = 1079637
## Log likelihood = -539818.4
## Number of persons = 20000
## Number of persons used = 20000
## Number of items = 45
## Number of estimated parameters = 90
## Item threshold parameters = 45
## Item slope parameters = 45
## Regression parameters = 0
## Variance/covariance parameters = 0
##
## AIC = 1079817 | penalty=180 | AIC=-2*LL + 2*p
## AIC3 = 1079907 | penalty=270 | AIC3=-2*LL + 3*p
## BIC = 1080528 | penalty=891.31 | BIC=-2*LL + log(n)*p
## aBIC = 1080242 | penalty=605.28 | aBIC=-2*LL + log((n-2)/24)*p (adjusted BIC)
## CAIC = 1080618 | penalty=981.31 | CAIC=-2*LL + [log(n)+1]*p (consistent AIC)
## AICc = 1079818 | penalty=180.82 | AICc=-2*LL + 2*p + 2*p*(p+1)/(n-p-1) (bias corrected AIC)
## GHP = 0.5999 | GHP=( -LL + p ) / (#Persons * #Items) (Gilula-Haberman log penalty)
##
## ------------------------------------------------------------
## EAP Reliability
## [1] 0.819
## ------------------------------------------------------------
## Covariances and Variances
## [,1]
## [1,] 1
## ------------------------------------------------------------
## Correlations and Standard Deviations (in the diagonal)
## [,1]
## [1,] 1
## ------------------------------------------------------------
## Regression Coefficients
## [,1]
## [1,] 0
## ------------------------------------------------------------
## Item Parameters -A*Xsi
## item N M xsi.item AXsi_.Cat1 B.Cat1.Dim1
## 1 ch_1 20000 0.466 0.144 0.144 0.787
## 2 ch_2 20000 0.665 -0.886 -0.886 1.157
## 3 ch_3 20000 0.406 0.429 0.429 0.909
## 4 ch_4 20000 0.642 -0.656 -0.656 0.696
## 5 ch_5 20000 0.181 1.825 1.825 1.062
## 6 ch_6 20000 0.391 0.486 0.486 0.731
## 7 ch_7 20000 0.216 1.369 1.369 0.543
## 8 ch_8 20000 0.467 0.137 0.137 0.742
## 9 ch_9 20000 0.745 -1.178 -1.178 0.682
## 10 ch_10 20000 0.185 1.579 1.579 0.571
## 11 ch_11 20000 0.732 -1.035 -1.035 0.370
## 12 ch_12 20000 0.491 0.013 0.013 1.184
## 13 ch_13 20000 0.378 0.613 0.613 1.251
## 14 ch_14 20000 0.473 0.110 0.110 0.919
## 15 ch_15 20000 0.332 0.801 0.801 0.871
## 16 ch_16 20000 0.241 1.182 1.182 0.383
## 17 ch_17 20000 0.532 -0.138 -0.138 0.481
## 18 ch_18 20000 0.473 0.110 0.110 0.472
## 19 ch_19 20000 0.539 -0.211 -0.211 1.003
## 20 ch_20 20000 0.154 1.731 1.731 0.280
## 21 ch_21 20000 0.714 -0.980 -0.980 0.570
## 22 ch_22 20000 0.383 0.526 0.526 0.751
## 23 ch_23 20000 0.230 1.223 1.223 0.252
## 24 ch_24 20000 0.209 1.578 1.578 0.989
## 25 ch_25 20000 0.496 0.006 0.006 0.709
## 26 ch_26 20000 0.600 -0.414 -0.414 0.299
## 27 ch_27 20000 0.506 -0.061 -0.061 1.130
## 28 ch_28 20000 0.295 0.961 0.961 0.709
## 29 ch_29 20000 0.518 -0.113 -0.113 1.075
## 30 ch_30 20000 0.274 1.041 1.041 0.572
## 31 ch_31 20000 0.376 0.529 0.529 0.440
## 32 ch_32 20000 0.373 0.539 0.539 0.439
## 33 ch_33 20000 0.468 0.132 0.132 0.314
## 34 ch_34 20000 0.353 0.647 0.647 0.566
## 35 ch_35 20000 0.197 1.584 1.584 0.802
## 36 ch_36 20000 0.399 0.423 0.423 0.382
## 37 ch_37 20000 0.439 0.251 0.251 0.297
## 38 ch_38 20000 0.386 0.503 0.503 0.673
## 39 ch_39 20000 0.328 0.863 0.863 1.087
## 40 ch_40 20000 0.293 0.883 0.883 0.108
## 41 ch_41 20000 0.337 0.724 0.724 0.577
## 42 ch_42 20000 0.710 -1.066 -1.066 0.938
## 43 ch_43 20000 0.408 0.399 0.399 0.640
## 44 ch_44 20000 0.673 -0.784 -0.784 0.598
## 45 ch_45 20000 0.415 0.350 0.350 0.324
##
## Item Parameters in IRT parameterization
## item alpha beta
## 1 ch_1 0.787 0.184
## 2 ch_2 1.157 -0.766
## 3 ch_3 0.909 0.471
## 4 ch_4 0.696 -0.942
## 5 ch_5 1.062 1.718
## 6 ch_6 0.731 0.665
## 7 ch_7 0.543 2.520
## 8 ch_8 0.742 0.185
## 9 ch_9 0.682 -1.726
## 10 ch_10 0.571 2.763
## 11 ch_11 0.370 -2.796
## 12 ch_12 1.184 0.011
## 13 ch_13 1.251 0.490
## 14 ch_14 0.919 0.119
## 15 ch_15 0.871 0.919
## 16 ch_16 0.383 3.085
## 17 ch_17 0.481 -0.287
## 18 ch_18 0.472 0.232
## 19 ch_19 1.003 -0.211
## 20 ch_20 0.280 6.186
## 21 ch_21 0.570 -1.720
## 22 ch_22 0.751 0.700
## 23 ch_23 0.252 4.852
## 24 ch_24 0.989 1.595
## 25 ch_25 0.709 0.009
## 26 ch_26 0.299 -1.386
## 27 ch_27 1.130 -0.054
## 28 ch_28 0.709 1.355
## 29 ch_29 1.075 -0.105
## 30 ch_30 0.572 1.818
## 31 ch_31 0.440 1.202
## 32 ch_32 0.439 1.228
## 33 ch_33 0.314 0.419
## 34 ch_34 0.566 1.142
## 35 ch_35 0.802 1.975
## 36 ch_36 0.382 1.108
## 37 ch_37 0.297 0.845
## 38 ch_38 0.673 0.748
## 39 ch_39 1.087 0.794
## 40 ch_40 0.108 8.197
## 41 ch_41 0.577 1.255
## 42 ch_42 0.938 -1.136
## 43 ch_43 0.640 0.623
## 44 ch_44 0.598 -1.312
## 45 ch_45 0.324 1.079dev.new()
plot(mod2, items = 10, ngroups=10)## Iteration in WLE/MLE estimation 1 | Maximal change 1.7436
## Iteration in WLE/MLE estimation 2 | Maximal change 1.4653
## Iteration in WLE/MLE estimation 3 | Maximal change 1.0083
## Iteration in WLE/MLE estimation 4 | Maximal change 0.452
## Iteration in WLE/MLE estimation 5 | Maximal change 0.1178
## Iteration in WLE/MLE estimation 6 | Maximal change 0.0207
## Iteration in WLE/MLE estimation 7 | Maximal change 0.0032
## Iteration in WLE/MLE estimation 8 | Maximal change 5e-04
## Iteration in WLE/MLE estimation 9 | Maximal change 1e-04
## ----
## WLE Reliability= 0.811## ....................................................
## Plots exported in png format into folder:
## C:/Users/araec/Documents/Doutorado/Disciplinas/1 semestre/TRI/Exercicios/Ex5/Plotsdev.new()
plot(mod2, items = 14, ngroups=10)## Iteration in WLE/MLE estimation 1 | Maximal change 1.7436
## Iteration in WLE/MLE estimation 2 | Maximal change 1.4653
## Iteration in WLE/MLE estimation 3 | Maximal change 1.0083
## Iteration in WLE/MLE estimation 4 | Maximal change 0.452
## Iteration in WLE/MLE estimation 5 | Maximal change 0.1178
## Iteration in WLE/MLE estimation 6 | Maximal change 0.0207
## Iteration in WLE/MLE estimation 7 | Maximal change 0.0032
## Iteration in WLE/MLE estimation 8 | Maximal change 5e-04
## Iteration in WLE/MLE estimation 9 | Maximal change 1e-04
## ----
## WLE Reliability= 0.811## ....................................................
## Plots exported in png format into folder:
## C:/Users/araec/Documents/Doutorado/Disciplinas/1 semestre/TRI/Exercicios/Ex5/Plotsdev.new()
plot(mod2, items = 23, ngroups=10)## Iteration in WLE/MLE estimation 1 | Maximal change 1.7436
## Iteration in WLE/MLE estimation 2 | Maximal change 1.4653
## Iteration in WLE/MLE estimation 3 | Maximal change 1.0083
## Iteration in WLE/MLE estimation 4 | Maximal change 0.452
## Iteration in WLE/MLE estimation 5 | Maximal change 0.1178
## Iteration in WLE/MLE estimation 6 | Maximal change 0.0207
## Iteration in WLE/MLE estimation 7 | Maximal change 0.0032
## Iteration in WLE/MLE estimation 8 | Maximal change 5e-04
## Iteration in WLE/MLE estimation 9 | Maximal change 1e-04
## ----
## WLE Reliability= 0.811## ....................................................
## Plots exported in png format into folder:
## C:/Users/araec/Documents/Doutorado/Disciplinas/1 semestre/TRI/Exercicios/Ex5/Plotsdev.new()
plot(mod2, items = 35, ngroups=10)## Iteration in WLE/MLE estimation 1 | Maximal change 1.7436
## Iteration in WLE/MLE estimation 2 | Maximal change 1.4653
## Iteration in WLE/MLE estimation 3 | Maximal change 1.0083
## Iteration in WLE/MLE estimation 4 | Maximal change 0.452
## Iteration in WLE/MLE estimation 5 | Maximal change 0.1178
## Iteration in WLE/MLE estimation 6 | Maximal change 0.0207
## Iteration in WLE/MLE estimation 7 | Maximal change 0.0032
## Iteration in WLE/MLE estimation 8 | Maximal change 5e-04
## Iteration in WLE/MLE estimation 9 | Maximal change 1e-04
## ----
## WLE Reliability= 0.811## ....................................................
## Plots exported in png format into folder:
## C:/Users/araec/Documents/Doutorado/Disciplinas/1 semestre/TRI/Exercicios/Ex5/Plotshist(mod2$person$EAP)
hist(mod2$xsi$xsi)
fit <- tam.fit(mod2)## Item fit calculation based on 5 simulations
## |**********|
## |----------|mod2$item_irt %>% view
fit$itemfit %>% viewCalibrando o modelo de três parâmetros
mod3 <- tam.mml.3pl(
score_ch2,
control = list(maxiter=200, conv = .001),
est.guess = 1:ncol(score_ch2),
guess= rep(.20, ncol(score_ch2) )
)## ....................................................
## Processing Data 2021-07-06 17:55:40
## * Response Data: 20000 Persons and 45 Items
## * Numerical integration with 21 nodes
## * Created Design Matrices ( 2021-07-06 17:55:40 )
## * Calculated Sufficient Statistics ( 2021-07-06 17:55:40 )
## ....................................................
## Iteration 1 2021-07-06 17:55:40
## E Step
## M Step Intercepts |----------
## M Step Slopes |------
## M Step Guessing |-----
## Deviance = 1114750.9917
## Maximum item intercept parameter change: 5.198877
## Maximum item slope parameter change: 2.103718
## Maximum item guessing parameter change: 0.096999
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.184279
## ....................................................
## Iteration 2 2021-07-06 17:55:41
## E Step
## M Step Intercepts |-----
## M Step Slopes |-----
## M Step Guessing |---
## Deviance = 1085687.0878 | Absolute change: 29063.9 | Relative change: 0.02677006
## Maximum item intercept parameter change: 0.541484
## Maximum item slope parameter change: 0.672138
## Maximum item guessing parameter change: 0.018912
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.025763
## ....................................................
## Iteration 3 2021-07-06 17:55:41
## E Step
## M Step Intercepts |----
## M Step Slopes |-----
## M Step Guessing |---
## Deviance = 1081579.9959 | Absolute change: 4107.092 | Relative change: 0.00379731
## Maximum item intercept parameter change: 0.62438
## Maximum item slope parameter change: 0.572283
## Maximum item guessing parameter change: 0.046063
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.040256
## ....................................................
## Iteration 4 2021-07-06 17:55:41
## E Step
## M Step Intercepts |-----
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1080134.8956 | Absolute change: 1445.1 | Relative change: 0.00133789
## Maximum item intercept parameter change: 0.615255
## Maximum item slope parameter change: 0.505835
## Maximum item guessing parameter change: 0.026285
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.042706
## ....................................................
## Iteration 5 2021-07-06 17:55:42
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1079394.3863 | Absolute change: 740.5093 | Relative change: 0.00068604
## Maximum item intercept parameter change: 0.589923
## Maximum item slope parameter change: 0.452609
## Maximum item guessing parameter change: 0.009013
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.037981
## ....................................................
## Iteration 6 2021-07-06 17:55:42
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1079002.0778 | Absolute change: 392.3085 | Relative change: 0.00036358
## Maximum item intercept parameter change: 0.577813
## Maximum item slope parameter change: 0.406171
## Maximum item guessing parameter change: 0.003622
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.030794
## ....................................................
## Iteration 7 2021-07-06 17:55:42
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1078833.4585 | Absolute change: 168.6193 | Relative change: 0.0001563
## Maximum item intercept parameter change: 0.586259
## Maximum item slope parameter change: 0.366603
## Maximum item guessing parameter change: 0.002649
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.023362
## ....................................................
## Iteration 8 2021-07-06 17:55:43
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1078801.9676 | Absolute change: 31.4909 | Relative change: 2.919e-05
## Maximum item intercept parameter change: 0.588325
## Maximum item slope parameter change: 0.336685
## Maximum item guessing parameter change: 0.002295
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.016866
## ....................................................
## Iteration 9 2021-07-06 17:55:43
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1078850.711 | Absolute change: -48.7434 | Relative change: 4.518e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.582437
## Maximum item slope parameter change: 0.318488
## Maximum item guessing parameter change: 0.002271
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.011729
## ....................................................
## Iteration 10 2021-07-06 17:55:43
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1078944.505 | Absolute change: -93.794 | Relative change: 8.693e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.569201
## Maximum item slope parameter change: 0.301006
## Maximum item guessing parameter change: 0.002228
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.007869
## ....................................................
## Iteration 11 2021-07-06 17:55:43
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1079062.174 | Absolute change: -117.669 | Relative change: 0.00010905
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.551134
## Maximum item slope parameter change: 0.307024
## Maximum item guessing parameter change: 0.002161
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.005065
## ....................................................
## Iteration 12 2021-07-06 17:55:44
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1079191.1361 | Absolute change: -128.9621 | Relative change: 0.0001195
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.531277
## Maximum item slope parameter change: 0.316217
## Maximum item guessing parameter change: 0.002082
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.003104
## ....................................................
## Iteration 13 2021-07-06 17:55:44
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1079323.987 | Absolute change: -132.8509 | Relative change: 0.00012309
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.512025
## Maximum item slope parameter change: 0.327596
## Maximum item guessing parameter change: 0.001998
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001801
## ....................................................
## Iteration 14 2021-07-06 17:55:44
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1079456.3997 | Absolute change: -132.4127 | Relative change: 0.00012267
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.494711
## Maximum item slope parameter change: 0.340124
## Maximum item guessing parameter change: 0.001912
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000996
## ....................................................
## Iteration 15 2021-07-06 17:55:44
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1079585.8428 | Absolute change: -129.4431 | Relative change: 0.0001199
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.479766
## Maximum item slope parameter change: 0.352684
## Maximum item guessing parameter change: 0.001832
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000555
## ....................................................
## Iteration 16 2021-07-06 17:55:45
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1079710.8327 | Absolute change: -124.99 | Relative change: 0.00011576
