Reading the Data
library(foreign)
library(reshape)
library(reshape2)
##
## Attaching package: 'reshape2'
## The following objects are masked from 'package:reshape':
##
## colsplit, melt, recast
library(lme4)
## Loading required package: Matrix
##
## Attaching package: 'Matrix'
## The following object is masked from 'package:reshape':
##
## expand
library(sjstats)
library(rockchalk)
library(lattice)
library(ggplot2)
library(psych)
##
## Attaching package: 'psych'
## The following objects are masked from 'package:ggplot2':
##
## %+%, alpha
## The following objects are masked from 'package:sjstats':
##
## pca, phi
setwd("/Users/yahyaalshehri/Desktop/SAudi TIMSS")
###sss<- read.spss("asgsaum652.sav", to.data.frame = TRUE)
dtfile <- read.csv("TIMSS.csv")[,c("IDSCHOOL", "IDBOOK", "ITSEX","ASBM01A", "ASBM01B", "ASBM01C", "ASBM01D","ASBM01E",
"ASBM01F", "ASBM01G", "ASBM01H","ASBM01I","ASMMAT03")]
head(dtfile)
## IDSCHOOL IDBOOK ITSEX ASBM01A ASBM01B ASBM01C ASBM01D ASBM01E ASBM01F
## 1 1 9 1 1 4 4 2 2 2
## 2 1 10 1 1 4 4 2 2 2
## 3 1 11 1 1 4 4 2 2 2
## 4 1 12 1 1 4 4 2 2 2
## 5 1 13 1 2 4 4 2 2 2
## 6 1 14 1 1 4 4 2 2 2
## ASBM01G ASBM01H ASBM01I ASMMAT03
## 1 2 2 3 374.9874
## 2 2 1 2 541.6871
## 3 2 1 1 427.7202
## 4 2 2 1 525.5990
## 5 2 2 2 452.4498
## 6 NA 2 1 539.5486
colnames(dtfile)
## [1] "IDSCHOOL" "IDBOOK" "ITSEX" "ASBM01A" "ASBM01B" "ASBM01C"
## [7] "ASBM01D" "ASBM01E" "ASBM01F" "ASBM01G" "ASBM01H" "ASBM01I"
## [13] "ASMMAT03"
dtfile$IDSCHOOL <- as.factor(dtfile$IDSCHOOL)
dtfile$IDBOOK <- as.factor(dtfile$IDBOOK)
dtfile$Gender <- factor(dtfile$ITSEX)
dtfile$Gender <- factor(dtfile$ITSEX, levels = c(2,1), labels= c ("Male", "Female"))
with(dtfile, table(Gender, ITSEX))
## ITSEX
## Gender 1 2
## Male 0 2156
## Female 2181 0
Summarize the Data
rockchalk::summarize(dtfile)
## Numeric variables
## ITSEX ASBM01A ASBM01B ASBM01C ASBM01D ASBM01E
## min 1 1 1 1 1 1
## med 1 1 4 4 1 1
## max 2 9 9 9 9 9
## mean 1.50 1.68 3.37 3.49 2 2
## sd 0.50 1.59 1.85 1.93 2.12 2.09
## skewness 0.01 3.32 1.18 1.22 2.55 2.54
## kurtosis -2 11.80 2.59 2.29 5.52 5.60
## nobs 4337 4225 4236 4242 4252 4263
## nmissing 0 112 101 95 85 74
## ASBM01F ASBM01G ASBM01H ASBM01I ASMMAT03
## min 1 1 1 1 40.78
## med 1 1 1 1 384.41
## max 9 9 9 9 722.22
## mean 2.05 2.04 2.14 2.13 384.26
## sd 2.08 2.08 2.11 2.02 90.28
## skewness 2.55 2.53 2.36 2.35 -0.03
## kurtosis 5.68 5.62 4.85 5.18 -0.12
## nobs 4268 4269 4269 4282 4337
## nmissing 69 68 68 55 0
##
## Nonnumeric variables
## IDSCHOOL IDBOOK Gender
## 116 : 44 3 : 324 Female: 2181
## 84 : 43 9 : 321 Male : 2156
## 11 : 40 4 : 318 nobs : 4337
## 183 : 40 1 : 314 nmiss : 0
## (All Others): 4170 (All Others): 3060 entropy : 1
## nobs : 4337 nobs : 4337 normedEntropy: 1
## nmiss : 0 nmiss : 0
## entropy : 7.48 entropy : 3.8
## normedEntropy: 0.99 normedEntropy: 1.0
summary(dtfile [,-c(1,2,3)])
