library(foreign)## Warning: package 'foreign' was built under R version 3.2.5r=read.dta("C:/Users/BINH THANG/Dropbox/Korea/STudy/Thesis/data management/DataR/dataR3.dta")
r1 <- subset(r)
attach(r1)
r1$wtp[r1$cost_inc >=1] <- 1
r1$wtp[is.na(r1$cost_inc )] <- 0
r1$b16a[b16a == 5] <- 0
r1$freeEn[c9==1] <- 1
r1$freeEn[c9>1] <- 0
r1$h1[h1== 1] <- 1
r1$h1[h1== 2] <- 0
r1$c7ad[c7== 2] <- 0
r1$c7ad[c7== 1] <- 1
r1$c7ad[is.na(r1$c7)] <- 0
r1$ant[c5==1& c5==2 & c5==7 & c5==8 & c5==9] <- 0
r1$ant[c5==3|c5==4|c5==5] <- 1
r1$ant[is.na(r1$c5)] <- 0
r1$p1=r1$label1+r1$freeEn+r1$ant+r1$c7ad
r1$p[r1$p1==0] <- 0
r1$p[r1$p1==1] <- 1
r1$p[r1$p1>=2] <- 2
attach(r)## The following objects are masked from r1:
##
## a1, advice, advice1, ag, age_group, anticam, anticam2, b1,
## b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, policy,
## policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4newdata2=r1
attach(newdata2 )## The following objects are masked from r:
##
## a1, advice, advice1, ag, age_group, anticam, anticam2, b1,
## b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, policy,
## policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4
##
## The following objects are masked from r1:
##
## a1, advice, advice1, ag, age_group, anticam, anticam2, b1,
## b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, policy,
## policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4newdata2$wtp=factor(newdata2$wtp)
newdata2$age_group=as.factor(newdata2$age_group)
newdata2$educ2=as.factor(newdata2$educ2)
newdata2$h1=as.factor(newdata2$h1)
newdata2$d1a=as.factor(newdata2$d1a)
newdata2$selfhealth=as.factor(newdata2$selfhealth)
newdata2$b18a=as.factor(newdata2$b18a)
newdata2$b16a=as.factor(newdata2$b16a)
newdata2$b6a=as.factor(newdata2$b6a)
newdata2$smostt=as.factor(newdata2$smostt)
newdata2$ter_in=as.factor(newdata2$ter_in)
newdata2$group_age1=as.factor(newdata2$group_age1)
newdata2$label1=as.factor(newdata2$label1)
newdata2$freeEn=as.factor(newdata2$freeEn)
newdata2$c7ad=as.factor(newdata2$c7ad)
newdata2$ant=as.factor(newdata2$ant)
newdata2$p=as.factor(newdata2$p)library("psych", lib.loc="~/R/win-library/3.2")## Warning: package 'psych' was built under R version 3.2.5a=describe(newdata2$cost_inc)
library(knitr)## Warning: package 'knitr' was built under R version 3.2.5kable(a, caption = "A knitr kable.")| vars | n | mean | sd | median | trimmed | mad | min | max | range | skew | kurtosis | se | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| X1 | 1 | 461 | 79438.18 | 55255.2 | 62000 | 70410.57 | 32617.2 | 17000 | 422000 | 405000 | 2.496445 | 8.829917 | 2573.491 |
describe.by(newdata2$cost_inc, newdata2$age_group)## Warning: describe.by is deprecated. Please use the describeBy function## $`group18-29`
## vars n mean sd median trimmed mad min max range
## X1 1 191 82424.08 52523.71 70000 75065.36 41512.8 22000 410000 388000
## skew kurtosis se
## X1 2.35 9.01 3800.48
##
## $gr3039
## vars n mean sd median trimmed mad min max range
## X1 1 76 88855.26 58710.07 73000 78500 41512.8 23000 322000 299000
## skew kurtosis se
## X1 1.77 3.3 6734.51
##
## $gr4049
## vars n mean sd median trimmed mad min max range
## X1 1 94 71005.32 49034.47 54500 63151.32 23721.6 19000 335000 316000
## skew kurtosis se
## X1 2.89 10.93 5057.52
##
## $gr5059
## vars n mean sd median trimmed mad min max range
## X1 1 73 75212.33 63821.47 57000 62754.24 25204.2 17000 422000 405000
## skew kurtosis se
## X1 2.85 10.71 7469.74
##
## $`60plus`
## vars n mean sd median trimmed mad min max range
## X1 1 27 72592.59 57910.58 54000 63521.74 28169.4 21000 320000 299000
## skew kurtosis se
## X1 2.87 9.49 11144.9
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$d1a)## Warning: describe.by is deprecated. Please use the describeBy function## $none