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.46707
## Maximum item slope parameter change: 0.36426
## Maximum item guessing parameter change: 0.001747
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.00037
## ....................................................
## Iteration 17 2021-07-06 17:55:45
## E Step
## M Step Intercepts |----
## M Step Slopes |-----
## M Step Guessing |--
## Deviance = 1079830.5297 | Absolute change: -119.697 | Relative change: 0.00011085
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.456274
## Maximum item slope parameter change: 0.374161
## Maximum item guessing parameter change: 0.001671
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000351
## ....................................................
## Iteration 18 2021-07-06 17:55:45
## E Step
## M Step Intercepts |----
## M Step Slopes |-----
## M Step Guessing |--
## Deviance = 1079944.5283 | Absolute change: -113.9986 | Relative change: 0.00010556
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.447029
## Maximum item slope parameter change: 0.382131
## Maximum item guessing parameter change: 0.0016
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000427
## ....................................................
## Iteration 19 2021-07-06 17:55:46
## E Step
## M Step Intercepts |----
## M Step Slopes |-----
## M Step Guessing |--
## Deviance = 1080052.7366 | Absolute change: -108.2083 | Relative change: 0.00010019
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.448563
## Maximum item slope parameter change: 0.388297
## Maximum item guessing parameter change: 0.001534
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000548
## ....................................................
## Iteration 20 2021-07-06 17:55:46
## E Step
## M Step Intercepts |----
## M Step Slopes |-----
## M Step Guessing |--
## Deviance = 1080155.2855 | Absolute change: -102.5489 | Relative change: 9.494e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.453378
## Maximum item slope parameter change: 0.393007
## Maximum item guessing parameter change: 0.001471
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000678
## ....................................................
## Iteration 21 2021-07-06 17:55:46
## E Step
## M Step Intercepts |----
## M Step Slopes |-----
## M Step Guessing |--
## Deviance = 1080252.4512 | Absolute change: -97.1657 | Relative change: 8.995e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.457908
## Maximum item slope parameter change: 0.396669
## Maximum item guessing parameter change: 0.001412
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000794
## ....................................................
## Iteration 22 2021-07-06 17:55:47
## E Step
## M Step Intercepts |----
## M Step Slopes |-----
## M Step Guessing |--
## Deviance = 1080344.5918 | Absolute change: -92.1406 | Relative change: 8.529e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.462231
## Maximum item slope parameter change: 0.399643
## Maximum item guessing parameter change: 0.001355
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000886
## ....................................................
## Iteration 23 2021-07-06 17:55:47
## E Step
## M Step Intercepts |----
## M Step Slopes |-----
## M Step Guessing |--
## Deviance = 1080432.0987 | Absolute change: -87.5069 | Relative change: 8.099e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.466389
## Maximum item slope parameter change: 0.402203
## Maximum item guessing parameter change: 0.001301
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000949
## ....................................................
## Iteration 24 2021-07-06 17:55:47
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1080515.3632 | Absolute change: -83.2645 | Relative change: 7.706e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.470403
## Maximum item slope parameter change: 0.296102
## Maximum item guessing parameter change: 0.001251
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000985
## ....................................................
## Iteration 25 2021-07-06 17:55:47
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1080602.1074 | Absolute change: -86.7442 | Relative change: 8.027e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.420124
## Maximum item slope parameter change: 0.269413
## Maximum item guessing parameter change: 0.004614
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000422
## ....................................................
## Iteration 26 2021-07-06 17:55:48
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1080775.4574 | Absolute change: -173.35 | Relative change: 0.00016039
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.426409
## Maximum item slope parameter change: 0.272668
## Maximum item guessing parameter change: 0.001811
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001098
## ....................................................
## Iteration 27 2021-07-06 17:55:48
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1080893.8367 | Absolute change: -118.3793 | Relative change: 0.00010952
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.337005
## Maximum item slope parameter change: 0.277366
## Maximum item guessing parameter change: 0.001238
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001348
## ....................................................
## Iteration 28 2021-07-06 17:55:48
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1080986.7484 | Absolute change: -92.9117 | Relative change: 8.595e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.34083
## Maximum item slope parameter change: 0.281726
## Maximum item guessing parameter change: 0.001208
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001302
## ....................................................
## Iteration 29 2021-07-06 17:55:48
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1081069.1499 | Absolute change: -82.4015 | Relative change: 7.622e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.344787
## Maximum item slope parameter change: 0.261515
## Maximum item guessing parameter change: 0.001157
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001175
## ....................................................
## Iteration 30 2021-07-06 17:55:49
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1081151.7023 | Absolute change: -82.5524 | Relative change: 7.636e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.323295
## Maximum item slope parameter change: 0.266775
## Maximum item guessing parameter change: 0.003163
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001356
## ....................................................
## Iteration 31 2021-07-06 17:55:49
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1081270.3476 | Absolute change: -118.6453 | Relative change: 0.00010973
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.334208
## Maximum item slope parameter change: 0.272683
## Maximum item guessing parameter change: 0.001442
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001768
## ....................................................
## Iteration 32 2021-07-06 17:55:49
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1081377.0589 | Absolute change: -106.7113 | Relative change: 9.868e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.368727
## Maximum item slope parameter change: 0.279918
## Maximum item guessing parameter change: 0.001675
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.002379
## ....................................................
## Iteration 33 2021-07-06 17:55:49
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1081492.7423 | Absolute change: -115.6834 | Relative change: 0.00010697
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.402017
## Maximum item slope parameter change: 0.28759
## Maximum item guessing parameter change: 0.001114
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.002605
## ....................................................
## Iteration 34 2021-07-06 17:55:50
## E Step
## M Step Intercepts |-----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1081591.5686 | Absolute change: -98.8262 | Relative change: 9.137e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.433177
## Maximum item slope parameter change: 0.294977
## Maximum item guessing parameter change: 0.001057
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.002456
## ....................................................
## Iteration 35 2021-07-06 17:55:50
## E Step
## M Step Intercepts |-----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1081684.0426 | Absolute change: -92.4741 | Relative change: 8.549e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.478937
## Maximum item slope parameter change: 0.292418
## Maximum item guessing parameter change: 0.003903
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.002249
## ....................................................
## Iteration 36 2021-07-06 17:55:50
## E Step
## M Step Intercepts |-----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1081796.3742 | Absolute change: -112.3316 | Relative change: 0.00010384
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.616544
## Maximum item slope parameter change: 0.282631
## Maximum item guessing parameter change: 0.002014
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.002788
## ....................................................
## Iteration 37 2021-07-06 17:55:50
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1081916.7552 | Absolute change: -120.381 | Relative change: 0.00011127
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.740247
## Maximum item slope parameter change: 0.190373
## Maximum item guessing parameter change: 0.002847
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.002971
## ....................................................
## Iteration 38 2021-07-06 17:55:51
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1082027.1898 | Absolute change: -110.4346 | Relative change: 0.00010206
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.658294
## Maximum item slope parameter change: 0.198234
## Maximum item guessing parameter change: 0.002057
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.003163
## ....................................................
## Iteration 39 2021-07-06 17:55:51
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1082137.6393 | Absolute change: -110.4495 | Relative change: 0.00010207
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.431638
## Maximum item slope parameter change: 0.207053
## Maximum item guessing parameter change: 0.001238
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.003321
## ....................................................
## Iteration 40 2021-07-06 17:55:51
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1082253.4341 | Absolute change: -115.7948 | Relative change: 0.00010699
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.330461
## Maximum item slope parameter change: 0.217396
## Maximum item guessing parameter change: 0.00162
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.003328
## ....................................................
## Iteration 41 2021-07-06 17:55:52
## E Step
## M Step Intercepts |-----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1082372.9801 | Absolute change: -119.546 | Relative change: 0.00011045
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.351416
## Maximum item slope parameter change: 0.229891
## Maximum item guessing parameter change: 0.002807
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.003246
## ....................................................
## Iteration 42 2021-07-06 17:55:52
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1082508.5267 | Absolute change: -135.5466 | Relative change: 0.00012522
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.881636
## Maximum item slope parameter change: 0.245595
## Maximum item guessing parameter change: 0.006998
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.003191
## ....................................................
## Iteration 43 2021-07-06 17:55:52
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1082689.9361 | Absolute change: -181.4094 | Relative change: 0.00016755
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.896737
## Maximum item slope parameter change: 0.264146
## Maximum item guessing parameter change: 0.004385
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.003619
## ....................................................
## Iteration 44 2021-07-06 17:55:53
## E Step
## M Step Intercepts |----------
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1082791.705 | Absolute change: -101.7688 | Relative change: 9.399e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.907893
## Maximum item slope parameter change: 0.166288
## Maximum item guessing parameter change: 0.005527
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.004716
## ....................................................
## Iteration 45 2021-07-06 17:55:53
## E Step
## M Step Intercepts |----
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1082896.8846 | Absolute change: -105.1796 | Relative change: 9.713e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.931355
## Maximum item slope parameter change: 0.152505
## Maximum item guessing parameter change: 0.004139
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.005921
## ....................................................
## Iteration 46 2021-07-06 17:55:53
## E Step
## M Step Intercepts |----
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1083009.9395 | Absolute change: -113.0549 | Relative change: 0.00010439
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.493509
## Maximum item slope parameter change: 0.147142
## Maximum item guessing parameter change: 0.001711
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.006912
## ....................................................
## Iteration 47 2021-07-06 17:55:54
## E Step
## M Step Intercepts |----
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1083143.0403 | Absolute change: -133.1008 | Relative change: 0.00012288
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.354833
## Maximum item slope parameter change: 0.087784
## Maximum item guessing parameter change: 0.002244
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.007255
## ....................................................
## Iteration 48 2021-07-06 17:55:54
## E Step
## M Step Intercepts |------
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1083283.9092 | Absolute change: -140.8689 | Relative change: 0.00013004
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.49162
## Maximum item slope parameter change: 0.089536
## Maximum item guessing parameter change: 0.004881
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.007382
## ....................................................
## Iteration 49 2021-07-06 17:55:54
## E Step
## M Step Intercepts |----------
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1083450.2569 | Absolute change: -166.3477 | Relative change: 0.00015354
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.59486
## Maximum item slope parameter change: 0.091222
## Maximum item guessing parameter change: 0.004333
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.007632
## ....................................................
## Iteration 50 2021-07-06 17:55:55
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1083602.6092 | Absolute change: -152.3522 | Relative change: 0.0001406
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.850981
## Maximum item slope parameter change: 0.174509
## Maximum item guessing parameter change: 0.004316
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.007937
## ....................................................
## Iteration 51 2021-07-06 17:55:55
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1083714.4183 | Absolute change: -111.8091 | Relative change: 0.00010317
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.741369
## Maximum item slope parameter change: 0.102152
## Maximum item guessing parameter change: 0.002397
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.008855
## ....................................................
## Iteration 52 2021-07-06 17:55:55
## E Step
## M Step Intercepts |-----
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1083870.2534 | Absolute change: -155.8351 | Relative change: 0.00014378
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.36168
## Maximum item slope parameter change: 0.108335
## Maximum item guessing parameter change: 0.004917
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.009096
## ....................................................
## Iteration 53 2021-07-06 17:55:56
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1084073.416 | Absolute change: -203.1626 | Relative change: 0.00018741
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 1.156714
## Maximum item slope parameter change: 0.114488
## Maximum item guessing parameter change: 0.012449
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.009184
## ....................................................
## Iteration 54 2021-07-06 17:55:56
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1084333.4189 | Absolute change: -260.0029 | Relative change: 0.00023978
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.896364
## Maximum item slope parameter change: 0.210811
## Maximum item guessing parameter change: 0.005251
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.010608
## ....................................................
## Iteration 55 2021-07-06 17:55:57
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1084429.9395 | Absolute change: -96.5206 | Relative change: 8.901e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.795177
## Maximum item slope parameter change: 0.137395
## Maximum item guessing parameter change: 0.004196
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.0128
## ....................................................
## Iteration 56 2021-07-06 17:55:57
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1084618.256 | Absolute change: -188.3165 | Relative change: 0.00017362
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.596832
## Maximum item slope parameter change: 0.150476
## Maximum item guessing parameter change: 0.008039
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.01418
## ....................................................
## Iteration 57 2021-07-06 17:55:57
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1084885.2727 | Absolute change: -267.0167 | Relative change: 0.00024612
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.733823
## Maximum item slope parameter change: 0.162423
## Maximum item guessing parameter change: 0.006935
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.015536
## ....................................................
## Iteration 58 2021-07-06 17:55:58
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1085111.2531 | Absolute change: -225.9803 | Relative change: 0.00020826
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.711531
## Maximum item slope parameter change: 0.172703
## Maximum item guessing parameter change: 0.011188
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.017199
## ....................................................
## Iteration 59 2021-07-06 17:55:58
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1085339.3776 | Absolute change: -228.1245 | Relative change: 0.00021019
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 1.127399
## Maximum item slope parameter change: 0.180176
## Maximum item guessing parameter change: 0.007777
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.020082
## ....................................................
## Iteration 60 2021-07-06 17:55:59
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1085404.3861 | Absolute change: -65.0085 | Relative change: 5.989e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.974016
## Maximum item slope parameter change: 0.25782
## Maximum item guessing parameter change: 0.007144
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.022923
## ....................................................
## Iteration 61 2021-07-06 17:55:59
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1085231.7547 | Absolute change: 172.6313 | Relative change: 0.00015907
## Maximum item intercept parameter change: 0.776254
## Maximum item slope parameter change: 0.131026
## Maximum item guessing parameter change: 0.005899
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.02818
## ....................................................
## Iteration 62 2021-07-06 17:55:59
## E Step
## M Step Intercepts |-----
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1085129.9238 | Absolute change: 101.831 | Relative change: 9.384e-05
## Maximum item intercept parameter change: 1.165492
## Maximum item slope parameter change: 0.129494
## Maximum item guessing parameter change: 0.007749
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.031289
## ....................................................
## Iteration 63 2021-07-06 17:56:00
## E Step
## M Step Intercepts |-----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1085028.2188 | Absolute change: 101.705 | Relative change: 9.373e-05
## Maximum item intercept parameter change: 0.628298
## Maximum item slope parameter change: 0.142157
## Maximum item guessing parameter change: 0.003485
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.033769
## ....................................................
## Iteration 64 2021-07-06 17:56:00
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1084938.6378 | Absolute change: 89.5809 | Relative change: 8.257e-05
## Maximum item intercept parameter change: 0.360603
## Maximum item slope parameter change: 0.156745
## Maximum item guessing parameter change: 0.002449
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.035352
## ....................................................
## Iteration 65 2021-07-06 17:56:00
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1084886.6802 | Absolute change: 51.9577 | Relative change: 4.789e-05
## Maximum item intercept parameter change: 0.363456
## Maximum item slope parameter change: 0.17288
## Maximum item guessing parameter change: 0.002856
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.035285
## ....................................................
## Iteration 66 2021-07-06 17:56:01
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1084863.9463 | Absolute change: 22.7339 | Relative change: 2.096e-05
## Maximum item intercept parameter change: 0.392996
## Maximum item slope parameter change: 0.189478
## Maximum item guessing parameter change: 0.004095
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.034404
## ....................................................
## Iteration 67 2021-07-06 17:56:01
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1084863.1748 | Absolute change: 0.7715 | Relative change: 7.1e-07
## Maximum item intercept parameter change: 0.423185
## Maximum item slope parameter change: 0.206826
## Maximum item guessing parameter change: 0.005143
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.03339
## ....................................................
## Iteration 68 2021-07-06 17:56:01
## E Step
## M Step Intercepts |-----
## M Step Slopes |-----
## M Step Guessing |--
## Deviance = 1084878.7022 | Absolute change: -15.5274 | Relative change: 1.431e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.45509
## Maximum item slope parameter change: 0.22537
## Maximum item guessing parameter change: 0.004802
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.032523
## ....................................................
## Iteration 69 2021-07-06 17:56:02
## E Step
## M Step Intercepts |-----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1084910.5221 | Absolute change: -31.8199 | Relative change: 2.933e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.488418
## Maximum item slope parameter change: 0.181275
## Maximum item guessing parameter change: 0.002944
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.031572
## ....................................................
## Iteration 70 2021-07-06 17:56:02
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1084965.4713 | Absolute change: -54.9492 | Relative change: 5.065e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.743451
## Maximum item slope parameter change: 0.099028
## Maximum item guessing parameter change: 0.003
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.030251
## ....................................................
## Iteration 71 2021-07-06 17:56:02
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1085067.09 | Absolute change: -101.6188 | Relative change: 9.365e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.735176
## Maximum item slope parameter change: 0.10444
## Maximum item guessing parameter change: 0.001605
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.028712
## ....................................................
## Iteration 72 2021-07-06 17:56:03
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1085168.196 | Absolute change: -101.106 | Relative change: 9.317e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.899708
## Maximum item slope parameter change: 0.10928
## Maximum item guessing parameter change: 0.001772
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.026596
## ....................................................
## Iteration 73 2021-07-06 17:56:03
## E Step
## M Step Intercepts |-----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1085274.162 | Absolute change: -105.966 | Relative change: 9.764e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.696446
## Maximum item slope parameter change: 0.113524
## Maximum item guessing parameter change: 0.002064
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.024425
## ....................................................
## Iteration 74 2021-07-06 17:56:03
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1085413.753 | Absolute change: -139.591 | Relative change: 0.00012861
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 1.059476
## Maximum item slope parameter change: 0.117325
## Maximum item guessing parameter change: 0.004786
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.022232
## ....................................................
## Iteration 75 2021-07-06 17:56:04
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1085612.7687 | Absolute change: -199.0157 | Relative change: 0.00018332