## ASBM01A ASBM01B ASBM01C ASBM01D
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:1.000
## Median :1.000 Median :4.000 Median :4.000 Median :1.000
## Mean :1.684 Mean :3.371 Mean :3.494 Mean :2.001
## 3rd Qu.:2.000 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:2.000
## Max. :9.000 Max. :9.000 Max. :9.000 Max. :9.000
## NA's :112 NA's :101 NA's :95 NA's :85
## ASBM01E ASBM01F ASBM01G ASBM01H
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000
## Median :1.000 Median :1.000 Median :1.000 Median :1.000
## Mean :2.004 Mean :2.048 Mean :2.037 Mean :2.142
## 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :9.000 Max. :9.000 Max. :9.000 Max. :9.000
## NA's :74 NA's :69 NA's :68 NA's :68
## ASBM01I ASMMAT03 Gender
## Min. :1.000 Min. : 40.78 Male :2156
## 1st Qu.:1.000 1st Qu.:323.09 Female:2181
## Median :1.000 Median :384.41
## Mean :2.133 Mean :384.26
## 3rd Qu.:3.000 3rd Qu.:446.29
## Max. :9.000 Max. :722.22
## NA's :55
describe(dtfile [,-c(1,2,3)])
## vars n mean sd median trimmed mad min max range
## ASBM01A 1 4225 1.68 1.59 1.00 1.28 0.00 1.00 9.00 8.00
## ASBM01B 2 4236 3.37 1.85 4.00 3.23 0.00 1.00 9.00 8.00
## ASBM01C 3 4242 3.49 1.93 4.00 3.29 0.00 1.00 9.00 8.00
## ASBM01D 4 4252 2.00 2.12 1.00 1.43 0.00 1.00 9.00 8.00
## ASBM01E 5 4263 2.00 2.09 1.00 1.45 0.00 1.00 9.00 8.00
## ASBM01F 6 4268 2.05 2.08 1.00 1.51 0.00 1.00 9.00 8.00
## ASBM01G 7 4269 2.04 2.08 1.00 1.50 0.00 1.00 9.00 8.00
## ASBM01H 8 4269 2.14 2.11 1.00 1.62 0.00 1.00 9.00 8.00
## ASBM01I 9 4282 2.13 2.02 1.00 1.67 0.00 1.00 9.00 8.00
## ASMMAT03 10 4337 384.26 90.28 384.41 384.30 91.31 40.78 722.22 681.44
## Gender* 11 4337 1.50 0.50 2.00 1.50 0.00 1.00 2.00 1.00
## skew kurtosis se
## ASBM01A 3.32 11.80 0.02
## ASBM01B 1.18 2.59 0.03
## ASBM01C 1.22 2.29 0.03
## ASBM01D 2.55 5.52 0.03
## ASBM01E 2.54 5.60 0.03
## ASBM01F 2.55 5.68 0.03
## ASBM01G 2.53 5.62 0.03
## ASBM01H 2.36 4.85 0.03
## ASBM01I 2.35 5.18 0.03
## ASMMAT03 -0.03 -0.12 1.37
## Gender* -0.01 -2.00 0.01
Ploting the Variables
hist(dtfile$ASBM01A)
hist(dtfile$ASBM01B)
hist(dtfile$ASBM01C)
hist(dtfile$ASBM01D)
hist(dtfile$ASBM01E)
hist(dtfile$ASBM01F)
hist(dtfile$ASBM01G)
hist(dtfile$ASBM01H)
hist(dtfile$ASBM01I)
hist(dtfile$ASMMAT03)
Multiple REgression Model
Regression_Model <- lm(ASMMAT03 ~ Gender + IDSCHOOL+ ASBM01A
+ ASBM01B + ASBM01C + ASBM01D + ASBM01E + ASBM01F
+ ASBM01G + ASBM01H + ASBM01I , data = dtfile)
summary(Regression_Model)
##
## Call:
## lm(formula = ASMMAT03 ~ Gender + IDSCHOOL + ASBM01A + ASBM01B +
## ASBM01C + ASBM01D + ASBM01E + ASBM01F + ASBM01G + ASBM01H +
## ASBM01I, data = dtfile)
##
## Residuals:
## Min 1Q Median 3Q Max
## -254.430 -45.244 -0.145 46.625 255.655
##
## Coefficients: (1 not defined because of singularities)
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 562.7595 26.3226 21.379 < 2e-16 ***