## vars n mean sd median trimmed mad min max range
## X1 1 180 81516.67 52744.61 69000 73986.11 39288.9 22000 410000 388000
## skew kurtosis se
## X1 2.44 9.55 3931.35
##
## $married
## vars n mean sd median trimmed mad min max range
## X1 1 281 78106.76 56857.91 60000 68117.78 29652 17000 422000 405000
## skew kurtosis se
## X1 2.52 8.4 3391.86
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$educ2)## Warning: describe.by is deprecated. Please use the describeBy function## $`1`
## vars n mean sd median trimmed mad min max range
## X1 1 96 75343.75 66666.78 53500 61666.67 25945.5 17000 422000 405000
## skew kurtosis se
## X1 2.83 9.39 6804.15
##
## $`2`
## vars n mean sd median trimmed mad min max range
## X1 1 220 75106.82 48438.91 60000 67818.18 29652 17000 335000 318000
## skew kurtosis se
## X1 2.16 6.26 3265.75
##
## $`3`
## vars n mean sd median trimmed mad min max range
## X1 1 136 90988.97 56800.97 77500 82186.36 45219.3 24000 410000 386000
## skew kurtosis se
## X1 2.27 7.81 4870.64
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$ter_in)## Warning: describe.by is deprecated. Please use the describeBy function## $`1`
## vars n mean sd median trimmed mad min max range
## X1 1 191 75222.51 52085.85 60000 66882.35 29652 17000 410000 393000
## skew kurtosis se
## X1 2.72 10.92 3768.8
##
## $`2`
## vars n mean sd median trimmed mad min max range
## X1 1 121 79471.07 51493.38 64000 73835.05 38547.6 17000 422000 405000
## skew kurtosis se
## X1 2.93 15.13 4681.22
##
## $`3`
## vars n mean sd median trimmed mad min max range
## X1 1 141 85670.21 62679.68 65000 73216.81 37065 25000 335000 310000
## skew kurtosis se
## X1 1.98 3.96 5278.58
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$selfhealth)## Warning: describe.by is deprecated. Please use the describeBy function## $notwell
## vars n mean sd median trimmed mad min max range
## X1 1 254 75470.47 57596.32 58000 65093.14 29652 17000 422000 405000
## skew kurtosis se
## X1 2.88 11.15 3613.91
##
## $good
## vars n mean sd median trimmed mad min max range
## X1 1 207 84306.76 51963.94 71000 76877.25 41512.8 17000 322000 305000
## skew kurtosis se
## X1 1.93 5.12 3611.74
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$c1)## Warning: describe.by is deprecated. Please use the describeBy function## $`1`
## vars n mean sd median trimmed mad min max range
## X1 1 398 79675.88 56008.34 62000 70735.94 32617.2 17000 422000 405000
## skew kurtosis se
## X1 2.58 9.37 2807.44
##
## $`2`
## vars n mean sd median trimmed mad min max range
## X1 1 63 77936.51 50627.63 68000 68686.27 38547.6 24000 240000 216000
## skew kurtosis se
## X1 1.69 2.55 6378.48
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$smostt)## Warning: describe.by is deprecated. Please use the describeBy function## $light
## vars n mean sd median trimmed mad min max range
## X1 1 127 83307.09 63480.09 62000 71223.3 32617.2 19000 410000 391000
## skew kurtosis se
## X1 2.28 6.52 5632.95
##
## $medium
## vars n mean sd median trimmed mad min max range
## X1 1 173 72190.75 39279.46 62000 67561.15 25204.2 17000 308000 291000
## skew kurtosis se
## X1 2.29 8.91 2986.36
##
## $heavy
## vars n mean sd median trimmed mad min max range
## X1 1 161 84173.91 62084.85 62000 73577.52 40030.2 17000 422000 405000
## skew kurtosis se
## X1 2.27 7.03 4892.97
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$b6a)## Warning: describe.by is deprecated. Please use the describeBy function## $no
## vars n mean sd median trimmed mad min max range
## X1 1 377 78286.47 53269.15 61000 69787.13 31134.6 17000 410000 393000
## skew kurtosis se
## X1 2.34 7.78 2743.5
##
## $yes
## vars n mean sd median trimmed mad min max range
## X1 1 76 88236.84 65419.64 72500 76403.23 43736.7 24000 422000 398000
## skew kurtosis se
## X1 2.64 8.9 7504.15
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$h1)## Warning: describe.by is deprecated. Please use the describeBy function## $`0`