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.872012
## Maximum item slope parameter change: 0.312836
## Maximum item guessing parameter change: 0.004675
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.020828
## ....................................................
## Iteration 76 2021-07-06 17:56:04
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1085730.6163 | Absolute change: -117.8477 | Relative change: 0.00010854
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.873188
## Maximum item slope parameter change: 0.12554
## Maximum item guessing parameter change: 0.002355
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.020636
## ....................................................
## Iteration 77 2021-07-06 17:56:05
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1085837.3943 | Absolute change: -106.778 | Relative change: 9.834e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.664114
## Maximum item slope parameter change: 0.130434
## Maximum item guessing parameter change: 0.002193
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.020564
## ....................................................
## Iteration 78 2021-07-06 17:56:05
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1085949.7855 | Absolute change: -112.3912 | Relative change: 0.0001035
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.76206
## Maximum item slope parameter change: 0.136242
## Maximum item guessing parameter change: 0.002076
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.020352
## ....................................................
## Iteration 79 2021-07-06 17:56:05
## E Step
## M Step Intercepts |-----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1086086.5834 | Absolute change: -136.7978 | Relative change: 0.00012595
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.469474
## Maximum item slope parameter change: 0.142994
## Maximum item guessing parameter change: 0.003817
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.019743
## ....................................................
## Iteration 80 2021-07-06 17:56:06
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1086255.9897 | Absolute change: -169.4063 | Relative change: 0.00015595
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 1.37307
## Maximum item slope parameter change: 0.151326
## Maximum item guessing parameter change: 0.008307
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.019035
## ....................................................
## Iteration 81 2021-07-06 17:56:06
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1086449.5062 | Absolute change: -193.5165 | Relative change: 0.00017812
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.737595
## Maximum item slope parameter change: 0.166259
## Maximum item guessing parameter change: 0.001786
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.019271
## ....................................................
## Iteration 82 2021-07-06 17:56:07
## E Step
## M Step Intercepts |-----
## M Step Slopes |-----
## M Step Guessing |--
## Deviance = 1086591.1443 | Absolute change: -141.6381 | Relative change: 0.00013035
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.688511
## Maximum item slope parameter change: 0.186633
## Maximum item guessing parameter change: 0.002738
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.018574
## ....................................................
## Iteration 83 2021-07-06 17:56:07
## E Step
## M Step Intercepts |----------
## M Step Slopes |-----
## M Step Guessing |---
## Deviance = 1086756.3813 | Absolute change: -165.237 | Relative change: 0.00015205
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.745809
## Maximum item slope parameter change: 0.221118
## Maximum item guessing parameter change: 0.008854
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.017374
## ....................................................
## Iteration 84 2021-07-06 17:56:08
## E Step
## M Step Intercepts |----------
## M Step Slopes |-------
## M Step Guessing |---
## Deviance = 1087033.7785 | Absolute change: -277.3972 | Relative change: 0.00025519
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 1.14237
## Maximum item slope parameter change: 0.465357
## Maximum item guessing parameter change: 0.007019
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.016265
## ....................................................
## Iteration 85 2021-07-06 17:56:08
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1087255.3643 | Absolute change: -221.5858 | Relative change: 0.0002038
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 1.26448
## Maximum item slope parameter change: 0.172352
## Maximum item guessing parameter change: 0.013628
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.015604
## ....................................................
## Iteration 86 2021-07-06 17:56:09
## E Step
## M Step Intercepts |----------
## M Step Slopes |---
## M Step Guessing |---
## Deviance = 1087230.4413 | Absolute change: 24.9231 | Relative change: 2.292e-05
## Maximum item intercept parameter change: 0.63832
## Maximum item slope parameter change: 0.144772
## Maximum item guessing parameter change: 0.004363
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.020152
## ....................................................
## Iteration 87 2021-07-06 17:56:09
## E Step
## M Step Intercepts |----------
## M Step Slopes |---
## M Step Guessing |---
## Deviance = 1087357.3055 | Absolute change: -126.8643 | Relative change: 0.00011667
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.934584
## Maximum item slope parameter change: 0.126907
## Maximum item guessing parameter change: 0.010191
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.022928
## ....................................................
## Iteration 88 2021-07-06 17:56:09
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1087679.2046 | Absolute change: -321.8991 | Relative change: 0.00029595
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.844072
## Maximum item slope parameter change: 0.114588
## Maximum item guessing parameter change: 0.005427
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.024218
## ....................................................
## Iteration 89 2021-07-06 17:56:10
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1087885.2131 | Absolute change: -206.0085 | Relative change: 0.00018937
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.961065
## Maximum item slope parameter change: 0.123846
## Maximum item guessing parameter change: 0.012473
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.025345
## ....................................................
## Iteration 90 2021-07-06 17:56:10
## E Step
## M Step Intercepts |----------
## M Step Slopes |------
## M Step Guessing |---
## Deviance = 1088072.5385 | Absolute change: -187.3254 | Relative change: 0.00017216
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.881212
## Maximum item slope parameter change: 0.223122
## Maximum item guessing parameter change: 0.00842
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.028187
## ....................................................
## Iteration 91 2021-07-06 17:56:11
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1087997.6402 | Absolute change: 74.8983 | Relative change: 6.884e-05
## Maximum item intercept parameter change: 1.182006
## Maximum item slope parameter change: 0.188029
## Maximum item guessing parameter change: 0.002167
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.033279
## ....................................................
## Iteration 92 2021-07-06 17:56:11
## E Step
## M Step Intercepts |----------
## M Step Slopes |---
## M Step Guessing |---
## Deviance = 1087925.1628 | Absolute change: 72.4774 | Relative change: 6.662e-05
## Maximum item intercept parameter change: 1.395175
## Maximum item slope parameter change: 0.437021
## Maximum item guessing parameter change: 0.006099
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.035934
## ....................................................
## Iteration 93 2021-07-06 17:56:11
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1087942.6312 | Absolute change: -17.4685 | Relative change: 1.606e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 1.644192
## Maximum item slope parameter change: 0.145927
## Maximum item guessing parameter change: 0.013616
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.036528
## ....................................................
## Iteration 94 2021-07-06 17:56:12
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1087703.4224 | Absolute change: 239.2089 | Relative change: 0.00021992
## Maximum item intercept parameter change: 0.752916
## Maximum item slope parameter change: 0.081743
## Maximum item guessing parameter change: 0.00313
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.043641
## ....................................................
## Iteration 95 2021-07-06 17:56:12
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1087514.2218 | Absolute change: 189.2006 | Relative change: 0.00017398
## Maximum item intercept parameter change: 0.430761
## Maximum item slope parameter change: 0.061791
## Maximum item guessing parameter change: 0.002832
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.048985
## ....................................................
## Iteration 96 2021-07-06 17:56:13
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1087460.4439 | Absolute change: 53.7779 | Relative change: 4.945e-05
## Maximum item intercept parameter change: 0.488823
## Maximum item slope parameter change: 0.067257
## Maximum item guessing parameter change: 0.004437
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.050674
## ....................................................
## Iteration 97 2021-07-06 17:56:13
## E Step
## M Step Intercepts |-----
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1087431.7521 | Absolute change: 28.6918 | Relative change: 2.638e-05
## Maximum item intercept parameter change: 0.745609
## Maximum item slope parameter change: 0.075134
## Maximum item guessing parameter change: 0.008675
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.050968
## ....................................................
## Iteration 98 2021-07-06 17:56:13
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1087367.387 | Absolute change: 64.3651 | Relative change: 5.919e-05
## Maximum item intercept parameter change: 0.818285
## Maximum item slope parameter change: 0.084027
## Maximum item guessing parameter change: 0.00773
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.052928
## ....................................................
## Iteration 99 2021-07-06 17:56:13
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1087284.1523 | Absolute change: 83.2347 | Relative change: 7.655e-05
## Maximum item intercept parameter change: 0.815866
## Maximum item slope parameter change: 0.094443
## Maximum item guessing parameter change: 0.003278
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.055988
## ....................................................
## Iteration 100 2021-07-06 17:56:14
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1087271.2175 | Absolute change: 12.9348 | Relative change: 1.19e-05
## Maximum item intercept parameter change: 0.889657
## Maximum item slope parameter change: 0.103837
## Maximum item guessing parameter change: 0.002401
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.056013
## ....................................................
## Iteration 101 2021-07-06 17:56:14
## E Step
## M Step Intercepts |-----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1087315.8879 | Absolute change: -44.6704 | Relative change: 4.108e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.741194
## Maximum item slope parameter change: 0.107774
## Maximum item guessing parameter change: 0.001731
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.052411
## ....................................................
## Iteration 102 2021-07-06 17:56:15
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1087407.9613 | Absolute change: -92.0734 | Relative change: 8.467e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.475331
## Maximum item slope parameter change: 0.106887
## Maximum item guessing parameter change: 0.002371
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.047295
## ....................................................
## Iteration 103 2021-07-06 17:56:15
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1087543.22 | Absolute change: -135.2588 | Relative change: 0.00012437
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.808815
## Maximum item slope parameter change: 0.106886
## Maximum item guessing parameter change: 0.004752
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.041226
## ....................................................
## Iteration 104 2021-07-06 17:56:16
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1087718.4244 | Absolute change: -175.2044 | Relative change: 0.00016108
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.961387
## Maximum item slope parameter change: 0.231864
## Maximum item guessing parameter change: 0.003577
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.035839
## ....................................................
## Iteration 105 2021-07-06 17:56:16
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1087798.2414 | Absolute change: -79.817 | Relative change: 7.337e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.916475
## Maximum item slope parameter change: 0.117972
## Maximum item guessing parameter change: 0.001681
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.032794
## ....................................................
## Iteration 106 2021-07-06 17:56:16
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1087880.5761 | Absolute change: -82.3347 | Relative change: 7.568e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.599701
## Maximum item slope parameter change: 0.135423
## Maximum item guessing parameter change: 0.00181
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.030148
## ....................................................
## Iteration 107 2021-07-06 17:56:17
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1087970.2586 | Absolute change: -89.6825 | Relative change: 8.243e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 2.200744
## Maximum item slope parameter change: 0.193142
## Maximum item guessing parameter change: 0.002072
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.027733
## ....................................................
## Iteration 108 2021-07-06 17:56:17
## E Step
## M Step Intercepts |----------
## M Step Slopes |-----
## M Step Guessing |--
## Deviance = 1088066.1784 | Absolute change: -95.9198 | Relative change: 8.816e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.481206
## Maximum item slope parameter change: 0.134552
## Maximum item guessing parameter change: 0.002279
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.025767
## ....................................................
## Iteration 109 2021-07-06 17:56:18
## E Step
## M Step Intercepts |----------
## M Step Slopes |-------
## M Step Guessing |--
## Deviance = 1088175.1327 | Absolute change: -108.9543 | Relative change: 0.00010013
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.75848
## Maximum item slope parameter change: 0.401549
## Maximum item guessing parameter change: 0.00287
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.02393
## ....................................................
## Iteration 110 2021-07-06 17:56:18
## E Step
## M Step Intercepts |----------
## M Step Slopes |---------
## M Step Guessing |---
## Deviance = 1088293.6494 | Absolute change: -118.5167 | Relative change: 0.0001089
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.943222
## Maximum item slope parameter change: 1.071875
## Maximum item guessing parameter change: 0.006525
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.022324
## ....................................................
## Iteration 111 2021-07-06 17:56:18
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1088449.1067 | Absolute change: -155.4573 | Relative change: 0.00014282
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.935492
## Maximum item slope parameter change: 2.20346
## Maximum item guessing parameter change: 0.00323
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.021367
## ....................................................
## Iteration 112 2021-07-06 17:56:19
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1088548.3293 | Absolute change: -99.2226 | Relative change: 9.115e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.713368
## Maximum item slope parameter change: 1.733138
## Maximum item guessing parameter change: 0.001005
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.020186
## ....................................................
## Iteration 113 2021-07-06 17:56:19
## E Step
## M Step Intercepts |-----
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1088635.7278 | Absolute change: -87.3985 | Relative change: 8.028e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.542715
## Maximum item slope parameter change: 0.955249
## Maximum item guessing parameter change: 0.004779
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.018379
## ....................................................
## Iteration 114 2021-07-06 17:56:20
## E Step
## M Step Intercepts |----
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1088737.2601 | Absolute change: -101.5324 | Relative change: 9.326e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.277238
## Maximum item slope parameter change: 0.038647
## Maximum item guessing parameter change: 0.003265
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.017183
## ....................................................
## Iteration 115 2021-07-06 17:56:20
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |---
## Deviance = 1088868.5559 | Absolute change: -131.2957 | Relative change: 0.00012058
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.506127
## Maximum item slope parameter change: 0.038847
## Maximum item guessing parameter change: 0.00593
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.015207
## ....................................................
## Iteration 116 2021-07-06 17:56:20
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |---
## Deviance = 1089068.2627 | Absolute change: -199.7068 | Relative change: 0.00018337
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.963289
## Maximum item slope parameter change: 0.511274
## Maximum item guessing parameter change: 0.010519
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.013899
## ....................................................
## Iteration 117 2021-07-06 17:56:21
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089022.755 | Absolute change: 45.5076 | Relative change: 4.179e-05
## Maximum item intercept parameter change: 0.936008
## Maximum item slope parameter change: 0.399165
## Maximum item guessing parameter change: 0.00419
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.019713
## ....................................................
## Iteration 118 2021-07-06 17:56:21
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |---
## Deviance = 1089032.0524 | Absolute change: -9.2974 | Relative change: 8.54e-06
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.572521
## Maximum item slope parameter change: 0.157362
## Maximum item guessing parameter change: 0.00653
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.025455
## ....................................................
## Iteration 119 2021-07-06 17:56:22
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |---
## Deviance = 1089241.305 | Absolute change: -209.2526 | Relative change: 0.00019211
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 1.522793
## Maximum item slope parameter change: 0.111573
## Maximum item guessing parameter change: 0.013432
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.027745
## ....................................................
## Iteration 120 2021-07-06 17:56:22
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |---
## Deviance = 1089529.7944 | Absolute change: -288.4894 | Relative change: 0.00026478
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 1.032905
## Maximum item slope parameter change: 0.1347
## Maximum item guessing parameter change: 0.013056
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.029415
## ....................................................
## Iteration 121 2021-07-06 17:56:23
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |---
## Deviance = 1089747.5881 | Absolute change: -217.7937 | Relative change: 0.00019986
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.916587
## Maximum item slope parameter change: 0.041389
## Maximum item guessing parameter change: 0.007207
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.032281
## ....................................................
## Iteration 122 2021-07-06 17:56:23
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089775.1739 | Absolute change: -27.5858 | Relative change: 2.531e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.864262
## Maximum item slope parameter change: 0.142407
## Maximum item guessing parameter change: 0.00381
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.036283
## ....................................................
## Iteration 123 2021-07-06 17:56:23
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |---
## Deviance = 1089642.7044 | Absolute change: 132.4695 | Relative change: 0.00012157
## Maximum item intercept parameter change: 0.808396
## Maximum item slope parameter change: 0.09862
## Maximum item guessing parameter change: 0.006231
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.042041
## ....................................................
## Iteration 124 2021-07-06 17:56:24
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |---
## Deviance = 1089584.1124 | Absolute change: 58.592 | Relative change: 5.377e-05
## Maximum item intercept parameter change: 0.896333
## Maximum item slope parameter change: 0.288403
## Maximum item guessing parameter change: 0.007071
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.046103
## ....................................................
## Iteration 125 2021-07-06 17:56:24
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089324.9944 | Absolute change: 259.118 | Relative change: 0.00023787
## Maximum item intercept parameter change: 0.493573
## Maximum item slope parameter change: 0.085356
## Maximum item guessing parameter change: 0.002831
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.055061
## ....................................................
## Iteration 126 2021-07-06 17:56:25
## E Step
## M Step Intercepts |----
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089200.6558 | Absolute change: 124.3386 | Relative change: 0.00011416
## Maximum item intercept parameter change: 0.478469
## Maximum item slope parameter change: 0.06294
## Maximum item guessing parameter change: 0.002679
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.060163
## ....................................................
## Iteration 127 2021-07-06 17:56:25
## E Step
## M Step Intercepts |-----
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089163.2892 | Absolute change: 37.3665 | Relative change: 3.431e-05
## Maximum item intercept parameter change: 0.781778
## Maximum item slope parameter change: 0.069042
## Maximum item guessing parameter change: 0.006017
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.060771
## ....................................................
## Iteration 128 2021-07-06 17:56:25
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |---
## Deviance = 1089106.5091 | Absolute change: 56.7801 | Relative change: 5.213e-05
## Maximum item intercept parameter change: 0.985259
## Maximum item slope parameter change: 0.279459
## Maximum item guessing parameter change: 0.010557
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.06196
## ....................................................
## Iteration 129 2021-07-06 17:56:26
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1088781.1558 | Absolute change: 325.3534 | Relative change: 0.00029882