## GenderFemale -80.8641 29.7901 -2.714 0.006668 **
## IDSCHOOL2 -152.6410 31.7796 -4.803 1.62e-06 ***
## IDSCHOOL3 -239.2549 35.8911 -6.666 3.00e-11 ***
## IDSCHOOL4 -153.2201 38.5798 -3.972 7.27e-05 ***
## IDSCHOOL5 -144.7972 35.9285 -4.030 5.68e-05 ***
## IDSCHOOL6 -320.0644 33.5421 -9.542 < 2e-16 ***
## IDSCHOOL7 -1.1648 20.3316 -0.057 0.954318
## IDSCHOOL8 -83.3419 20.4830 -4.069 4.82e-05 ***
## IDSCHOOL9 -7.4968 20.2829 -0.370 0.711692
## IDSCHOOL10 -190.1840 29.5543 -6.435 1.39e-10 ***
## IDSCHOOL11 -224.4101 28.7439 -7.807 7.50e-15 ***
## IDSCHOOL12 -212.3076 29.6527 -7.160 9.65e-13 ***
## IDSCHOOL13 -192.7788 30.0977 -6.405 1.69e-10 ***
## IDSCHOOL14 24.4415 27.1195 0.901 0.367511
## IDSCHOOL15 -273.1820 32.1227 -8.504 < 2e-16 ***
## IDSCHOOL16 -111.3815 21.6471 -5.145 2.81e-07 ***
## IDSCHOOL17 -62.4803 20.2514 -3.085 0.002048 **
## IDSCHOOL18 -222.8851 31.7993 -7.009 2.82e-12 ***
## IDSCHOOL19 -82.6938 20.0326 -4.128 3.74e-05 ***
## IDSCHOOL20 -115.7667 19.1491 -6.046 1.63e-09 ***
## IDSCHOOL21 -91.8136 19.6503 -4.672 3.08e-06 ***
## IDSCHOOL22 -161.4220 19.1666 -8.422 < 2e-16 ***
## IDSCHOOL23 -26.9157 19.6415 -1.370 0.170658
## IDSCHOOL24 -248.9520 34.9701 -7.119 1.29e-12 ***
## IDSCHOOL25 -269.8955 30.9045 -8.733 < 2e-16 ***
## IDSCHOOL26 -231.0698 29.9749 -7.709 1.61e-14 ***
## IDSCHOOL27 -228.1660 29.0260 -7.861 4.93e-15 ***
## IDSCHOOL28 -171.5002 29.0254 -5.909 3.75e-09 ***
## IDSCHOOL29 -197.6484 29.1348 -6.784 1.35e-11 ***
## IDSCHOOL30 -75.3418 31.7472 -2.373 0.017685 *
## IDSCHOOL31 -13.0635 21.3107 -0.613 0.539912
## IDSCHOOL32 -216.1971 33.5411 -6.446 1.29e-10 ***
## IDSCHOOL33 -214.2032 30.9207 -6.928 5.01e-12 ***
## IDSCHOOL34 -166.6058 31.9037 -5.222 1.86e-07 ***
## IDSCHOOL35 -199.4504 30.7316 -6.490 9.68e-11 ***
## IDSCHOOL36 -36.5725 29.6700 -1.233 0.217785
## IDSCHOOL37 -153.5790 21.6620 -7.090 1.59e-12 ***
## IDSCHOOL38 -122.3763 20.2528 -6.042 1.66e-09 ***
## IDSCHOOL39 -102.8905 19.4655 -5.286 1.32e-07 ***
## IDSCHOOL40 -241.9232 29.1288 -8.305 < 2e-16 ***
## IDSCHOOL41 -170.1083 29.5430 -5.758 9.18e-09 ***
## IDSCHOOL42 -218.8778 29.5348 -7.411 1.54e-13 ***
## IDSCHOOL43 -101.5877 18.1954 -5.583 2.53e-08 ***
## IDSCHOOL44 -110.5227 21.6365 -5.108 3.41e-07 ***
## IDSCHOOL45 -48.9798 20.2640 -2.417 0.015692 *
## IDSCHOOL46 -167.1365 21.0112 -7.955 2.35e-15 ***
## IDSCHOOL47 -24.9385 20.4864 -1.217 0.223558
## IDSCHOOL48 -58.8125 23.3293 -2.521 0.011743 *
## IDSCHOOL49 -69.0061 27.1505 -2.542 0.011073 *
## IDSCHOOL50 -119.2751 20.4804 -5.824 6.23e-09 ***
## IDSCHOOL51 -60.3752 19.8380 -3.043 0.002355 **
## IDSCHOOL52 -91.0184 18.6191 -4.888 1.06e-06 ***
## IDSCHOOL53 -92.6960 18.6255 -4.977 6.75e-07 ***
## IDSCHOOL54 -91.2491 20.1220 -4.535 5.94e-06 ***
## IDSCHOOL55 -178.4365 29.9609 -5.956 2.82e-09 ***
## IDSCHOOL56 -75.2859 31.1678 -2.416 0.015760 *
## IDSCHOOL57 -212.7497 29.0456 -7.325 2.91e-13 ***
## IDSCHOOL58 -244.1387 30.6738 -7.959 2.27e-15 ***
## IDSCHOOL59 -179.8983 29.7873 -6.039 1.69e-09 ***
## IDSCHOOL60 -80.8264 27.1439 -2.978 0.002922 **
## IDSCHOOL61 -212.1523 31.1541 -6.810 1.13e-11 ***
## IDSCHOOL62 -224.3607 32.5389 -6.895 6.27e-12 ***
## IDSCHOOL63 -178.3692 30.4673 -5.854 5.19e-09 ***
## IDSCHOOL64 -77.7178 19.3615 -4.014 6.08e-05 ***
## IDSCHOOL65 -85.7908 20.7642 -4.132 3.68e-05 ***
## IDSCHOOL66 -157.7202 18.8879 -8.350 < 2e-16 ***
## IDSCHOOL67 -187.3668 20.0528 -9.344 < 2e-16 ***
## IDSCHOOL68 -97.6625 30.2934 -3.224 0.001275 **
## IDSCHOOL69 -237.6441 32.1228 -7.398 1.69e-13 ***
## IDSCHOOL70 -189.3653 31.4294 -6.025 1.85e-09 ***
## IDSCHOOL71 -213.3353 32.0990 -6.646 3.44e-11 ***
## IDSCHOOL72 -237.6141 30.9795 -7.670 2.17e-14 ***
## IDSCHOOL73 -103.5832 18.7389 -5.528 3.46e-08 ***
## IDSCHOOL74 -180.4002 31.8181 -5.670 1.54e-08 ***
## IDSCHOOL75 -128.7442 31.1411 -4.134 3.64e-05 ***
## IDSCHOOL76 -195.8587 29.6587 -6.604 4.56e-11 ***
## IDSCHOOL77 -167.9382 30.9331 -5.429 6.02e-08 ***
## IDSCHOOL78 -218.3677 31.4311 -6.947 4.35e-12 ***
## IDSCHOOL79 -121.1916 18.5088 -6.548 6.62e-11 ***
## IDSCHOOL80 -27.3603 28.3310 -0.966 0.334236
## IDSCHOOL81 -33.2937 20.7487 -1.605 0.108662
## IDSCHOOL82 -144.6910 21.6332 -6.688 2.59e-11 ***
## IDSCHOOL83 -94.8394 19.6518 -4.826 1.45e-06 ***
## IDSCHOOL84 -107.9912 17.8779 -6.040 1.68e-09 ***
## IDSCHOOL85 -232.7968 29.7905 -7.814 7.09e-15 ***
## IDSCHOOL86 -89.0222 30.2629 -2.942 0.003285 **
## IDSCHOOL87 -295.9578 29.6661 -9.976 < 2e-16 ***
## IDSCHOOL88 -242.6931 29.1240 -8.333 < 2e-16 ***
## IDSCHOOL89 -297.3691 30.5360 -9.738 < 2e-16 ***
## IDSCHOOL90 -99.4294 20.0527 -4.958 7.42e-07 ***
## IDSCHOOL91 -41.3087 19.6548 -2.102 0.035644 *
## IDSCHOOL92 -103.4714 19.6468 -5.267 1.47e-07 ***
## IDSCHOOL93 -83.8805 21.6472 -3.875 0.000108 ***
## IDSCHOOL94 -90.8921 18.8623 -4.819 1.50e-06 ***
## IDSCHOOL95 -255.7439 30.9057 -8.275 < 2e-16 ***
## IDSCHOOL96 -109.4082 18.5100 -5.911 3.70e-09 ***
## IDSCHOOL97 -134.5168 20.4839 -6.567 5.83e-11 ***
## IDSCHOOL98 -49.5825 18.6027 -2.665 0.007723 **
## IDSCHOOL99 -161.4493 19.4639 -8.295 < 2e-16 ***
## IDSCHOOL100 -39.5154 20.2618 -1.950 0.051221 .