## vars n mean sd median trimmed mad min max range
## X1 1 169 74893.49 49650.21 60000 67635.04 29652 17000 322000 305000
## skew kurtosis se
## X1 2.21 6.78 3819.25
##
## $`1`
## vars n mean sd median trimmed mad min max range
## X1 1 292 82068.49 58173.46 68000 72061.97 38547.6 17000 422000 405000
## skew kurtosis se
## X1 2.55 8.96 3404.34
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$b16a)## Warning: describe.by is deprecated. Please use the describeBy function## $`0`
## vars n mean sd median trimmed mad min max range
## X1 1 64 76218.75 42595.35 66000 73384.62 36323.7 19000 255000 236000
## skew kurtosis se
## X1 1.32 2.96 5324.42
##
## $`1`
## vars n mean sd median trimmed mad min max range
## X1 1 395 79982.28 57177 62000 69954.26 32617.2 17000 422000 405000
## skew kurtosis se
## X1 2.53 8.67 2876.89
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$b18a)## Warning: describe.by is deprecated. Please use the describeBy function## $Good
## vars n mean sd median trimmed mad min max range
## X1 1 154 73600.65 53508.27 55500 65495.97 27428.1 17000 410000 393000
## skew kurtosis se
## X1 3.24 14.46 4311.82
##
## $bad
## vars n mean sd median trimmed mad min max range
## X1 1 304 82284.54 56143.72 68000 72795.08 39288.9 17000 422000 405000
## skew kurtosis se
## X1 2.18 6.64 3220.06
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$label1)## Warning: describe.by is deprecated. Please use the describeBy function## $`0`
## vars n mean sd median trimmed mad min max range
## X1 1 383 80616.19 56002.85 63000 71607.49 34099.8 17000 422000 405000
## skew kurtosis se
## X1 2.49 8.93 2861.61
##
## $`1`
## vars n mean sd median trimmed mad min max range skew
## X1 1 77 73961.04 51639.04 60000 65238.1 29652 17000 322000 305000 2.42
## kurtosis se
## X1 7.27 5884.81
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$ant)## Warning: describe.by is deprecated. Please use the describeBy function## $`0`
## vars n mean sd median trimmed mad min max range skew
## X1 1 2 37500 17677.67 37500 37500 18532.5 25000 50000 25000 0
## kurtosis se
## X1 -2.75 12500
##
## $`1`
## vars n mean sd median trimmed mad min max range
## X1 1 172 77244.19 48618.68 61500 69920.29 34841.1 17000 285000 268000
## skew kurtosis se
## X1 1.71 3.33 3707.14
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$freeEn)## Warning: describe.by is deprecated. Please use the describeBy function## $`0`
## vars n mean sd median trimmed mad min max range
## X1 1 346 80234.1 53920.38 64000 71314.75 31134.6 19000 410000 391000
## skew kurtosis se
## X1 2.36 7.64 2898.78
##
## $`1`
## vars n mean sd median trimmed mad min max range
## X1 1 113 77743.36 59537.92 56000 68417.58 29652 17000 422000 405000
## skew kurtosis se
## X1 2.77 10.9 5600.86
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$c7ad)## Warning: describe.by is deprecated. Please use the describeBy function## $`0`
## vars n mean sd median trimmed mad min max range
## X1 1 302 78725.17 55784.76 61000 69431.82 31134.6 17000 410000 393000
## skew kurtosis se
## X1 2.37 7.45 3210.05
##
## $`1`
## vars n mean sd median trimmed mad min max range
## X1 1 159 80792.45 54384.02 68000 72410.85 38547.6 25000 422000 397000
## skew kurtosis se
## X1 2.75 11.54 4312.93
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$cost_inc, newdata2$p)## Warning: describe.by is deprecated. Please use the describeBy function## $`1`
## vars n mean sd median trimmed mad min max range
## X1 1 53 89283.02 63575.33 62000 78744.19 40030.2 21000 285000 264000
## skew kurtosis se
## X1 1.43 1.24 8732.74
##
## $`2`
## vars n mean sd median trimmed mad min max range
## X1 1 119 71882.35 39373.09 61000 67701.03 31134.6 17000 222000 205000
## skew kurtosis se
## X1 1.32 2.13 3609.33
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)Now, we are going to see description for casual branch in Vietnam.