## Maximum item intercept parameter change: 0.783161
## Maximum item slope parameter change: 0.090438
## Maximum item guessing parameter change: 0.004512
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.072041
## ....................................................
## Iteration 130 2021-07-06 17:56:26
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1088608.8302 | Absolute change: 172.3256 | Relative change: 0.0001583
## Maximum item intercept parameter change: 0.639998
## Maximum item slope parameter change: 0.07446
## Maximum item guessing parameter change: 0.003276
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.079156
## ....................................................
## Iteration 131 2021-07-06 17:56:27
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1088602.7043 | Absolute change: 6.1259 | Relative change: 5.63e-06
## Maximum item intercept parameter change: 0.537662
## Maximum item slope parameter change: 0.075674
## Maximum item guessing parameter change: 0.002101
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.077167
## ....................................................
## Iteration 132 2021-07-06 17:56:27
## E Step
## M Step Intercepts |-----
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1088661.797 | Absolute change: -59.0928 | Relative change: 5.428e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.673636
## Maximum item slope parameter change: 0.205523
## Maximum item guessing parameter change: 0.002065
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.06924
## ....................................................
## Iteration 133 2021-07-06 17:56:28
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1088759.8185 | Absolute change: -98.0215 | Relative change: 9.003e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 1.372207
## Maximum item slope parameter change: 0.07013
## Maximum item guessing parameter change: 0.004626
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.058772
## ....................................................
## Iteration 134 2021-07-06 17:56:28
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1088907.0956 | Absolute change: -147.277 | Relative change: 0.00013525
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.807051
## Maximum item slope parameter change: 0.154914
## Maximum item guessing parameter change: 0.003354
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.049264
## ....................................................
## Iteration 135 2021-07-06 17:56:28
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1088988.4123 | Absolute change: -81.3167 | Relative change: 7.467e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.901577
## Maximum item slope parameter change: 0.286042
## Maximum item guessing parameter change: 0.002148
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.041842
## ....................................................
## Iteration 136 2021-07-06 17:56:29
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089062.1362 | Absolute change: -73.724 | Relative change: 6.769e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.946193
## Maximum item slope parameter change: 0.073338
## Maximum item guessing parameter change: 0.00115
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.036304
## ....................................................
## Iteration 137 2021-07-06 17:56:29
## E Step
## M Step Intercepts |-----
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089123.7713 | Absolute change: -61.6351 | Relative change: 5.659e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.785103
## Maximum item slope parameter change: 0.055103
## Maximum item guessing parameter change: 0.000924
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.032784
## ....................................................
## Iteration 138 2021-07-06 17:56:30
## E Step
## M Step Intercepts |-----
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089202.4141 | Absolute change: -78.6428 | Relative change: 7.22e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.398972
## Maximum item slope parameter change: 0.051816
## Maximum item guessing parameter change: 0.001135
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.029299
## ....................................................
## Iteration 139 2021-07-06 17:56:30
## E Step
## M Step Intercepts |----
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089284.03 | Absolute change: -81.6159 | Relative change: 7.493e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.330361
## Maximum item slope parameter change: 0.047686
## Maximum item guessing parameter change: 0.0012
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.025595
## ....................................................
## Iteration 140 2021-07-06 17:56:30
## E Step
## M Step Intercepts |----
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089353.4409 | Absolute change: -69.4109 | Relative change: 6.372e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.262611
## Maximum item slope parameter change: 0.043289
## Maximum item guessing parameter change: 0.0014
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.022268
## ....................................................
## Iteration 141 2021-07-06 17:56:30
## E Step
## M Step Intercepts |-----
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089417.3105 | Absolute change: -63.8696 | Relative change: 5.863e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.285672
## Maximum item slope parameter change: 0.039019
## Maximum item guessing parameter change: 0.002392
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.019596
## ....................................................
## Iteration 142 2021-07-06 17:56:31
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |---
## Deviance = 1089492.2389 | Absolute change: -74.9283 | Relative change: 6.877e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.932377
## Maximum item slope parameter change: 0.035102
## Maximum item guessing parameter change: 0.006032
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.01777
## ....................................................
## Iteration 143 2021-07-06 17:56:31
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089609.4155 | Absolute change: -117.1767 | Relative change: 0.00010754
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.938867
## Maximum item slope parameter change: 0.031863
## Maximum item guessing parameter change: 0.003035
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.017339
## ....................................................
## Iteration 144 2021-07-06 17:56:31
## E Step
## M Step Intercepts |----------
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089677.3696 | Absolute change: -67.954 | Relative change: 6.236e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.542588
## Maximum item slope parameter change: 0.029856
## Maximum item guessing parameter change: 0.001535
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.017516
## ....................................................
## Iteration 145 2021-07-06 17:56:32
## E Step
## M Step Intercepts |----
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089738.5622 | Absolute change: -61.1926 | Relative change: 5.615e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.537991
## Maximum item slope parameter change: 0.027815
## Maximum item guessing parameter change: 0.001202
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.017334
## ....................................................
## Iteration 146 2021-07-06 17:56:32
## E Step
## M Step Intercepts |----
## M Step Slopes |----------
## M Step Guessing |--
## Deviance = 1089804.8202 | Absolute change: -66.258 | Relative change: 6.08e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.216976
## Maximum item slope parameter change: 0.026371
## Maximum item guessing parameter change: 0.001569
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.016741
## ....................................................
## Iteration 147 2021-07-06 17:56:32
## E Step
## M Step Intercepts |----------
## M Step Slopes |-------
## M Step Guessing |--
## Deviance = 1089878.553 | Absolute change: -73.7329 | Relative change: 6.765e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.504635
## Maximum item slope parameter change: 0.026574
## Maximum item guessing parameter change: 0.004156
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.015417
## ....................................................
## Iteration 148 2021-07-06 17:56:33
## E Step
## M Step Intercepts |----------
## M Step Slopes |---------
## M Step Guessing |---
## Deviance = 1089966.9917 | Absolute change: -88.4387 | Relative change: 8.114e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.893045
## Maximum item slope parameter change: 0.400133
## Maximum item guessing parameter change: 0.0084
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.014162
## ....................................................
## Iteration 149 2021-07-06 17:56:33
## E Step
## M Step Intercepts |----------
## M Step Slopes |--------
## M Step Guessing |---
## Deviance = 1089973.3523 | Absolute change: -6.3606 | Relative change: 5.84e-06
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.957554
## Maximum item slope parameter change: 0.102468
## Maximum item guessing parameter change: 0.00575
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.019215
## ....................................................
## Iteration 150 2021-07-06 17:56:34
## E Step
## M Step Intercepts |----------
## M Step Slopes |------
## M Step Guessing |--
## Deviance = 1090056.434 | Absolute change: -83.0817 | Relative change: 7.622e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.844909
## Maximum item slope parameter change: 0.13154
## Maximum item guessing parameter change: 0.003359
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.023005
## ....................................................
## Iteration 151 2021-07-06 17:56:34
## E Step
## M Step Intercepts |-----
## M Step Slopes |-----
## M Step Guessing |---
## Deviance = 1090092.0362 | Absolute change: -35.6022 | Relative change: 3.266e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.867747
## Maximum item slope parameter change: 0.095245
## Maximum item guessing parameter change: 0.0055
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.026732
## ....................................................
## Iteration 152 2021-07-06 17:56:34
## E Step
## M Step Intercepts |----------
## M Step Slopes |---
## M Step Guessing |---
## Deviance = 1090273.8009 | Absolute change: -181.7647 | Relative change: 0.00016671
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 1.542134
## Maximum item slope parameter change: 0.036295
## Maximum item guessing parameter change: 0.013005
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.026865
## ....................................................
## Iteration 153 2021-07-06 17:56:35
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1090528.493 | Absolute change: -254.6921 | Relative change: 0.00023355
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.616541
## Maximum item slope parameter change: 0.032865
## Maximum item guessing parameter change: 0.006238
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.027027
## ....................................................
## Iteration 154 2021-07-06 17:56:35
## E Step
## M Step Intercepts |----------
## M Step Slopes |---
## M Step Guessing |---
## Deviance = 1090657.5006 | Absolute change: -129.0076 | Relative change: 0.00011828
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 1.831559
## Maximum item slope parameter change: 0.034241
## Maximum item guessing parameter change: 0.015594
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.027509
## ....................................................
## Iteration 155 2021-07-06 17:56:36
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1090719.5807 | Absolute change: -62.0801 | Relative change: 5.692e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.887415
## Maximum item slope parameter change: 0.055735
## Maximum item guessing parameter change: 0.002389
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.031294
## ....................................................
## Iteration 156 2021-07-06 17:56:36
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1090585.879 | Absolute change: 133.7016 | Relative change: 0.0001226
## Maximum item intercept parameter change: 0.927652
## Maximum item slope parameter change: 0.055735
## Maximum item guessing parameter change: 0.006913
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.038971
## ....................................................
## Iteration 157 2021-07-06 17:56:36
## E Step
## M Step Intercepts |----------
## M Step Slopes |-----
## M Step Guessing |---
## Deviance = 1090530.6641 | Absolute change: 55.215 | Relative change: 5.063e-05
## Maximum item intercept parameter change: 0.907263
## Maximum item slope parameter change: 0.245689
## Maximum item guessing parameter change: 0.006613
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.045301
## ....................................................
## Iteration 158 2021-07-06 17:56:37
## E Step
## M Step Intercepts |----------
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1090286.4217 | Absolute change: 244.2423 | Relative change: 0.00022402
## Maximum item intercept parameter change: 0.510846
## Maximum item slope parameter change: 0.073773
## Maximum item guessing parameter change: 0.002667
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.056821
## ....................................................
## Iteration 159 2021-07-06 17:56:37
## E Step
## M Step Intercepts |----
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1090150.8838 | Absolute change: 135.5379 | Relative change: 0.00012433
## Maximum item intercept parameter change: 0.47429
## Maximum item slope parameter change: 0.045562
## Maximum item guessing parameter change: 0.002263
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.063333
## ....................................................
## Iteration 160 2021-07-06 17:56:38
## E Step
## M Step Intercepts |----------
## M Step Slopes |---
## M Step Guessing |---
## Deviance = 1090095.7307 | Absolute change: 55.1531 | Relative change: 5.059e-05
## Maximum item intercept parameter change: 1.166842
## Maximum item slope parameter change: 0.048143
## Maximum item guessing parameter change: 0.009783
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.064322
## ....................................................
## Iteration 161 2021-07-06 17:56:38
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1089899.1254 | Absolute change: 196.6054 | Relative change: 0.00018039
## Maximum item intercept parameter change: 0.799458
## Maximum item slope parameter change: 0.146843
## Maximum item guessing parameter change: 0.005638
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.070874
## ....................................................
## Iteration 162 2021-07-06 17:56:38
## E Step
## M Step Intercepts |------
## M Step Slopes |----
## M Step Guessing |---
## Deviance = 1089439.6903 | Absolute change: 459.435 | Relative change: 0.00042172
## Maximum item intercept parameter change: 1.657044
## Maximum item slope parameter change: 0.042141
## Maximum item guessing parameter change: 0.004714
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.088852
## ....................................................
## Iteration 163 2021-07-06 17:56:39
## E Step
## M Step Intercepts |----------
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089326.2619 | Absolute change: 113.4284 | Relative change: 0.00010413
## Maximum item intercept parameter change: 0.545822
## Maximum item slope parameter change: 0.03366
## Maximum item guessing parameter change: 0.002771
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.095039
## ....................................................
## Iteration 164 2021-07-06 17:56:39
## E Step
## M Step Intercepts |----
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089335.5922 | Absolute change: -9.3302 | Relative change: 8.57e-06
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.760701
## Maximum item slope parameter change: 0.034689
## Maximum item guessing parameter change: 0.001766
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.088461
## ....................................................
## Iteration 165 2021-07-06 17:56:39
## E Step
## M Step Intercepts |-----
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089375.2258 | Absolute change: -39.6336 | Relative change: 3.638e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.274541
## Maximum item slope parameter change: 0.034422
## Maximum item guessing parameter change: 0.001471
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.075561
## ....................................................
## Iteration 166 2021-07-06 17:56:40
## E Step
## M Step Intercepts |----------
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089431.9878 | Absolute change: -56.7621 | Relative change: 5.21e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.457795
## Maximum item slope parameter change: 0.035289
## Maximum item guessing parameter change: 0.002179
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.061137
## ....................................................
## Iteration 167 2021-07-06 17:56:40
## E Step
## M Step Intercepts |----------
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089504.3482 | Absolute change: -72.3603 | Relative change: 6.642e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.854929
## Maximum item slope parameter change: 0.03594
## Maximum item guessing parameter change: 0.00332
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.048002
## ....................................................
## Iteration 168 2021-07-06 17:56:40
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1089604.0373 | Absolute change: -99.6891 | Relative change: 9.149e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.915269
## Maximum item slope parameter change: 0.148912
## Maximum item guessing parameter change: 0.003862
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.037496
## ....................................................
## Iteration 169 2021-07-06 17:56:41
## E Step
## M Step Intercepts |----------
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1089654.4496 | Absolute change: -50.4123 | Relative change: 4.626e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.943907
## Maximum item slope parameter change: 0.060528
## Maximum item guessing parameter change: 0.001565
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.031126
## ....................................................
## Iteration 170 2021-07-06 17:56:41
## E Step
## M Step Intercepts |----------
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089692.2436 | Absolute change: -37.794 | Relative change: 3.468e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.644684
## Maximum item slope parameter change: 0.059807
## Maximum item guessing parameter change: 0.000622
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.027205
## ....................................................
## Iteration 171 2021-07-06 17:56:42
## E Step
## M Step Intercepts |-----
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089732.1862 | Absolute change: -39.9426 | Relative change: 3.665e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.781407
## Maximum item slope parameter change: 0.028577
## Maximum item guessing parameter change: 0.000677
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.024267
## ....................................................
## Iteration 172 2021-07-06 17:56:42
## E Step
## M Step Intercepts |-----
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089771.8098 | Absolute change: -39.6236 | Relative change: 3.636e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.822772
## Maximum item slope parameter change: 0.015196
## Maximum item guessing parameter change: 0.000532
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.021211
## ....................................................
## Iteration 173 2021-07-06 17:56:42
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1089811.0462 | Absolute change: -39.2364 | Relative change: 3.6e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.729218
## Maximum item slope parameter change: 0.037242
## Maximum item guessing parameter change: 0.000436
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.017726
## ....................................................
## Iteration 174 2021-07-06 17:56:43
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1089835.5771 | Absolute change: -24.5309 | Relative change: 2.251e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.596763
## Maximum item slope parameter change: 0.038926
## Maximum item guessing parameter change: 0.000442
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.014369
## ....................................................
## Iteration 175 2021-07-06 17:56:43
## E Step
## M Step Intercepts |----
## M Step Slopes |----
## M Step Guessing |--
## Deviance = 1089849.1599 | Absolute change: -13.5828 | Relative change: 1.246e-05
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.48598
## Maximum item slope parameter change: 0.028839
## Maximum item guessing parameter change: 0.000446
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.011439
## ....................................................
## Iteration 176 2021-07-06 17:56:43
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089855.3399 | Absolute change: -6.18 | Relative change: 5.67e-06
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.385154
## Maximum item slope parameter change: 0.020258
## Maximum item guessing parameter change: 0.000451
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.009013
## ....................................................
## Iteration 177 2021-07-06 17:56:43
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089856.2981 | Absolute change: -0.9582 | Relative change: 8.8e-07
## !!! Deviance increases! !!!!
## !!! Choose maybe fac.oldxsi > 0 and/or increment.factor > 1 !!!!
## Maximum item intercept parameter change: 0.296054
## Maximum item slope parameter change: 0.014978
## Maximum item guessing parameter change: 0.000452
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.007058
## ....................................................
## Iteration 178 2021-07-06 17:56:43
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089853.3985 | Absolute change: 2.8996 | Relative change: 2.66e-06
## Maximum item intercept parameter change: 0.22093
## Maximum item slope parameter change: 0.014822
## Maximum item guessing parameter change: 0.000447
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.005506
## ....................................................
## Iteration 179 2021-07-06 17:56:44
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089847.5493 | Absolute change: 5.8492 | Relative change: 5.37e-06
## Maximum item intercept parameter change: 0.160174
## Maximum item slope parameter change: 0.014648
## Maximum item guessing parameter change: 0.000439
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.004279
## ....................................................
## Iteration 180 2021-07-06 17:56:44
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089839.3975 | Absolute change: 8.1518 | Relative change: 7.48e-06
## Maximum item intercept parameter change: 0.112808
## Maximum item slope parameter change: 0.014462
## Maximum item guessing parameter change: 0.000437
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.003312
## ....................................................
## Iteration 181 2021-07-06 17:56:44
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089829.4313 | Absolute change: 9.9663 | Relative change: 9.14e-06
## Maximum item intercept parameter change: 0.076897
## Maximum item slope parameter change: 0.014268
## Maximum item guessing parameter change: 0.000433
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.002549
## ....................................................
## Iteration 182 2021-07-06 17:56:44
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089818.0334 | Absolute change: 11.3978 | Relative change: 1.046e-05