## IDSCHOOL101 -265.6481 29.9325 -8.875 < 2e-16 ***
## IDSCHOOL102 -150.6188 30.9006 -4.874 1.14e-06 ***
## IDSCHOOL103 -201.2527 31.4335 -6.402 1.71e-10 ***
## IDSCHOOL104 -157.9063 29.9329 -5.275 1.40e-07 ***
## IDSCHOOL105 -111.2279 20.7386 -5.363 8.66e-08 ***
## IDSCHOOL106 -63.1663 20.7471 -3.045 0.002346 **
## IDSCHOOL107 -41.3020 20.0431 -2.061 0.039403 *
## IDSCHOOL108 -183.8571 21.6407 -8.496 < 2e-16 ***
## IDSCHOOL109 -99.8319 25.2678 -3.951 7.93e-05 ***
## IDSCHOOL110 -141.4913 21.6517 -6.535 7.21e-11 ***
## IDSCHOOL111 -72.5036 21.0144 -3.450 0.000566 ***
## IDSCHOOL112 -205.8807 31.4537 -6.546 6.72e-11 ***
## IDSCHOOL113 -184.3107 32.5234 -5.667 1.56e-08 ***
## IDSCHOOL114 -254.6444 29.8245 -8.538 < 2e-16 ***
## IDSCHOOL115 -235.8904 29.2068 -8.077 8.85e-16 ***
## IDSCHOOL116 -246.9488 28.4170 -8.690 < 2e-16 ***
## IDSCHOOL117 -279.2137 30.9313 -9.027 < 2e-16 ***
## IDSCHOOL118 -222.8378 29.3208 -7.600 3.71e-14 ***
## IDSCHOOL119 -206.2847 31.4849 -6.552 6.44e-11 ***
## IDSCHOOL120 -205.8994 30.2886 -6.798 1.23e-11 ***
## IDSCHOOL121 -206.3966 43.4907 -4.746 2.15e-06 ***
## IDSCHOOL122 -47.7691 19.4745 -2.453 0.014215 *
## IDSCHOOL123 -42.0809 24.5502 -1.714 0.086596 .
## IDSCHOOL124 -180.2553 32.5117 -5.544 3.15e-08 ***
## IDSCHOOL125 36.6256 26.2351 1.396 0.162781
## IDSCHOOL126 -166.8919 30.6709 -5.441 5.62e-08 ***
## IDSCHOOL127 -142.1368 30.6830 -4.632 3.73e-06 ***
## IDSCHOOL128 -204.4069 30.2871 -6.749 1.71e-11 ***
## IDSCHOOL129 -20.4478 31.4406 -0.650 0.515497
## IDSCHOOL130 -85.9765 20.2651 -4.243 2.26e-05 ***
## IDSCHOOL131 -244.9237 30.7311 -7.970 2.08e-15 ***
## IDSCHOOL132 -131.6692 30.1035 -4.374 1.25e-05 ***
## IDSCHOOL133 -27.4551 29.5752 -0.928 0.353303
## IDSCHOOL134 -230.1703 29.3145 -7.852 5.29e-15 ***
## IDSCHOOL135 -266.9920 29.5617 -9.032 < 2e-16 ***
## IDSCHOOL136 -46.9328 19.0032 -2.470 0.013565 *
## IDSCHOOL137 -178.4686 20.0394 -8.906 < 2e-16 ***
## IDSCHOOL138 -82.4303 18.5040 -4.455 8.64e-06 ***
## IDSCHOOL139 -61.6431 18.7374 -3.290 0.001012 **
## IDSCHOOL140 -133.7644 31.1460 -4.295 1.79e-05 ***
## IDSCHOOL141 -34.3658 20.2764 -1.695 0.090182 .