Descriptive for common smoke price in Vietnam
r=read.dta("C:/Users/BINH THANG/Dropbox/Korea/STudy/Thesis/data management/DataR/dataR3.dta")
r1 <- subset(r, br==10)
attach(r1)## The following objects are masked from newdata2:
##
## a1, advice, advice1, ag, age_group, anticam, anticam2, b1,
## b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, policy,
## policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4## The following objects are masked from r:
##
## a1, advice, advice1, ag, age_group, anticam, anticam2, b1,
## b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, policy,
## policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4## The following objects are masked from r1 (pos = 7):
##
## a1, advice, advice1, ag, age_group, anticam, anticam2, b1,
## b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, policy,
## policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4r1$freeEn[c9==1] <- 1
r1$freeEn[c9>1] <- 0
r1$h1[h1== 1] <- 1
r1$h1[h1== 2] <- 0
r1$c7ad[c7== 2] <- 0
r1$c7ad[c7== 1] <- 1
r1$c7ad[is.na(r1$c7)] <- 0
r1$ant[c5==1& c5==2 & c5==7 & c5==8 & c5==9] <- 0
r1$ant[c5==3|c5==4|c5==5] <- 1
r1$ant[is.na(r1$c5)] <- 0
r1$p1=r1$label1+r1$freeEn+r1$ant+r1$c7ad
r1$p[r1$p1==0] <- 0
r1$p[r1$p1==1] <- 1
r1$p[r1$p1>=2] <- 2
attach(r1)## The following objects are masked from r1 (pos = 3):
##
## a1, advice, advice1, ag, age_group, anticam, anticam2, b1,
## b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, policy,
## policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4## The following objects are masked from newdata2:
##
## a1, advice, advice1, ag, age_group, ant, anticam, anticam2,
## b1, b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c7ad, c8, c9, COST, cost_inc, cost1, costincrease, ct,
## d1, d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9,
## Decision, e1, e2, edu, educ1, educ2, f1, freeEn, ghi1, ghi2,
## ghiro2, giadinhkoUH, group_age, group_age1, h1, h10a, h10a1,
## h10a10, h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6,
## h10a7, h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3,
## h4, h5, h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5,
## l6, label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, p, p1,
## policy, policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4## The following objects are masked from r:
##
## a1, advice, advice1, ag, age_group, anticam, anticam2, b1,
## b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, policy,
## policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4## The following objects are masked from r1 (pos = 8):
##
## a1, advice, advice1, ag, age_group, anticam, anticam2, b1,
## b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, policy,
## policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4newdata2=r1
attach(newdata2 )## The following objects are masked from r1 (pos = 3):
##
## a1, advice, advice1, ag, age_group, ant, anticam, anticam2,
## b1, b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c7ad, c8, c9, COST, cost_inc, cost1, costincrease, ct,
## d1, d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9,
## Decision, e1, e2, edu, educ1, educ2, f1, freeEn, ghi1, ghi2,
## ghiro2, giadinhkoUH, group_age, group_age1, h1, h10a, h10a1,
## h10a10, h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6,
## h10a7, h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3,
## h4, h5, h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5,
## l6, label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, p, p1,
## policy, policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4## The following objects are masked from r1 (pos = 4):
##
## a1, advice, advice1, ag, age_group, anticam, anticam2, b1,
## b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, policy,
## policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4## The following objects are masked from newdata2 (pos = 7):
##
## a1, advice, advice1, ag, age_group, ant, anticam, anticam2,
## b1, b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c7ad, c8, c9, COST, cost_inc, cost1, costincrease, ct,
## d1, d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9,
## Decision, e1, e2, edu, educ1, educ2, f1, freeEn, ghi1, ghi2,
## ghiro2, giadinhkoUH, group_age, group_age1, h1, h10a, h10a1,
## h10a10, h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6,
## h10a7, h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3,
## h4, h5, h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5,
## l6, label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, p, p1,
## policy, policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4## The following objects are masked from r:
##
## a1, advice, advice1, ag, age_group, anticam, anticam2, b1,
## b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, policy,
## policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4## The following objects are masked from r1 (pos = 9):
##
## a1, advice, advice1, ag, age_group, anticam, anticam2, b1,
## b10, b10a1, b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11,
## b11a, b11a2, b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17,
## b18, b18a, b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1,
## b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br,
## branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5,
## c6, c7, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, label2, moneyspent, msdt, n01, n02, n03, n05, n06,
## n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13, n14,
## n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4,
## n40, n41, n42, n43, n44, n45, n46, n47, n48, n49, n5, n50,
## n51, n52, n53, n54, n55, n56, n57, n58, n59, n6, n60, n61,
## n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a,
## n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8, n88, n89,
## n8nha, n9, n97, n98, n99, n9khach, noEnvi2, occup1, policy,
## policy_a, policy2, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4```
newdata2$age_group=as.factor(newdata2$age_group)
newdata2$educ2=as.factor(newdata2$educ2)
newdata2$h1=as.factor(newdata2$h1)
newdata2$d1a=as.factor(newdata2$d1a)
newdata2$selfhealth=as.factor(newdata2$selfhealth)
newdata2$b18a=as.factor(newdata2$b18a)
newdata2$b16a=as.factor(newdata2$b16a)
newdata2$b6a=as.factor(newdata2$b6a)
newdata2$smostt=as.factor(newdata2$smostt)
newdata2$ter_in=as.factor(newdata2$ter_in)
newdata2$group_age1=as.factor(newdata2$group_age1)
newdata2$label1=as.factor(newdata2$label1)
newdata2$freeEn=as.factor(newdata2$freeEn)
newdata2$c7ad=as.factor(newdata2$c7ad)
newdata2$ant=as.factor(newdata2$ant)
newdata2$p=as.factor(newdata2$p)library("psych", lib.loc="~/R/win-library/3.2")
a=describe(newdata2$cost_inc)
library(knitr)
kable(a, caption = "A knitr kable.")| vars | n | mean | sd | median | trimmed | mad | min | max | range | skew | kurtosis | se | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| X1 | 1 | 337 | 78826.41 | 51109.54 | 63000 | 70749.08 | 32617.2 | 17000 | 335000 | 318000 | 2.042623 | 5.385577 | 2784.114 |
describe.by(newdata2$b11a2, newdata2$age_group)## Warning: describe.by is deprecated. Please use the describeBy function## $`group18-29`
## vars n mean sd median trimmed mad min max range skew
## X1 1 146 25013.7 15800.91 22500 23525.42 3706.5 7000 2e+05 193000 9.31
## kurtosis se
## X1 100.16 1307.69
##
## $gr3039
## vars n mean sd median trimmed mad min max range skew
## X1 1 62 25016.13 8673.48 23500 24420 5189.1 8000 70000 62000 2.15
## kurtosis se
## X1 9.74 1101.53
##
## $gr4049
## vars n mean sd median trimmed mad min max range skew
## X1 1 84 25583.67 29365.37 22000 22411.76 5930.4 28 280000 279972 7.73
## kurtosis se
## X1 64.11 3204.02
##
## $gr5059
## vars n mean sd median trimmed mad min max range skew
## X1 1 49 24908.16 26572.16 22000 21707.32 7413 6000 2e+05 194000 5.8
## kurtosis se
## X1 35.5 3796.02
##
## $`60plus`
## vars n mean sd median trimmed mad min max range skew
## X1 1 17 21117.65 7192.73 22000 21466.67 8895.6 7000 30000 23000 -0.61
## kurtosis se
## X1 -1.06 1744.49
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$d1a)## Warning: describe.by is deprecated. Please use the describeBy function## $none