## Maximum item intercept parameter change: 0.05186
## Maximum item slope parameter change: 0.014067
## Maximum item guessing parameter change: 0.000427
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001943
## ....................................................
## Iteration 183 2021-07-06 17:56:45
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089805.5108 | Absolute change: 12.5226 | Relative change: 1.149e-05
## Maximum item intercept parameter change: 0.050906
## Maximum item slope parameter change: 0.013864
## Maximum item guessing parameter change: 0.000421
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001461
## ....................................................
## Iteration 184 2021-07-06 17:56:45
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089792.1112 | Absolute change: 13.3996 | Relative change: 1.23e-05
## Maximum item intercept parameter change: 0.04998
## Maximum item slope parameter change: 0.013658
## Maximum item guessing parameter change: 0.000413
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001073
## ....................................................
## Iteration 185 2021-07-06 17:56:45
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089778.0345 | Absolute change: 14.0767 | Relative change: 1.292e-05
## Maximum item intercept parameter change: 0.049079
## Maximum item slope parameter change: 0.013651
## Maximum item guessing parameter change: 0.000405
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000759
## ....................................................
## Iteration 186 2021-07-06 17:56:46
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089763.4406 | Absolute change: 14.5939 | Relative change: 1.339e-05
## Maximum item intercept parameter change: 0.0482
## Maximum item slope parameter change: 0.014939
## Maximum item guessing parameter change: 0.000397
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000502
## ....................................................
## Iteration 187 2021-07-06 17:56:46
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089748.4563 | Absolute change: 14.9843 | Relative change: 1.375e-05
## Maximum item intercept parameter change: 0.047342
## Maximum item slope parameter change: 0.016178
## Maximum item guessing parameter change: 0.000388
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000287
## ....................................................
## Iteration 188 2021-07-06 17:56:46
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089733.1803 | Absolute change: 15.276 | Relative change: 1.402e-05
## Maximum item intercept parameter change: 0.046502
## Maximum item slope parameter change: 0.017362
## Maximum item guessing parameter change: 0.00038
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000106
## ....................................................
## Iteration 189 2021-07-06 17:56:46
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089717.6881 | Absolute change: 15.4922 | Relative change: 1.422e-05
## Maximum item intercept parameter change: 0.045677
## Maximum item slope parameter change: 0.018485
## Maximum item guessing parameter change: 0.000374
## Maximum regression parameter change: 0
## Maximum variance parameter change: 5.2e-05
## ....................................................
## Iteration 190 2021-07-06 17:56:46
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089702.036 | Absolute change: 15.6521 | Relative change: 1.436e-05
## Maximum item intercept parameter change: 0.044867
## Maximum item slope parameter change: 0.019542
## Maximum item guessing parameter change: 0.000369
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000193
## ....................................................
## Iteration 191 2021-07-06 17:56:47
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089686.2646 | Absolute change: 15.7714 | Relative change: 1.447e-05
## Maximum item intercept parameter change: 0.048516
## Maximum item slope parameter change: 0.020527
## Maximum item guessing parameter change: 0.000364
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000322
## ....................................................
## Iteration 192 2021-07-06 17:56:47
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089670.4016 | Absolute change: 15.863 | Relative change: 1.456e-05
## Maximum item intercept parameter change: 0.053587
## Maximum item slope parameter change: 0.021438
## Maximum item guessing parameter change: 0.000358
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000445
## ....................................................
## Iteration 193 2021-07-06 17:56:47
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089654.4645 | Absolute change: 15.9371 | Relative change: 1.463e-05
## Maximum item intercept parameter change: 0.058508
## Maximum item slope parameter change: 0.022272
## Maximum item guessing parameter change: 0.000355
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000563
## ....................................................
## Iteration 194 2021-07-06 17:56:47
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089638.4632 | Absolute change: 16.0013 | Relative change: 1.468e-05
## Maximum item intercept parameter change: 0.063262
## Maximum item slope parameter change: 0.023028
## Maximum item guessing parameter change: 0.000356
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000681
## ....................................................
## Iteration 195 2021-07-06 17:56:47
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089622.4018 | Absolute change: 16.0615 | Relative change: 1.474e-05
## Maximum item intercept parameter change: 0.067829
## Maximum item slope parameter change: 0.023706
## Maximum item guessing parameter change: 0.000358
## Maximum regression parameter change: 0
## Maximum variance parameter change: 8e-04
## ....................................................
## Iteration 196 2021-07-06 17:56:48
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089606.2804 | Absolute change: 16.1214 | Relative change: 1.48e-05
## Maximum item intercept parameter change: 0.072186
## Maximum item slope parameter change: 0.024307
## Maximum item guessing parameter change: 0.00036
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000921
## ....................................................
## Iteration 197 2021-07-06 17:56:48
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089590.0973 | Absolute change: 16.1831 | Relative change: 1.485e-05
## Maximum item intercept parameter change: 0.076307
## Maximum item slope parameter change: 0.024832
## Maximum item guessing parameter change: 0.000361
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001045
## ....................................................
## Iteration 198 2021-07-06 17:56:48
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089573.8501 | Absolute change: 16.2472 | Relative change: 1.491e-05
## Maximum item intercept parameter change: 0.080167
## Maximum item slope parameter change: 0.025284
## Maximum item guessing parameter change: 0.000361
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001171
## ....................................................
## Iteration 199 2021-07-06 17:56:48
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089557.5371 | Absolute change: 16.313 | Relative change: 1.497e-05
## Maximum item intercept parameter change: 0.083742
## Maximum item slope parameter change: 0.025666
## Maximum item guessing parameter change: 0.000362
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001299
## ....................................................
## Iteration 200 2021-07-06 17:56:49
## E Step
## M Step Intercepts |---
## M Step Slopes |---
## M Step Guessing |--
## Deviance = 1089541.1585 | Absolute change: 16.3785 | Relative change: 1.503e-05
## Maximum item intercept parameter change: 0.08701
## Maximum item slope parameter change: 0.025982
## Maximum item guessing parameter change: 0.000361
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001427
## ....................................................
## Item Parameters
## xsi.index xsi.label est
## 1 1 ch_1 0.9070
## 2 2 ch_2 -0.5063
## 3 3 ch_3 1.5913
## 4 4 ch_4 -0.2697
## 5 5 ch_5 6.4307
## 6 6 ch_6 1.4808
## 7 7 ch_7 5.2484
## 8 8 ch_8 0.8735
## 9 9 ch_9 -0.8838
## 10 10 ch_10 6.2094
## 11 11 ch_11 -0.7192
## 12 12 ch_12 0.7370
## 13 13 ch_13 2.2841
## 14 14 ch_14 0.8410
## 15 15 ch_15 2.5512
## 16 16 ch_16 3.8079
## 17 17 ch_17 0.3873
## 18 18 ch_18 0.7253
## 19 19 ch_19 0.3873
## 20 20 ch_20 10.2652
## 21 21 ch_21 -0.6605
## 22 22 ch_22 1.6396
## 23 23 ch_23 4.3814
## 24 24 ch_24 5.5424
## 25 25 ch_25 0.5979
## 26 26 ch_26 0.0087
## 27 27 ch_27 0.6439
## 28 28 ch_28 3.1547
## 29 29 ch_29 0.5087
## 30 30 ch_30 2.9683
## 31 31 ch_31 1.4916
## 32 32 ch_32 1.4637
## 33 33 ch_33 0.7336
## 34 34 ch_34 1.9042
## 35 35 ch_35 5.7060
## 36 36 ch_36 1.2729
## 37 37 ch_37 0.9287
## 38 38 ch_38 1.6700
## 39 39 ch_39 2.4816
## 40 40 ch_40 2.1908
## 41 41 ch_41 2.0277
## 42 42 ch_42 -0.7449
## 43 43 ch_43 1.3159
## 44 44 ch_44 -0.4331
## 45 45 ch_45 1.0906
## ...................................
## Regression Coefficients
## [,1]
## [1,] 0
##
## Variance:
## [,1]
## [1,] 0.598
##
##
## EAP Reliability:
## [1] 0.779
##
## -----------------------------
##
## Minimal deviance at iteration 8 with deviance 1078801.968
## The corresponding estimates are
## xsi.min.deviance
## beta.min.deviance
## variance.min.deviance
##
##
## Start: 2021-07-06 17:55:40
## End: 2021-07-06 17:56:49
## Time difference of 1.147856 minssummary(mod3)## ------------------------------------------------------------
## TAM 3.7-16 (2021-06-24 14:31:37)
## R version 4.0.2 (2020-06-22) x86_64, mingw32 | nodename=DESKTOP-U0L65SJ | login=araec
##
## Date of Analysis: 2021-07-06 17:56:49
## Time difference of 1.147856 mins
## Computation time: 1.147856
##
## Multidimensional Item Response Model in TAM
##
## IRT Model 2PL (Function 'tam.mml.3pl')
## Call:
## tam.mml.3pl(resp = score_ch2, est.guess = 1:ncol(score_ch2),
## guess = rep(0.2, ncol(score_ch2)), control = list(maxiter = 200,
## conv = 0.001))
##
## ------------------------------------------------------------
## Number of iterations = 200
##
## Skill space: Normal Distribution
## Numeric integration with 21 integration points
##
## Deviance = 1078802 | Log Likelihood = -539401
## Number of persons = 20000
## Number of persons used = 20000
## Number of items = 45
## Number of estimated parameters = 136
## Item threshold parameters = 45
## Item slope parameters = 45
## Non-active item slopes = 0
## Item guessing parameters = 45
## Regression parameters = 0
## Variance/covariance parameters = 1
## Delta parameters = 0
##
## AIC = 1079074 | penalty=272 | AIC=-2*LL + 2*p
## AIC3 = 1079210 | penalty=408 | AIC3=-2*LL + 3*p
## BIC = 1080149 | penalty=1346.87 | BIC=-2*LL + log(n)*p
## aBIC = 1079717 | penalty=914.65 | aBIC=-2*LL + log((n-2)/24)*p (adjusted BIC)
## CAIC = 1080285 | penalty=1482.87 | CAIC=-2*LL + [log(n)+1]*p (consistent AIC)
## AICc = 1079076 | penalty=273.88 | AICc=-2*LL + 2*p + 2*p*(p+1)/(n-p-1) (bias corrected AIC)
## GHP = 0.59949 | GHP=( -LL + p ) / (#Persons * #Items) (Gilula-Haberman log penalty)
##
## ------------------------------------------------------------
## EAP Reliability
## [1] 0.779
## ------------------------------------------------------------
## Covariances and Variances
## [,1]
## [1,] 0.598
## ------------------------------------------------------------
## Correlations and Standard Deviations (in the diagonal)
## [,1]
## [1,] 0.773
## ------------------------------------------------------------
## Regression Coefficients
## [,1]
## [1,] 0
## ------------------------------------------------------------
## Item Parameters -A*Xsi
## item N M est.guess guess AXsi_.Cat1 B.Cat1.Dim1
## 1 ch_1 20000 0.466 1 0.289 0.907 1.692
## 2 ch_2 20000 0.665 2 0.285 -0.506 1.812
## 3 ch_3 20000 0.406 3 0.286 1.591 2.377
## 4 ch_4 20000 0.642 4 0.288 -0.270 1.091
## 5 ch_5 20000 0.181 5 0.132 6.431 5.560
## 6 ch_6 20000 0.391 6 0.281 1.481 1.729
## 7 ch_7 20000 0.216 7 0.191 5.248 3.855
## 8 ch_8 20000 0.467 8 0.291 0.873 1.556
## 9 ch_9 20000 0.745 9 0.282 -0.884 0.991
## 10 ch_10 20000 0.185 10 0.182 6.209 4.350
## 11 ch_11 20000 0.732 11 0.287 -0.719 0.557
## 12 ch_12 20000 0.491 12 0.269 0.737 2.261
## 13 ch_13 20000 0.378 13 0.284 2.284 3.708
## 14 ch_14 20000 0.473 14 0.281 0.841 1.816
## 15 ch_15 20000 0.332 15 0.272 2.551 2.847
## 16 ch_16 20000 0.241 16 0.238 3.808 2.218
## 17 ch_17 20000 0.532 17 0.295 0.387 0.898
## 18 ch_18 20000 0.473 18 0.286 0.725 0.911
## 19 ch_19 20000 0.539 19 0.288 0.387 1.862
## 20 ch_20 20000 0.154 20 0.154 10.265 5.650
## 21 ch_21 20000 0.714 21 0.283 -0.661 0.843
## 22 ch_22 20000 0.383 22 0.287 1.640 1.919
## 23 ch_23 20000 0.230 23 0.228 4.381 2.331
## 24 ch_24 20000 0.209 24 0.155 5.542 5.032
## 25 ch_25 20000 0.496 25 0.279 0.598 1.273
## 26 ch_26 20000 0.600 26 0.289 0.009 0.486
## 27 ch_27 20000 0.506 27 0.278 0.644 2.206
## 28 ch_28 20000 0.295 28 0.245 3.155 2.910
## 29 ch_29 20000 0.518 29 0.272 0.509 1.968
## 30 ch_30 20000 0.274 30 0.247 2.968 2.147
## 31 ch_31 20000 0.376 31 0.290 1.492 1.154
## 32 ch_32 20000 0.373 32 0.283 1.464 1.075
## 33 ch_33 20000 0.468 33 0.286 0.734 0.599
## 34 ch_34 20000 0.353 34 0.296 1.904 1.713
## 35 ch_35 20000 0.197 35 0.160 5.706 4.570
## 36 ch_36 20000 0.399 36 0.295 1.273 0.975
## 37 ch_37 20000 0.439 37 0.291 0.929 0.636
## 38 ch_38 20000 0.386 38 0.294 1.670 1.913
## 39 ch_39 20000 0.328 39 0.269 2.482 3.027
## 40 ch_40 20000 0.293 40 0.293 2.191 0.402
## 41 ch_41 20000 0.337 41 0.289 2.028 1.726
## 42 ch_42 20000 0.710 42 0.281 -0.745 1.385
## 43 ch_43 20000 0.408 43 0.289 1.316 1.531
## 44 ch_44 20000 0.673 44 0.287 -0.433 0.930
## 45 ch_45 20000 0.415 45 0.287 1.091 0.734
##
## Gammaslope Parameters
## [1] 1.692 1.812 2.377 1.091 5.560 1.729 3.855 1.556 0.991 4.350 0.557 2.261
## [13] 3.708 1.816 2.847 2.218 0.898 0.911 1.862 5.650 0.843 1.919 2.331 5.032
## [25] 1.273 0.486 2.206 2.910 1.968 2.147 1.154 1.075 0.599 1.713 4.570 0.975
## [37] 0.636 1.913 3.027 0.402 1.726 1.385 1.531 0.930 0.734mod3$item_irt %>% view
hist(mod3$person$EAP)
hist(mod3$xsi$xsi)
Correlacionando 1, 2, e 3 parâmetros a partir dos resultados do TAM
df <- tibble(
scr = mod1$person$score,
eap1 = mod1$person$EAP,
eap2 = mod2$person$EAP,
eap3 = mod3$person$EAP
)
corr.test(df)## Call:corr.test(x = df)