## IDSCHOOL142 -83.0082 19.4607 -4.265 2.04e-05 ***
## IDSCHOOL143 5.3867 18.7482 0.287 0.773885
## IDSCHOOL144 -91.4986 21.0176 -4.353 1.38e-05 ***
## IDSCHOOL145 -321.8597 30.4167 -10.582 < 2e-16 ***
## IDSCHOOL146 -252.0456 33.5379 -7.515 7.04e-14 ***
## IDSCHOOL147 -156.4201 31.4454 -4.974 6.84e-07 ***
## IDSCHOOL148 -161.4533 30.9026 -5.225 1.84e-07 ***
## IDSCHOOL149 -67.3991 19.8438 -3.396 0.000690 ***
## IDSCHOOL150 -101.2185 21.6670 -4.672 3.09e-06 ***
## IDSCHOOL151 -96.3190 21.0207 -4.582 4.75e-06 ***
## IDSCHOOL152 -161.9275 30.4564 -5.317 1.12e-07 ***
## IDSCHOOL153 -204.9136 34.1972 -5.992 2.26e-09 ***
## IDSCHOOL154 -229.6931 31.1509 -7.374 2.03e-13 ***
## IDSCHOOL155 7.0913 29.8021 0.238 0.811936
## IDSCHOOL156 -77.0973 27.1307 -2.842 0.004511 **
## IDSCHOOL157 -29.1180 23.3547 -1.247 0.212559
## IDSCHOOL158 -152.7382 18.6626 -8.184 3.70e-16 ***
## IDSCHOOL159 -57.6475 19.4803 -2.959 0.003103 **
## IDSCHOOL160 -207.9735 32.5168 -6.396 1.79e-10 ***
## IDSCHOOL161 -218.7214 30.1009 -7.266 4.46e-13 ***
## IDSCHOOL162 -202.6801 29.2050 -6.940 4.59e-12 ***
## IDSCHOOL163 -208.3977 29.5601 -7.050 2.12e-12 ***
## IDSCHOOL164 -212.3900 28.8038 -7.374 2.03e-13 ***
## IDSCHOOL165 -113.3317 19.0134 -5.961 2.74e-09 ***
## IDSCHOOL166 -132.6207 19.0074 -6.977 3.53e-12 ***
## IDSCHOOL167 -113.9466 18.8790 -6.036 1.73e-09 ***
## IDSCHOOL168 20.5817 31.6594 0.650 0.515669
## IDSCHOOL169 -73.4146 29.7949 -2.464 0.013783 *
## IDSCHOOL170 -237.1133 31.5254 -7.521 6.72e-14 ***
## IDSCHOOL171 -227.7551 31.7692 -7.169 9.03e-13 ***
## IDSCHOOL172 -177.3039 29.7854 -5.953 2.88e-09 ***
## IDSCHOOL173 -180.6617 30.6746 -5.890 4.21e-09 ***
## IDSCHOOL174 -113.7495 18.8732 -6.027 1.83e-09 ***
## IDSCHOOL175 -261.4133 33.1102 -7.895 3.76e-15 ***
## IDSCHOOL176 -63.3139 31.7585 -1.994 0.046266 *
## IDSCHOOL177 -195.9926 29.9618 -6.541 6.90e-11 ***
## IDSCHOOL178 -179.5935 30.9172 -5.809 6.80e-09 ***
## IDSCHOOL179 -197.4734 32.5243 -6.072 1.39e-09 ***
## IDSCHOOL180 -56.6853 19.3003 -2.937 0.003334 **
## IDSCHOOL181 -108.5058 19.8363 -5.470 4.79e-08 ***
## IDSCHOOL182 -77.5054 19.8266 -3.909 9.42e-05 ***
## IDSCHOOL183 -147.2850 18.2900 -8.053 1.07e-15 ***
## IDSCHOOL184 -93.1731 22.8623 -4.075 4.69e-05 ***
## IDSCHOOL185 -67.2483 21.3066 -3.156 0.001611 **
## IDSCHOOL186 -26.3091 22.8444 -1.152 0.249531
## IDSCHOOL187 -183.0709 32.9836 -5.550 3.05e-08 ***
## IDSCHOOL188 NA NA NA NA
## IDSCHOOL189 -62.7300 23.3265 -2.689 0.007193 **
## ASBM01A -1.2465 1.0091 -1.235 0.216821
## ASBM01B 5.4427 0.8168 6.663 3.06e-11 ***
## ASBM01C 3.3847 0.7857 4.308 1.69e-05 ***
## ASBM01D -2.0998 0.8208 -2.558 0.010558 *
## ASBM01E -1.3600 1.0210 -1.332 0.182944
## ASBM01F 0.6827 0.9900 0.690 0.490517
## ASBM01G 0.3844 1.1435 0.336 0.736757
## ASBM01H -1.5915 1.1816 -1.347 0.178103
## ASBM01I -6.1758 1.2046 -5.127 3.10e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 69.33 on 3811 degrees of freedom
## (328 observations deleted due to missingness)
## Multiple R-squared: 0.4289, Adjusted R-squared: 0.3994
## F-statistic: 14.53 on 197 and 3811 DF, p-value: < 2.2e-16
histogram(~ ASMMAT03 |ITSEX, data = dtfile)