## Correlation matrix
## scr eap1 eap2 eap3
## scr 1.00 1.00 0.98 0.97
## eap1 1.00 1.00 0.98 0.97
## eap2 0.98 0.98 1.00 0.98
## eap3 0.97 0.97 0.98 1.00
## Sample Size
## [1] 20000
## Probability values (Entries above the diagonal are adjusted for multiple tests.)
## scr eap1 eap2 eap3
## scr 0 0 0 0
## eap1 0 0 0 0
## eap2 0 0 0 0
## eap3 0 0 0 0
##
## To see confidence intervals of the correlations, print with the short=FALSE optiondf %>% ggplot(aes(y = eap1, x = scr, color = scr)) +
geom_point(alpha=.2) + theme_light() + geom_smooth()
df %>% ggplot(aes(y = eap2, x = scr, color = scr)) +
geom_point(alpha=.2) + theme_light() + geom_smooth()
df %>% ggplot(aes(y = eap3, x = scr, color = scr)) +
geom_point(alpha=.2) + theme_light() + geom_smooth()
df %>% ggplot(aes(y = eap1, x = eap2, color = scr)) +
geom_point(alpha=.2) + theme_light() + geom_smooth()
df %>% ggplot(aes(y = eap3, x = eap1, color = scr)) +
geom_point(alpha=.2) + theme_light() + geom_smooth()
df %>% ggplot(aes(y = eap2, x = eap3, color = scr)) +
geom_point(alpha=.2) + theme_light() + geom_smooth()
Calibrações usando o MIRT
Rasch no MIRT
\(P(x = 1|θ, d) = \frac{1}{1 + exp(-(θ + d))}\)
Veja https://philchalmers.github.io/mirt/html/Three-Rasch.html
Fixed slope set to 1
mod1 <- mirt(score_ch2, model = 1, TOL = .001, itemtype='Rasch')##
Iteration: 1, Log-Lik: -546715.471, Max-Change: 0.43162
Iteration: 2, Log-Lik: -544658.421, Max-Change: 0.09291
Iteration: 3, Log-Lik: -544432.135, Max-Change: 0.03127
Iteration: 4, Log-Lik: -544393.545, Max-Change: 0.01233
Iteration: 5, Log-Lik: -544384.074, Max-Change: 0.00522
Iteration: 6, Log-Lik: -544380.551, Max-Change: 0.00372
Iteration: 7, Log-Lik: -544376.547, Max-Change: 0.00203
Iteration: 8, Log-Lik: -544376.288, Max-Change: 0.00095summary(mod1)## F1 h2
## ch_1 0.329 0.108
## ch_2 0.329 0.108
## ch_3 0.329 0.108
## ch_4 0.329 0.108
## ch_5 0.329 0.108
## ch_6 0.329 0.108
## ch_7 0.329 0.108
## ch_8 0.329 0.108
## ch_9 0.329 0.108
## ch_10 0.329 0.108
## ch_11 0.329 0.108
## ch_12 0.329 0.108
## ch_13 0.329 0.108
## ch_14 0.329 0.108
## ch_15 0.329 0.108
## ch_16 0.329 0.108
## ch_17 0.329 0.108
## ch_18 0.329 0.108
## ch_19 0.329 0.108
## ch_20 0.329 0.108
## ch_21 0.329 0.108
## ch_22 0.329 0.108
## ch_23 0.329 0.108
## ch_24 0.329 0.108
## ch_25 0.329 0.108
## ch_26 0.329 0.108
## ch_27 0.329 0.108
## ch_28 0.329 0.108
## ch_29 0.329 0.108
## ch_30 0.329 0.108
## ch_31 0.329 0.108
## ch_32 0.329 0.108
## ch_33 0.329 0.108
## ch_34 0.329 0.108
## ch_35 0.329 0.108
## ch_36 0.329 0.108
## ch_37 0.329 0.108
## ch_38 0.329 0.108
## ch_39 0.329 0.108
## ch_40 0.329 0.108
## ch_41 0.329 0.108
## ch_42 0.329 0.108
## ch_43 0.329 0.108
## ch_44 0.329 0.108
## ch_45 0.329 0.108
##
## SS loadings: 4.88
## Proportion Var: 0.108
##
## Factor correlations:
##
## F1
## F1 1coef(mod1 , simplify=TRUE) %>% view
coef(mod1 , simplify=TRUE, IRTpars=TRUE) %>% view
plot(mod1, type = 'trace', facet_items = TRUE)
itemfit(mod1, fit_stats = 'infit')## item outfit z.outfit infit z.infit
## 1 ch_1 0.933 -15.758 0.938 -16.432
## 2 ch_2 0.866 -18.923 0.906 -17.163
## 3 ch_3 0.913 -17.035 0.920 -17.923
## 4 ch_4 0.947 -8.058 0.960 -7.952
## 5 ch_5 0.863 -9.901 0.921 -6.892
## 6 ch_6 0.944 -10.175 0.953 -9.868
## 7 ch_7 1.010 0.789 0.995 -0.492
## 8 ch_8 0.939 -14.354 0.948 -13.801
## 9 ch_9 0.965 -3.384 0.966 -4.218
## 10 ch_10 1.008 0.570 0.999 -0.121
## 11 ch_11 1.047 4.611 1.011 1.403
## 12 ch_12 0.872 -31.306 0.885 -32.191
## 13 ch_13 0.862 -24.637 0.875 -25.564
## 14 ch_14 0.907 -22.143 0.918 -22.043
## 15 ch_15 0.920 -11.371 0.928 -11.975
## 16 ch_16 1.043 3.883 1.030 3.376
## 17 ch_17 0.984 -3.507 0.995 -1.323
## 18 ch_18 0.993 -1.662 0.995 -1.340
## 19 ch_19 0.893 -24.604 0.910 -24.917
## 20 ch_20 1.112 6.468 1.053 3.851
## 21 ch_21 0.982 -1.951 0.975 -3.577
## 22 ch_22 0.938 -11.002 0.946 -10.905
## 23 ch_23 1.094 7.926 1.056 5.891
## 24 ch_24 0.892 -8.788 0.924 -7.521
## 25 ch_25 0.945 -13.075 0.949 -13.985
## 26 ch_26 1.041 7.203 1.032 7.396
## 27 ch_27 0.875 -30.455 0.889 -31.336
## 28 ch_28 0.958 -4.923 0.957 -6.092
## 29 ch_29 0.884 -27.854 0.894 -29.860
## 30 ch_30 0.984 -1.702 0.992 -1.017
## 31 ch_31 1.009 1.466 1.008 1.492
## 32 ch_32 1.006 1.064 1.009 1.712
## 33 ch_33 1.036 8.144 1.032 8.274
## 34 ch_34 0.984 -2.476 0.984 -2.901
## 35 ch_35 0.940 -4.563 0.958 -3.934
## 36 ch_36 1.024 4.412 1.020 4.256
## 37 ch_37 1.044 9.297 1.040 9.537
## 38 ch_38 0.957 -7.687 0.958 -8.480
## 39 ch_39 0.873 -17.947 0.898 -16.892
## 40 ch_40 1.110 12.328 1.091 12.304
## 41 ch_41 0.981 -2.670 0.984 -2.680
## 42 ch_42 0.897 -11.764 0.932 -10.153
## 43 ch_43 0.963 -7.243 0.967 -7.375
## 44 ch_44 0.958 -5.527 0.970 -5.179
## 45 ch_45 1.035 6.758 1.033 7.313itemfit(mod1, empirical.plot=3)
itemfit(mod1, empirical.plot=41)
theta1a <- mirt::fscores(mod1, method = "ML")
skim(theta1a)| Name | theta1a |
| Number of rows | 20000 |
| Number of columns | 1 |
| _______________________ | |
| Column type frequency: | |
| numeric | 1 |
| ________________________ | |
| Group variables | None |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| F1 | 0 | 1 | -Inf | NaN | -Inf | -0.53 | -0.09 | 0.42 | 3.68 | ▁▂▇▂▁ |
skim(theta1a[!is.infinite(theta1a)])| Name | theta1a[!is.infinite(thet… |
| Number of rows | 19998 |
| Number of columns | 1 |
| _______________________ | |
| Column type frequency: | |
| numeric | 1 |
| ________________________ | |
| Group variables | None |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| data | 0 | 1 | 0 | 0.74 | -3.7 | -0.53 | -0.09 | 0.42 | 3.68 | ▁▂▇▂▁ |
# parâmetros
parms1 <- mirt(
score_ch2,
model = 1, TOL = .001,
itemtype='Rasch',
pars = 'values'
) - Freely estimate slope parameters but constrain them to be equal across all items
m1 <- mirt.model(
'Theta = 1-45
CONSTRAIN = (1-45, a1)'
)
parms1b <- mirt(score_ch2, model = m1, TOL = .001, pars = 'values')
mod1b <- mirt(score_ch2, model = m1, TOL = .001)##
Iteration: 1, Log-Lik: -545568.410, Max-Change: 0.14840
Iteration: 2, Log-Lik: -544743.211, Max-Change: 0.04333
Iteration: 3, Log-Lik: -544545.919, Max-Change: 0.02347
Iteration: 4, Log-Lik: -544465.607, Max-Change: 0.02249
Iteration: 5, Log-Lik: -544411.640, Max-Change: 0.01512
Iteration: 6, Log-Lik: -544388.649, Max-Change: 0.00987
Iteration: 7, Log-Lik: -544379.874, Max-Change: 0.00365
Iteration: 8, Log-Lik: -544377.829, Max-Change: 0.00245
Iteration: 9, Log-Lik: -544376.866, Max-Change: 0.00155
Iteration: 10, Log-Lik: -544376.159, Max-Change: 0.00083summary(mod1b)## Theta h2
## ch_1 0.357 0.128
## ch_2 0.357 0.128
## ch_3 0.357 0.128
## ch_4 0.357 0.128
## ch_5 0.357 0.128
## ch_6 0.357 0.128
## ch_7 0.357 0.128
## ch_8 0.357 0.128
## ch_9 0.357 0.128
## ch_10 0.357 0.128
## ch_11 0.357 0.128
## ch_12 0.357 0.128
## ch_13 0.357 0.128
## ch_14 0.357 0.128
## ch_15 0.357 0.128
## ch_16 0.357 0.128
## ch_17 0.357 0.128
## ch_18 0.357 0.128
## ch_19 0.357 0.128
## ch_20 0.357 0.128
## ch_21 0.357 0.128
## ch_22 0.357 0.128
## ch_23 0.357 0.128
## ch_24 0.357 0.128
## ch_25 0.357 0.128
## ch_26 0.357 0.128
## ch_27 0.357 0.128
## ch_28 0.357 0.128
## ch_29 0.357 0.128
## ch_30 0.357 0.128
## ch_31 0.357 0.128
## ch_32 0.357 0.128
## ch_33 0.357 0.128
## ch_34 0.357 0.128
## ch_35 0.357 0.128
## ch_36 0.357 0.128
## ch_37 0.357 0.128
## ch_38 0.357 0.128
## ch_39 0.357 0.128
## ch_40 0.357 0.128
## ch_41 0.357 0.128
## ch_42 0.357 0.128
## ch_43 0.357 0.128
## ch_44 0.357 0.128
## ch_45 0.357 0.128
##
## SS loadings: 5.744
## Proportion Var: 0.128
##
## Factor correlations:
##
## Theta
## Theta 1summary(mod1)## F1 h2
## ch_1 0.329 0.108
## ch_2 0.329 0.108
## ch_3 0.329 0.108
## ch_4 0.329 0.108
## ch_5 0.329 0.108
## ch_6 0.329 0.108
## ch_7 0.329 0.108
## ch_8 0.329 0.108
## ch_9 0.329 0.108
## ch_10 0.329 0.108
## ch_11 0.329 0.108
## ch_12 0.329 0.108
## ch_13 0.329 0.108
## ch_14 0.329 0.108
## ch_15 0.329 0.108
## ch_16 0.329 0.108
## ch_17 0.329 0.108
## ch_18 0.329 0.108
## ch_19 0.329 0.108
## ch_20 0.329 0.108
## ch_21 0.329 0.108
## ch_22 0.329 0.108
## ch_23 0.329 0.108
## ch_24 0.329 0.108
## ch_25 0.329 0.108
## ch_26 0.329 0.108
## ch_27 0.329 0.108
## ch_28 0.329 0.108
## ch_29 0.329 0.108
## ch_30 0.329 0.108
## ch_31 0.329 0.108
## ch_32 0.329 0.108
## ch_33 0.329 0.108
## ch_34 0.329 0.108
## ch_35 0.329 0.108
## ch_36 0.329 0.108
## ch_37 0.329 0.108
## ch_38 0.329 0.108
## ch_39 0.329 0.108
## ch_40 0.329 0.108
## ch_41 0.329 0.108
## ch_42 0.329 0.108
## ch_43 0.329 0.108
## ch_44 0.329 0.108
## ch_45 0.329 0.108
##
## SS loadings: 4.88
## Proportion Var: 0.108
##
## Factor correlations:
##
## F1
## F1 1coef(mod1b , simplify=TRUE, IRTpars=TRUE) %>% view
theta1b <- mirt::fscores(mod1b, method = "ML")
skim(theta1b[!is.infinite(theta1b)])| Name | theta1b[!is.infinite(thet… |
| Number of rows | 19998 |
| Number of columns | 1 |
| _______________________ | |
| Column type frequency: | |
| numeric | 1 |
| ________________________ | |
| Group variables | None |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| data | 0 | 1 | 0 | 1.14 | -5.68 | -0.81 | -0.14 | 0.64 | 5.66 | ▁▂▇▂▁ |
hist(theta1a, at = seq(-4, 4, .5), xlim = c(-4,4))
hist(theta1b, at = seq(-4, 4, .5), xlim = c(-4,4))
- Fix slopes to 1, center intercept mean = 0
#constraint: create function for solnp to compute constraint, and declare value in eqB
eqfun <- function(p, optim_args) sum(p[1:45])
solnp_args <- list(eqfun=eqfun, eqB=0, LB = c(rep(-15, 46), 1e-4))
m2 <- mirt.model(
'Theta = 1-45
MEAN = Theta
COV = Theta*Theta'
)
mod1c <- mirt(
score_ch2,
model = m2,
TOL = .001,
itemtype = "Rasch",
optimizer = 'solnp',
solnp_args=solnp_args
)##
Iteration: 1, Log-Lik: -546715.471, Max-Change: 0.65504
Iteration: 2, Log-Lik: -547109.774, Max-Change: 0.32907
Iteration: 3, Log-Lik: -544494.814, Max-Change: 0.05397
Iteration: 4, Log-Lik: -544384.552, Max-Change: 0.01150
Iteration: 5, Log-Lik: -544376.923, Max-Change: 0.00423
Iteration: 6, Log-Lik: -544376.111, Max-Change: 0.00038summary(mod1c)## Theta h2
## ch_1 0.33 0.109
## ch_2 0.33 0.109
## ch_3 0.33 0.109
## ch_4 0.33 0.109
## ch_5 0.33 0.109
## ch_6 0.33 0.109
## ch_7 0.33 0.109
## ch_8 0.33 0.109
## ch_9 0.33 0.109
## ch_10 0.33 0.109
## ch_11 0.33 0.109
## ch_12 0.33 0.109
## ch_13 0.33 0.109
## ch_14 0.33 0.109
## ch_15 0.33 0.109
## ch_16 0.33 0.109
## ch_17 0.33 0.109
## ch_18 0.33 0.109
## ch_19 0.33 0.109
## ch_20 0.33 0.109
## ch_21 0.33 0.109
## ch_22 0.33 0.109
## ch_23 0.33 0.109
## ch_24 0.33 0.109
## ch_25 0.33 0.109
## ch_26 0.33 0.109
## ch_27 0.33 0.109
## ch_28 0.33 0.109
## ch_29 0.33 0.109
## ch_30 0.33 0.109
## ch_31 0.33 0.109
## ch_32 0.33 0.109
## ch_33 0.33 0.109
## ch_34 0.33 0.109
## ch_35 0.33 0.109
## ch_36 0.33 0.109
## ch_37 0.33 0.109
## ch_38 0.33 0.109
## ch_39 0.33 0.109
## ch_40 0.33 0.109
## ch_41 0.33 0.109
## ch_42 0.33 0.109
## ch_43 0.33 0.109
## ch_44 0.33 0.109
## ch_45 0.33 0.109
##
## SS loadings: 4.907
## Proportion Var: 0.109
##
## Factor correlations:
##
## Theta
## Theta 1ipars <- coef(mod1c , simplify=TRUE, IRTpars=TRUE)
round(mean(ipars$items[, 2]), 4)## [1] 0theta1c<- mirt::fscores(mod1c, method = "ML")
skim(theta1b[!is.infinite(theta1c)])| Name | theta1b[!is.infinite(thet… |
| Number of rows | 19998 |
| Number of columns | 1 |
| _______________________ | |
| Column type frequency: | |
| numeric | 1 |
| ________________________ | |
| Group variables | None |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| data | 0 | 1 | 0 | 1.14 | -5.68 | -0.81 | -0.14 | 0.64 | 5.66 | ▁▂▇▂▁ |
hist(theta1a, at = seq(-4, 4, .5), xlim = c(-4,4))
hist(theta1b, at = seq(-4, 4, .5), xlim = c(-4,4))
hist(theta1c, at = seq(-4, 4, .5), xlim = c(-4,4))
parms1c <- mirt( score_ch2,
model = m2,
TOL = .001,
itemtype = "Rasch",
optimizer = 'solnp',
solnp_args=solnp_args,
pars = 'values'
) Dois parâmetros no mirt
mod2 <- mirt(score_ch2, model = 1, TOL = .001, itemtype='2PL')##
Iteration: 1, Log-Lik: -545568.410, Max-Change: 0.57866
Iteration: 2, Log-Lik: -540384.657, Max-Change: 0.12528
Iteration: 3, Log-Lik: -539963.652, Max-Change: 0.03952
Iteration: 4, Log-Lik: -539881.493, Max-Change: 0.02362
Iteration: 5, Log-Lik: -539848.383, Max-Change: 0.01780
Iteration: 6, Log-Lik: -539833.010, Max-Change: 0.01299
Iteration: 7, Log-Lik: -539825.594, Max-Change: 0.00907
Iteration: 8, Log-Lik: -539822.001, Max-Change: 0.00617
Iteration: 9, Log-Lik: -539820.219, Max-Change: 0.00427
Iteration: 10, Log-Lik: -539818.687, Max-Change: 0.00141
Iteration: 11, Log-Lik: -539818.562, Max-Change: 0.00103
Iteration: 12, Log-Lik: -539818.496, Max-Change: 0.00090parms2 <- mirt(score_ch2, model = 1, TOL = .001, itemtype='2PL', pars = 'values')
summary(mod2)## F1 h2
## ch_1 0.4197 0.1761
## ch_2 0.5624 0.3163
## ch_3 0.4713 0.2221
## ch_4 0.3787 0.1434
## ch_5 0.5297 0.2806
## ch_6 0.3946 0.1557
## ch_7 0.3042 0.0925
## ch_8 0.3999 0.1599
## ch_9 0.3724 0.1386
## ch_10 0.3184 0.1014
## ch_11 0.2126 0.0452
## ch_12 0.5712 0.3262
## ch_13 0.5925 0.3510
## ch_14 0.4751 0.2257
## ch_15 0.4559 0.2078
## ch_16 0.2197 0.0483
## ch_17 0.2721 0.0740
## ch_18 0.2675 0.0715
## ch_19 0.5078 0.2579
## ch_20 0.1623 0.0264
## ch_21 0.3178 0.1010
## ch_22 0.4038 0.1630
## ch_23 0.1465 0.0215
## ch_24 0.5027 0.2527
## ch_25 0.3846 0.1479
## ch_26 0.1731 0.0300
## ch_27 0.5533 0.3061
## ch_28 0.3847 0.1480
## ch_29 0.5342 0.2853
## ch_30 0.3189 0.1017
## ch_31 0.2502 0.0626
## ch_32 0.2499 0.0624
## ch_33 0.1818 0.0331
## ch_34 0.3159 0.0998
## ch_35 0.4265 0.1819
## ch_36 0.2189 0.0479
## ch_37 0.1719 0.0295
## ch_38 0.3677 0.1352
## ch_39 0.5383 0.2898
## ch_40 0.0632 0.0040
## ch_41 0.3214 0.1033
## ch_42 0.4831 0.2334
## ch_43 0.3519 0.1238
## ch_44 0.3316 0.1100
## ch_45 0.1872 0.0351
##
## SS loadings: 6.53
## Proportion Var: 0.145
##
## Factor correlations:
##
## F1
## F1 1coef(mod2 , simplify=TRUE, IRTpars=TRUE) %>% view
plot(mod2, type = 'trace', facet_items = FALSE)
coef(mod2 )## $ch_1
## a1 d g u
## par 0.787 -0.147 0 1
##
## $ch_2
## a1 d g u
## par 1.158 0.882 0 1
##
## $ch_3
## a1 d g u
## par 0.909 -0.431 0 1
##
## $ch_4
## a1 d g u
## par 0.696 0.654 0 1
##
## $ch_5
## a1 d g u
## par 1.063 -1.828 0 1
##
## $ch_6
## a1 d g u
## par 0.731 -0.488 0 1
##
## $ch_7
## a1 d g u
## par 0.544 -1.371 0 1
##
## $ch_8
## a1 d g u
## par 0.743 -0.14 0 1
##
## $ch_9
## a1 d g u
## par 0.683 1.176 0 1
##
## $ch_10
## a1 d g u
## par 0.572 -1.58 0 1
##
## $ch_11
## a1 d g u
## par 0.37 1.034 0 1
##
## $ch_12
## a1 d g u
## par 1.184 -0.016 0 1
##
## $ch_13
## a1 d g u
## par 1.252 -0.616 0 1
##
## $ch_14
## a1 d g u
## par 0.919 -0.112 0 1
##
## $ch_15
## a1 d g u
## par 0.872 -0.803 0 1
##
## $ch_16
## a1 d g u
## par 0.383 -1.183 0 1
##
## $ch_17
## a1 d g u
## par 0.481 0.136 0 1
##
## $ch_18
## a1 d g u
## par 0.472 -0.111 0 1
##
## $ch_19
## a1 d g u
## par 1.003 0.208 0 1
##
## $ch_20
## a1 d g u
## par 0.28 -1.732 0 1
##
## $ch_21
## a1 d g u
## par 0.57 0.978 0 1
##
## $ch_22
## a1 d g u
## par 0.751 -0.528 0 1
##
## $ch_23
## a1 d g u
## par 0.252 -1.223 0 1
##
## $ch_24
## a1 d g u
## par 0.99 -1.58 0 1
##
## $ch_25
## a1 d g u
## par 0.709 -0.008 0 1
##
## $ch_26
## a1 d g u
## par 0.299 0.413 0 1
##
## $ch_27
## a1 d g u
## par 1.13 0.058 0 1
##
## $ch_28
## a1 d g u
## par 0.709 -0.963 0 1
##
## $ch_29
## a1 d g u
## par 1.075 0.11 0 1
##
## $ch_30
## a1 d g u
## par 0.573 -1.042 0 1
##
## $ch_31
## a1 d g u
## par 0.44 -0.53 0 1
##
## $ch_32
## a1 d g u
## par 0.439 -0.54 0 1
##
## $ch_33
## a1 d g u
## par 0.315 -0.133 0 1
##
## $ch_34
## a1 d g u
## par 0.567 -0.649 0 1
##
## $ch_35
## a1 d g u
## par 0.803 -1.586 0 1
##
## $ch_36
## a1 d g u
## par 0.382 -0.424 0 1
##
## $ch_37
## a1 d g u
## par 0.297 -0.252 0 1
##
## $ch_38
## a1 d g u
## par 0.673 -0.505 0 1
##
## $ch_39
## a1 d g u
## par 1.087 -0.866 0 1
##
## $ch_40
## a1 d g u
## par 0.108 -0.884 0 1
##
## $ch_41
## a1 d g u
## par 0.578 -0.726 0 1
##
## $ch_42
## a1 d g u
## par 0.939 1.064 0 1
##
## $ch_43
## a1 d g u
## par 0.64 -0.4 0 1
##
## $ch_44
## a1 d g u
## par 0.598 0.782 0 1
##
## $ch_45
## a1 d g u
## par 0.324 -0.351 0 1
##
## $GroupPars
## MEAN_1 COV_11
## par 0 1itemfit(mod2)## item S_X2 df.S_X2 RMSEA.S_X2 p.S_X2
## 1 ch_1 116.182 34 0.011 0.000
## 2 ch_2 28.950 31 0.000 0.572
## 3 ch_3 120.382 34 0.011 0.000
## 4 ch_4 53.664 34 0.005 0.017
## 5 ch_5 105.781 34 0.010 0.000
## 6 ch_6 38.033 35 0.002 0.333
## 7 ch_7 103.037 36 0.010 0.000
## 8 ch_8 65.414 34 0.007 0.001
## 9 ch_9 239.228 35 0.017 0.000
## 10 ch_10 102.373 35 0.010 0.000
## 11 ch_11 207.656 36 0.015 0.000
## 12 ch_12 57.529 32 0.006 0.004
## 13 ch_13 172.421 32 0.015 0.000
## 14 ch_14 32.082 33 0.000 0.513
## 15 ch_15 115.284 34 0.011 0.000
## 16 ch_16 31.286 36 0.000 0.692
## 17 ch_17 145.898 36 0.012 0.000
## 18 ch_18 67.308 36 0.007 0.001
## 19 ch_19 65.770 33 0.007 0.001
## 20 ch_20 68.930 36 0.007 0.001
## 21 ch_21 241.754 35 0.017 0.000
## 22 ch_22 42.156 35 0.003 0.189
## 23 ch_23 51.620 36 0.005 0.044
## 24 ch_24 244.030 34 0.018 0.000
## 25 ch_25 159.726 35 0.013 0.000
## 26 ch_26 61.793 37 0.006 0.006
## 27 ch_27 57.582 32 0.006 0.004
## 28 ch_28 158.288 35 0.013 0.000
## 29 ch_29 143.232 33 0.013 0.000
## 30 ch_30 48.215 35 0.004 0.068
## 31 ch_31 35.095 36 0.000 0.511
## 32 ch_32 70.438 36 0.007 0.001
## 33 ch_33 233.303 36 0.017 0.000
## 34 ch_34 64.234 35 0.006 0.002
## 35 ch_35 143.773 34 0.013 0.000
## 36 ch_36 67.053 36 0.007 0.001
## 37 ch_37 33.368 36 0.000 0.594
## 38 ch_38 150.493 35 0.013 0.000
## 39 ch_39 120.873 33 0.012 0.000
## 40 ch_40 91.233 37 0.009 0.000
## 41 ch_41 55.845 35 0.005 0.014
## 42 ch_42 80.630 33 0.008 0.000
## 43 ch_43 39.445 35 0.003 0.278
## 44 ch_44 73.073 35 0.007 0.000
## 45 ch_45 52.688 36 0.005 0.036itemfit(mod2, empirical.plot=2)
itemfit(mod2, empirical.plot=3)
itemfit(mod2, empirical.plot=10)
itemfit(mod2, empirical.plot=43)
Três parâmetros no mirt
mod3 <- mirt(score_ch2, model = 1, TOL = .001, itemtype='3PL')##
Iteration: 1, Log-Lik: -548888.737, Max-Change: 2.24987
Iteration: 2, Log-Lik: -542022.701, Max-Change: 0.37445
Iteration: 3, Log-Lik: -540288.285, Max-Change: 0.63814
Iteration: 4, Log-Lik: -539600.890, Max-Change: 0.63348
Iteration: 5, Log-Lik: -539129.773, Max-Change: 0.34078
Iteration: 6, Log-Lik: -538845.675, Max-Change: 0.23942
Iteration: 7, Log-Lik: -538673.133, Max-Change: 0.23156
Iteration: 8, Log-Lik: -538548.460, Max-Change: 0.24394
Iteration: 9, Log-Lik: -538459.848, Max-Change: 0.48172
Iteration: 10, Log-Lik: -538392.384, Max-Change: 0.49145
Iteration: 11, Log-Lik: -538342.093, Max-Change: 0.42178
Iteration: 12, Log-Lik: -538298.006, Max-Change: 0.43775
Iteration: 13, Log-Lik: -538264.313, Max-Change: 0.25606
Iteration: 14, Log-Lik: -538238.712, Max-Change: 0.11091
Iteration: 15, Log-Lik: -538220.699, Max-Change: 0.03588
Iteration: 16, Log-Lik: -538205.895, Max-Change: 0.02042
Iteration: 17, Log-Lik: -538193.813, Max-Change: 0.13368
Iteration: 18, Log-Lik: -538185.346, Max-Change: 0.01655
Iteration: 19, Log-Lik: -538178.117, Max-Change: 0.01369
Iteration: 20, Log-Lik: -538172.658, Max-Change: 0.01195
Iteration: 21, Log-Lik: -538168.442, Max-Change: 0.01041
Iteration: 22, Log-Lik: -538155.228, Max-Change: 0.00202
Iteration: 23, Log-Lik: -538155.025, Max-Change: 0.00176
Iteration: 24, Log-Lik: -538154.874, Max-Change: 0.00319
Iteration: 25, Log-Lik: -538154.671, Max-Change: 0.00135
Iteration: 26, Log-Lik: -538154.558, Max-Change: 0.00115
Iteration: 27, Log-Lik: -538154.497, Max-Change: 0.00096parms3 <- mirt(score_ch2, model = 1, TOL = .001, itemtype='3PL', pars = 'values')
summary(mod3)## F1 h2
## ch_1 0.650 0.42212
## ch_2 0.630 0.39750
## ch_3 0.753 0.56653
## ch_4 0.452 0.20407
## ch_5 0.750 0.56218
## ch_6 0.516 0.26608
## ch_7 0.764 0.58298
## ch_8 0.674 0.45405
## ch_9 0.387 0.14947
## ch_10 0.622 0.38695
## ch_11 0.227 0.05171
## ch_12 0.618 0.38247
## ch_13 0.810 0.65686
## ch_14 0.571 0.32598
## ch_15 0.737 0.54253
## ch_16 0.469 0.22026
## ch_17 0.838 0.70290
## ch_18 0.300 0.08974
## ch_19 0.684 0.46787
## ch_20 0.636 0.40457
## ch_21 0.329 0.10833
## ch_22 0.626 0.39166
## ch_23 0.604 0.36471
## ch_24 0.763 0.58151
## ch_25 0.398 0.15874
## ch_26 0.187 0.03484
## ch_27 0.686 0.47018
## ch_28 0.770 0.59337
## ch_29 0.574 0.32963
## ch_30 0.444 0.19679
## ch_31 0.588 0.34549
## ch_32 0.298 0.08871
## ch_33 0.198 0.03904
## ch_34 0.703 0.49455
## ch_35 0.686 0.47051
## ch_36 0.729 0.53195
## ch_37 0.580 0.33684
## ch_38 0.798 0.63760
## ch_39 0.634 0.40213
## ch_40 0.078 0.00609
## ch_41 0.557 0.30996
## ch_42 0.489 0.23920
## ch_43 0.626 0.39126
## ch_44 0.355 0.12600
## ch_45 0.249 0.06208
##
## SS loadings: 15.548
## Proportion Var: 0.346
##
## Factor correlations:
##
## F1
## F1 1coef(mod3 , simplify=TRUE, IRTpars=TRUE) %>% view
plot(mod3, type = 'trace', facet_items = FALSE)
itemfit(mod3)## item S_X2 df.S_X2 RMSEA.S_X2 p.S_X2
## 1 ch_1 77.434 34 0.008 0.000
## 2 ch_2 27.047 32 0.000 0.716
## 3 ch_3 21.712 32 0.000 0.915
## 4 ch_4 45.963 34 0.004 0.083
## 5 ch_5 31.112 32 0.000 0.511
## 6 ch_6 31.856 34 0.000 0.573
## 7 ch_7 29.630 34 0.000 0.682
## 8 ch_8 49.023 34 0.005 0.046
## 9 ch_9 101.000 33 0.010 0.000
## 10 ch_10 78.148 35 0.008 0.000
## 11 ch_11 89.585 36 0.009 0.000
## 12 ch_12 47.052 32 0.005 0.042
## 13 ch_13 32.713 31 0.002 0.383
## 14 ch_14 33.325 33 0.001 0.451
## 15 ch_15 40.452 33 0.003 0.174
## 16 ch_16 28.797 35 0.000 0.761
## 17 ch_17 49.843 32 0.005 0.023
## 18 ch_18 36.301 35 0.001 0.408
## 19 ch_19 52.566 33 0.005 0.017
## 20 ch_20 56.421 35 0.006 0.012
## 21 ch_21 110.158 34 0.011 0.000
## 22 ch_22 37.576 33 0.003 0.267
## 23 ch_23 50.447 35 0.005 0.044
## 24 ch_24 98.097 33 0.010 0.000
## 25 ch_25 52.150 34 0.005 0.024
## 26 ch_26 73.196 35 0.007 0.000
## 27 ch_27 44.324 32 0.004 0.072
## 28 ch_28 41.568 33 0.004 0.146
## 29 ch_29 74.283 32 0.008 0.000
## 30 ch_30 33.667 35 0.000 0.532
## 31 ch_31 29.275 35 0.000 0.740
## 32 ch_32 33.054 35 0.000 0.562
## 33 ch_33 85.083 36 0.008 0.000
## 34 ch_34 31.198 34 0.000 0.606
## 35 ch_35 77.874 34 0.008 0.000
## 36 ch_36 28.347 35 0.000 0.780
## 37 ch_37 34.158 35 0.000 0.509
## 38 ch_38 25.213 33 0.000 0.832
## 39 ch_39 81.892 33 0.009 0.000
## 40 ch_40 43.403 36 0.003 0.185
## 41 ch_41 49.886 34 0.005 0.039
## 42 ch_42 29.245 33 0.000 0.655
## 43 ch_43 23.748 34 0.000 0.905
## 44 ch_44 49.918 34 0.005 0.038
## 45 ch_45 40.961 36 0.003 0.262itemfit(mod3, empirical.plot=2)
itemfit(mod3, empirical.plot=3)
itemfit(mod3, empirical.plot=10)