histogram(~ ASMMAT03 | IDSCHOOL, data = dtfile)
boxplot(ASMMAT03 ~ IDSCHOOL, data = dtfile)
plotSlopes(Regression_Model, plotx = "ASBM01B", modx = "IDSCHOOL")
## Warning in predict.lm(structure(list(coefficients =
## structure(c(562.759500659585, : prediction from a rank-deficient fit may be
## misleading
Base Multilevel Model
first.model <- lmer(ASMMAT03 ~ (1| IDSCHOOL), data = dtfile)
summary(first.model)
## Linear mixed model fit by REML ['lmerMod']
## Formula: ASMMAT03 ~ (1 | IDSCHOOL)
## Data: dtfile
##
## REML criterion at convergence: 49816.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.6407 -0.6667 -0.0045 0.6857 3.6889
##
## Random effects:
## Groups Name Variance Std.Dev.
## IDSCHOOL (Intercept) 3340 57.79
## Residual 5071 71.21
## Number of obs: 4337, groups: IDSCHOOL, 189
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 387.661 4.359 88.93
icc(first.model)
##
## Linear mixed model
## Family: gaussian (identity)
## Formula: ASMMAT03 ~ (1 | IDSCHOOL)
##
## ICC (IDSCHOOL): 0.397096
outreg(list("Model1"= first.model), type = "html", browse = TRUE)
##
## Temp file: /var/folders/nt/strrwnzj3_92_s8t4_4qfl100000gn/T//RtmpQGYvFq/file74f41cb46b99.html
### Plottig this model
basemodel <- ranef(first.model, condVar=TRUE)
dotplot(basemodel)
## $IDSCHOOL
ggplot(data = dtfile[as.numeric(dtfile$IDSCHOOL)<=20,], aes(x=IDSCHOOL, y=ASMMAT03)) + geom_point() + facet_wrap(~IDSCHOOL)
ggplot(data = dtfile[as.numeric(dtfile$IDSCHOOL)<=20,], aes(x=IDSCHOOL, y=ASMMAT03)) + geom_boxplot() + facet_wrap(~IDSCHOOL)
Second Model
second.model <- lmer(ASMMAT03 ~ ITSEX + ASBM01A
+ ASBM01B + ASBM01C + ASBM01D + ASBM01E + ASBM01F
+ ASBM01G + ASBM01H + ASBM01I + ( 1| IDSCHOOL), dtfile, REML = FALSE)
summary(second.model)
## Linear mixed model fit by maximum likelihood ['lmerMod']
## Formula:
## ASMMAT03 ~ ITSEX + ASBM01A + ASBM01B + ASBM01C + ASBM01D + ASBM01E +
## ASBM01F + ASBM01G + ASBM01H + ASBM01I + (1 | IDSCHOOL)
## Data: dtfile
##
## AIC BIC logLik deviance df.resid
## 45854.1 45936.0 -22914.1 45828.1 3996
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.7476 -0.6684 -0.0062 0.6772 3.6552