itemfit(mod3, empirical.plot=43)
itemfit(mod3, empirical.plot=5)
itemfit(mod3, empirical.plot=3)
itemfit(mod3, empirical.plot=41)
Tentando achar os parâmetros “originais” dos itens
Especificando distribuições a priori para os parâmetros
ggplot(data.frame(x = c(-4, 4)), aes(x = x)) +
stat_function(fun = dnorm, args = list(mean = 0, sd=1))
ggplot(data.frame(x = c(-4, 4)), aes(x = x)) +
stat_function(fun = dlnorm, args = list(mean = 1, sd=.5))
- Calibrando na métrica do ENEM
m3pl <- mirt.model(
"th_mt = 1-45
PRIOR = (1-45, a1, lnorm, 1, 0.5),
(1-45, d, norm, 0, 1),
(1-45, g, expbeta, 5, 17)"
)
parms <- mirt(score_ch, model = m3pl, TOL = .001, itemtype='3PL', pars = 'values')
M <- (mean(enem_2015$NU_NOTA_CH, na.rm = TRUE) - 500) / 100
DP <- sd(enem_2015$NU_NOTA_CH, na.rm = TRUE) / 100
parms[parms$name == "MEAN_1", ]$value <- M
parms[parms$name == "COV_11", ]$value <- DP*DP
mt3pl <- mirt(score_ch, model = m3pl, TOL = .001, itemtype='3PL', pars = parms)##
Iteration: 1, Log-Lik: -3719645.969, Max-Change: 2.26058
Iteration: 2, Log-Lik: -3357646.727, Max-Change: 0.52547
Iteration: 3, Log-Lik: -3341389.363, Max-Change: 0.38019
Iteration: 4, Log-Lik: -3328209.419, Max-Change: 0.32477
Iteration: 5, Log-Lik: -3315969.988, Max-Change: 0.30902
Iteration: 6, Log-Lik: -3304496.156, Max-Change: 0.27972
Iteration: 7, Log-Lik: -3293927.924, Max-Change: 0.25937
Iteration: 8, Log-Lik: -3284279.578, Max-Change: 0.23380
Iteration: 9, Log-Lik: -3275549.690, Max-Change: 0.21748
Iteration: 10, Log-Lik: -3267728.779, Max-Change: 0.19829
Iteration: 11, Log-Lik: -3260789.229, Max-Change: 0.18224
Iteration: 12, Log-Lik: -3254676.579, Max-Change: 0.16686
Iteration: 13, Log-Lik: -3249349.203, Max-Change: 0.15315
Iteration: 14, Log-Lik: -3244747.841, Max-Change: 0.13965
Iteration: 15, Log-Lik: -3240802.522, Max-Change: 0.12672
Iteration: 16, Log-Lik: -3237446.445, Max-Change: 0.11501
Iteration: 17, Log-Lik: -3234611.559, Max-Change: 0.10838
Iteration: 18, Log-Lik: -3232233.050, Max-Change: 0.09520
Iteration: 19, Log-Lik: -3230250.346, Max-Change: 0.08400
Iteration: 20, Log-Lik: -3228614.142, Max-Change: 0.08170
Iteration: 21, Log-Lik: -3227264.576, Max-Change: 0.06845
Iteration: 22, Log-Lik: -3226167.667, Max-Change: 0.06453
Iteration: 23, Log-Lik: -3225278.118, Max-Change: 0.05677
Iteration: 24, Log-Lik: -3224558.843, Max-Change: 0.05109
Iteration: 25, Log-Lik: -3223981.656, Max-Change: 0.04596
Iteration: 26, Log-Lik: -3223519.415, Max-Change: 0.04737
Iteration: 27, Log-Lik: -3223151.393, Max-Change: 0.04445
Iteration: 28, Log-Lik: -3222859.647, Max-Change: 0.03927
Iteration: 29, Log-Lik: -3222629.092, Max-Change: 0.03356
Iteration: 30, Log-Lik: -3222448.864, Max-Change: 0.02679
Iteration: 31, Log-Lik: -3222305.810, Max-Change: 0.02267
Iteration: 32, Log-Lik: -3222194.348, Max-Change: 0.01431
Iteration: 33, Log-Lik: -3222107.755, Max-Change: 0.01237
Iteration: 34, Log-Lik: -3222040.288, Max-Change: 0.01079
Iteration: 35, Log-Lik: -3221987.549, Max-Change: 0.01906
Iteration: 36, Log-Lik: -3221946.327, Max-Change: 0.01700
Iteration: 37, Log-Lik: -3221914.213, Max-Change: 0.00739
Iteration: 38, Log-Lik: -3221889.688, Max-Change: 0.00647
Iteration: 39, Log-Lik: -3221870.841, Max-Change: 0.00572
Iteration: 40, Log-Lik: -3221856.191, Max-Change: 0.00502
Iteration: 41, Log-Lik: -3221844.905, Max-Change: 0.00439
Iteration: 42, Log-Lik: -3221836.195, Max-Change: 0.00382
Iteration: 43, Log-Lik: -3221829.502, Max-Change: 0.00336
Iteration: 44, Log-Lik: -3221824.332, Max-Change: 0.00301
Iteration: 45, Log-Lik: -3221820.337, Max-Change: 0.00269
Iteration: 46, Log-Lik: -3221807.699, Max-Change: 0.00112
Iteration: 47, Log-Lik: -3221807.468, Max-Change: 0.00110
Iteration: 48, Log-Lik: -3221807.285, Max-Change: 0.00103
Iteration: 49, Log-Lik: -3221806.676, Max-Change: 0.01712
Iteration: 50, Log-Lik: -3221806.305, Max-Change: 0.03465
Iteration: 51, Log-Lik: -3221805.918, Max-Change: 0.00936
Iteration: 52, Log-Lik: -3221805.874, Max-Change: 0.06386
Iteration: 53, Log-Lik: -3221804.817, Max-Change: 0.00000summary(mt3pl)## th_mt h2
## ch_1 0.523 0.2736
## ch_2 0.522 0.2725
## ch_3 0.600 0.3595
## ch_4 0.413 0.1703
## ch_5 0.603 0.3632
## ch_6 0.454 0.2060
## ch_7 0.605 0.3657
## ch_8 0.564 0.3176
## ch_9 0.381 0.1450
## ch_10 0.529 0.2795
## ch_11 0.220 0.0483
## ch_12 0.538 0.2889
## ch_13 0.624 0.3898
## ch_14 0.496 0.2459
## ch_15 0.581 0.3377
## ch_16 0.417 0.1736
## ch_17 0.617 0.3809
## ch_18 0.307 0.0944
## ch_19 0.553 0.3053
## ch_20 0.471 0.2220
## ch_21 0.321 0.1030
## ch_22 0.518 0.2680
## ch_23 0.499 0.2485
## ch_24 0.599 0.3588
## ch_25 0.399 0.1590
## ch_26 0.266 0.0707
## ch_27 0.566 0.3201
## ch_28 0.608 0.3701
## ch_29 0.498 0.2480
## ch_30 0.411 0.1692
## ch_31 0.463 0.2144
## ch_32 0.304 0.0926
## ch_33 0.215 0.0462
## ch_34 0.553 0.3053
## ch_35 0.555 0.3084
## ch_36 0.591 0.3493
## ch_37 0.482 0.2320
## ch_38 0.626 0.3915
## ch_39 0.535 0.2866
## ch_40 0.137 0.0187
## ch_41 0.498 0.2483
## ch_42 0.448 0.2006
## ch_43 0.547 0.2994
## ch_44 0.332 0.1105
## ch_45 0.259 0.0672
##
## SS loadings: 10.726
## Proportion Var: 0.238
##
## Factor correlations:
##
## th_mt
## th_mt 1coef(mt3pl , simplify=TRUE, IRTpars=TRUE) %>% view
plot(mt3pl, type = 'trace', facet_items = FALSE)
dev.new()
itemfit(mt3pl, empirical.plot=2)
itemfit(mt3pl, empirical.plot=3)
itemfit(mt3pl, empirical.plot=10)
itemfit(mt3pl, empirical.plot=43)
eap_mt = fscores(mt3pl, method = "EAP")
names(enem_2015)## [1] "NU_INSCRICAO" "NU_ANO"
## [3] "CO_MUNICIPIO_RESIDENCIA" "NO_MUNICIPIO_RESIDENCIA"
## [5] "CO_UF_RESIDENCIA" "SG_UF_RESIDENCIA"
## [7] "IN_ESTUDA_CLASSE_HOSPITALAR" "IN_TREINEIRO"
## [9] "CO_ESCOLA" "CO_MUNICIPIO_ESC"
## [11] "NO_MUNICIPIO_ESC" "CO_UF_ESC"
## [13] "SG_UF_ESC" "TP_DEPENDENCIA_ADM_ESC"
## [15] "TP_LOCALIZACAO_ESC" "TP_SIT_FUNC_ESC"
## [17] "NU_IDADE" "TP_SEXO"
## [19] "TP_NACIONALIDADE" "CO_MUNICIPIO_NASCIMENTO"
## [21] "NO_MUNICIPIO_NASCIMENTO" "CO_UF_NASCIMENTO"
## [23] "SG_UF_NASCIMENTO" "TP_ST_CONCLUSAO"
## [25] "TP_ANO_CONCLUIU" "TP_ESCOLA"
## [27] "TP_ENSINO" "TP_ESTADO_CIVIL"
## [29] "TP_COR_RACA" "IN_BAIXA_VISAO"
## [31] "IN_CEGUEIRA" "IN_SURDEZ"
## [33] "IN_DEFICIENCIA_AUDITIVA" "IN_SURDO_CEGUEIRA"
## [35] "IN_DEFICIENCIA_FISICA" "IN_DEFICIENCIA_MENTAL"
## [37] "IN_DEFICIT_ATENCAO" "IN_DISLEXIA"
## [39] "IN_GESTANTE" "IN_LACTANTE"
## [41] "IN_IDOSO" "IN_DISCALCULIA"
## [43] "IN_AUTISMO" "IN_VISAO_MONOCULAR"
## [45] "IN_SABATISTA" "IN_OUTRA_DEF"
## [47] "IN_SEM_RECURSO" "IN_NOME_SOCIAL"
## [49] "IN_BRAILLE" "IN_AMPLIADA_24"
## [51] "IN_AMPLIADA_18" "IN_LEDOR"
## [53] "IN_ACESSO" "IN_TRANSCRICAO"
## [55] "IN_LIBRAS" "IN_LEITURA_LABIAL"
## [57] "IN_MESA_CADEIRA_RODAS" "IN_MESA_CADEIRA_SEPARADA"
## [59] "IN_APOIO_PERNA" "IN_GUIA_INTERPRETE"
## [61] "IN_MACA" "IN_COMPUTADOR"
## [63] "IN_CADEIRA_ESPECIAL" "IN_CADEIRA_CANHOTO"
## [65] "IN_CADEIRA_ACOLCHOADA" "IN_PROVA_DEITADO"
## [67] "IN_MOBILIARIO_OBESO" "IN_LAMINA_OVERLAY"
## [69] "IN_PROTETOR_AURICULAR" "IN_MEDIDOR_GLICOSE"
## [71] "IN_MAQUINA_BRAILE" "IN_SOROBAN"
## [73] "IN_MARCA_PASSO" "IN_SONDA"
## [75] "IN_MEDICAMENTOS" "IN_SALA_INDIVIDUAL"
## [77] "IN_SALA_ESPECIAL" "IN_SALA_ACOMPANHANTE"
## [79] "IN_MOBILIARIO_ESPECIFICO" "IN_MATERIAL_ESPECIFICO"
## [81] "IN_CERTIFICADO" "NO_ENTIDADE_CERTIFICACAO"
## [83] "CO_UF_ENTIDADE_CERTIFICACAO" "SG_UF_ENTIDADE_CERTIFICACAO"
## [85] "CO_MUNICIPIO_PROVA" "NO_MUNICIPIO_PROVA"
## [87] "CO_UF_PROVA" "SG_UF_PROVA"
## [89] "TP_PRESENCA_CN" "TP_PRESENCA_CH"
## [91] "TP_PRESENCA_LC" "TP_PRESENCA_MT"
## [93] "CO_PROVA_CN" "CO_PROVA_CH"
## [95] "CO_PROVA_LC" "CO_PROVA_MT"
## [97] "NU_NOTA_CN" "NU_NOTA_CH"
## [99] "NU_NOTA_LC" "NU_NOTA_MT"
## [101] "TX_RESPOSTAS_CN" "TX_RESPOSTAS_CH"
## [103] "TX_RESPOSTAS_LC" "TX_RESPOSTAS_MT"
## [105] "TP_LINGUA" "TX_GABARITO_CN"
## [107] "TX_GABARITO_CH" "TX_GABARITO_LC"
## [109] "TX_GABARITO_MT" "TP_STATUS_REDACAO"
## [111] "NU_NOTA_COMP1" "NU_NOTA_COMP2"
## [113] "NU_NOTA_COMP3" "NU_NOTA_COMP4"
## [115] "NU_NOTA_COMP5" "NU_NOTA_REDACAO"
## [117] "Q001" "Q002"
## [119] "Q003" "Q004"
## [121] "Q005" "Q006"
## [123] "Q007" "Q008"
## [125] "Q009" "Q010"
## [127] "Q011" "Q012"
## [129] "Q013" "Q014"
## [131] "Q015" "Q016"
## [133] "Q017" "Q018"
## [135] "Q019" "Q020"
## [137] "Q021" "Q022"
## [139] "Q023" "Q024"
## [141] "Q025" "Q026"
## [143] "Q027" "Q028"
## [145] "Q029" "Q030"
## [147] "Q031" "Q032"
## [149] "Q033" "Q034"
## [151] "Q035" "Q036"
## [153] "Q037" "Q038"
## [155] "Q039" "Q040"
## [157] "Q041" "Q042"
## [159] "Q043" "Q044"
## [161] "Q045" "Q046"
## [163] "Q047" "Q048"
## [165] "Q049" "Q050"
## [167] "totCH" "NU_NOTA_CHz"
## [169] "theta_ch1" "theta_ch2"
## [171] "theta_ch3" "theta_ch4"df <- cbind(
NU_NOTA_CH = enem_2015$NU_NOTA_CH,
eap_mt = fscores(mt3pl, method = "EAP")[, 1],
tot = apply(score_ch, MARGIN = 1, sum, na.rm =TRUE)
)
corr.test(df)## Call:corr.test(x = df)
## Correlation matrix
## NU_NOTA_CH eap_mt tot
## NU_NOTA_CH 1.00 0.98 0.94
## eap_mt 0.98 1.00 0.97
## tot 0.94 0.97 1.00
## Sample Size
## [1] 119827
## Probability values (Entries above the diagonal are adjusted for multiple tests.)
## NU_NOTA_CH eap_mt tot
## NU_NOTA_CH 0 0 0
## eap_mt 0 0 0
## tot 0 0 0
##
## To see confidence intervals of the correlations, print with the short=FALSE optiondf %>% as.data.frame %>%
mutate(
eap_mt = (eap_mt*100) + 500
) %>%
ggplot(aes(y=NU_NOTA_CH, x=eap_mt, colour = tot)) +
geom_point(alpha = 1/8) +
scale_x_continuous(breaks=seq(200, 1000, 50), limits = c(200, 1000)) +
scale_y_continuous(breaks=seq(200, 1000, 50), limits = c(200, 1000))
frq(df[, 3])##
## x <numeric>
## # total N=119827 valid N=119827 mean=19.06 sd=6.67
##
## Value | N | Raw % | Valid % | Cum. %
## ---------------------------------------
## 0 | 16 | 0.01 | 0.01 | 0.01
## 1 | 5 | 0.00 | 0.00 | 0.02
## 2 | 5 | 0.00 | 0.00 | 0.02
## 3 | 28 | 0.02 | 0.02 | 0.05
## 4 | 73 | 0.06 | 0.06 | 0.11
## 5 | 199 | 0.17 | 0.17 | 0.27
## 6 | 447 | 0.37 | 0.37 | 0.65
## 7 | 876 | 0.73 | 0.73 | 1.38
## 8 | 1557 | 1.30 | 1.30 | 2.68
## 9 | 2361 | 1.97 | 1.97 | 4.65
## 10 | 3379 | 2.82 | 2.82 | 7.47
## 11 | 4452 | 3.72 | 3.72 | 11.18
## 12 | 5565 | 4.64 | 4.64 | 15.83
## 13 | 6383 | 5.33 | 5.33 | 21.15
## 14 | 7080 | 5.91 | 5.91 | 27.06
## 15 | 7453 | 6.22 | 6.22 | 33.28
## 16 | 7643 | 6.38 | 6.38 | 39.66
## 17 | 7651 | 6.39 | 6.39 | 46.04
## 18 | 7290 | 6.08 | 6.08 | 52.13
## 19 | 6876 | 5.74 | 5.74 | 57.87
## 20 | 6253 | 5.22 | 5.22 | 63.08
## 21 | 5832 | 4.87 | 4.87 | 67.95
## 22 | 5247 | 4.38 | 4.38 | 72.33
## 23 | 4559 | 3.80 | 3.80 | 76.13
## 24 | 4122 | 3.44 | 3.44 | 79.57
## 25 | 3842 | 3.21 | 3.21 | 82.78
## 26 | 3272 | 2.73 | 2.73 | 85.51
## 27 | 2877 | 2.40 | 2.40 | 87.91
## 28 | 2471 | 2.06 | 2.06 | 89.97
## 29 | 2236 | 1.87 | 1.87 | 91.84
## 30 | 1923 | 1.60 | 1.60 | 93.45
## 31 | 1684 | 1.41 | 1.41 | 94.85
## 32 | 1390 | 1.16 | 1.16 | 96.01
## 33 | 1145 | 0.96 | 0.96 | 96.97
## 34 | 947 | 0.79 | 0.79 | 97.76
## 35 | 811 | 0.68 | 0.68 | 98.43
## 36 | 621 | 0.52 | 0.52 | 98.95
## 37 | 525 | 0.44 | 0.44 | 99.39
## 38 | 298 | 0.25 | 0.25 | 99.64
## 39 | 179 | 0.15 | 0.15 | 99.79
## 40 | 148 | 0.12 | 0.12 | 99.91
## 41 | 68 | 0.06 | 0.06 | 99.97
## 42 | 32 | 0.03 | 0.03 | 99.99
## 43 | 6 | 0.01 | 0.01 | 100.00
## <NA> | 0 | 0.00 | <NA> | <NA>