##
## Random effects:
## Groups Name Variance Std.Dev.
## IDSCHOOL (Intercept) 2677 51.74
## Residual 4798 69.27
## Number of obs: 4009, groups: IDSCHOOL, 189
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 432.1607 12.8660 33.589
## ITSEX -32.6655 7.9124 -4.128
## ASBM01A -1.0687 1.0047 -1.064
## ASBM01B 5.4329 0.8133 6.680
## ASBM01C 3.3859 0.7825 4.327
## ASBM01D -2.1003 0.8180 -2.567
## ASBM01E -1.5907 1.0172 -1.564
## ASBM01F 0.6748 0.9860 0.684
## ASBM01G 0.3645 1.1395 0.320
## ASBM01H -1.6865 1.1777 -1.432
## ASBM01I -6.1159 1.2006 -5.094
##
## Correlation of Fixed Effects:
## (Intr) ITSEX ASBM01A ASBM01B ASBM01C ASBM01D ASBM01E ASBM01F
## ITSEX -0.932
## ASBM01A -0.040 -0.001
## ASBM01B -0.104 0.025 -0.018
## ASBM01C -0.098 0.018 0.037 -0.467
## ASBM01D 0.012 -0.014 -0.107 -0.080 -0.013
## ASBM01E 0.030 -0.019 -0.157 0.002 -0.089 -0.109
## ASBM01F 0.015 -0.008 -0.042 -0.050 -0.087 -0.119 -0.125
## ASBM01G 0.010 -0.003 -0.114 -0.054 -0.002 -0.070 -0.221 -0.197
## ASBM01H 0.008 -0.012 -0.083 0.002 -0.020 -0.137 -0.154 -0.132
## ASBM01I -0.008 -0.003 -0.067 -0.021 -0.014 -0.085 -0.144 -0.167
## ASBM01G ASBM01H
## ITSEX
## ASBM01A
## ASBM01B
## ASBM01C
## ASBM01D
## ASBM01E
## ASBM01F
## ASBM01G
## ASBM01H -0.219
## ASBM01I -0.215 -0.374
confint(second.model)
## Computing profile confidence intervals ...
## 2.5 % 97.5 %
## .sig01 46.382920 58.0215589
## .sigma 67.741230 70.8501223
## (Intercept) 406.842246 457.5219032
## ITSEX -48.266788 -17.0891826
## ASBM01A -3.038501 0.9014459
## ASBM01B 3.838506 7.0273649
## ASBM01C 1.851740 4.9199857
## ASBM01D -3.703966 -0.4965415
## ASBM01E -3.585668 0.4037699
## ASBM01F -1.258206 2.6076993
## ASBM01G -1.869400 2.5983604
## ASBM01H -3.995614 0.6223680
## ASBM01I -8.469653 -3.7619871
outreg(list("Model2"= second.model), type = "html", browse = TRUE)
##
## Temp file: /var/folders/nt/strrwnzj3_92_s8t4_4qfl100000gn/T//RtmpQGYvFq/file74f46be68d57.html
Thrid Model
third.model <- lmer(ASMMAT03 ~ ITSEX + ASBM01B + ASBM01C + ASBM01D + ASBM01I + (1|IDSCHOOL), data = dtfile)
summary(third.model)
## Linear mixed model fit by REML ['lmerMod']
## Formula: ASMMAT03 ~ ITSEX + ASBM01B + ASBM01C + ASBM01D + ASBM01I + (1 |
## IDSCHOOL)
## Data: dtfile
##
## REML criterion at convergence: 47222.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.6807 -0.6555 -0.0090 0.6742 3.7063
##
## Random effects:
## Groups Name Variance Std.Dev.
## IDSCHOOL (Intercept) 2730 52.25
## Residual 4788 69.20
## Number of obs: 4134, groups: IDSCHOOL, 189
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 432.7624 12.9276 33.476
## ITSEX -33.2709 7.9645 -4.177
## ASBM01B 5.0614 0.7762 6.521
## ASBM01C 3.2700 0.7392 4.424
## ASBM01D -2.9589 0.7302 -4.052
## ASBM01I -7.6560 0.7836 -9.770
##
## Correlation of Fixed Effects:
## (Intr) ITSEX ASBM01B ASBM01C ASBM01D
## ITSEX -0.934
## ASBM01B -0.100 0.023
## ASBM01C -0.091 0.015 -0.474
## ASBM01D 0.022 -0.027 -0.127 -0.073
## ASBM01I 0.016 -0.037 -0.115 -0.136 -0.536
confint(third.model)
## Computing profile confidence intervals ...
## 2.5 % 97.5 %
## .sig01 46.584927 58.205973
## .sigma 67.662592 70.716982
## (Intercept) 407.444768 458.096002
## ITSEX -48.881110 -17.670849
## ASBM01B 3.540553 6.582151
## ASBM01C 1.821297 4.718246
## ASBM01D -4.389887 -1.528503
## ASBM01I -9.192718 -6.121648
outreg(list("Model3"= third.model), type = "html", browse = TRUE)
##
## Temp file: /var/folders/nt/strrwnzj3_92_s8t4_4qfl100000gn/T//RtmpQGYvFq/file74f474fc2db5.html
third.model1<-ranef(third.model, condVar=TRUE)
dotplot(third.model1)
## $IDSCHOOL