## vars n mean sd median trimmed mad min max range skew
## X1 1 136 25705.88 16417.3 23000 23981.82 4447.8 7000 2e+05 193000 8.8
## kurtosis se
## X1 90.53 1407.77
##
## $married
## vars n mean sd median trimmed mad min max range
## X1 1 222 24484.36 22396.65 22000 22640.45 5930.4 28 280000 279972
## skew kurtosis se
## X1 8.87 90.43 1503.16
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$educ2)## Warning: describe.by is deprecated. Please use the describeBy function## $`1`
## vars n mean sd median trimmed mad min max range
## X1 1 66 27606.06 39291.76 22000 21129.63 5930.4 7000 280000 273000
## skew kurtosis se
## X1 5.27 28.42 4836.48
##
## $`2`
## vars n mean sd median trimmed mad min max range skew
## X1 1 187 24350.42 14704.06 23000 23549.67 4447.8 28 2e+05 199972 9.1
## kurtosis se
## X1 106.18 1075.27
##
## $`3`
## vars n mean sd median trimmed mad min max range skew
## X1 1 97 24443.3 7966.03 23000 23987.34 4447.8 7000 70000 63000 1.91
## kurtosis se
## X1 9.97 808.83
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$ter_in)## Warning: describe.by is deprecated. Please use the describeBy function## $`1`
## vars n mean sd median trimmed mad min max range skew
## X1 1 145 22493.1 16201.42 22000 21692.31 4447.8 6000 2e+05 194000 9
## kurtosis se
## X1 96.47 1345.45
##
## $`2`
## vars n mean sd median trimmed mad min max range
## X1 1 95 26389.47 27047.36 22000 23610.39 4447.8 7000 280000 273000
## skew kurtosis se
## X1 8.67 78.38 2775
##
## $`3`
## vars n mean sd median trimmed mad min max range skew
## X1 1 111 27009.26 18876.03 25000 24977.53 7413 28 2e+05 199972 7.01
## kurtosis se
## X1 60.95 1791.63
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$selfhealth)## Warning: describe.by is deprecated. Please use the describeBy function## $notwell
## vars n mean sd median trimmed mad min max range skew
## X1 1 191 24505.38 19572.82 22000 22954.25 5930.4 28 2e+05 199972 7.51
## kurtosis se
## X1 64.78 1416.24
##
## $good
## vars n mean sd median trimmed mad min max range
## X1 1 167 25455.09 21184.7 23000 23644.44 4447.8 7000 280000 273000
## skew kurtosis se
## X1 10.43 121.97 1639.32
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$c1)## Warning: describe.by is deprecated. Please use the describeBy function## $`1`
## vars n mean sd median trimmed mad min max range skew
## X1 1 309 25347.99 21648.12 23000 23449.8 4447.8 28 280000 279972 8.67
## kurtosis se
## X1 86.5 1231.52
##
## $`2`
## vars n mean sd median trimmed mad min max range skew
## X1 1 49 22428.57 7452.63 22000 22390.24 2965.2 7000 41000 34000 0.02
## kurtosis se
## X1 0.44 1064.66
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$smostt)## Warning: describe.by is deprecated. Please use the describeBy function## $light
## vars n mean sd median trimmed mad min max range skew
## X1 1 98 23857.14 8256.21 23000 23512.5 4447.8 7000 70000 63000 1.75
## kurtosis se
## X1 8.89 834
##
## $medium
## vars n mean sd median trimmed mad min max range
## X1 1 137 26306.57 27476.61 23000 23396.4 4447.8 6000 280000 274000
## skew kurtosis se
## X1 7.57 61.73 2347.49
##
## $heavy
## vars n mean sd median trimmed mad min max range skew
## X1 1 123 24305.11 17569.64 22000 23020.2 4447.8 28 2e+05 199972 8.1
## kurtosis se
## X1 78.46 1584.2
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$b6a)## Warning: describe.by is deprecated. Please use the describeBy function## $no
## vars n mean sd median trimmed mad min max range skew
## X1 1 296 25049.08 22122.7 22000 23050.42 4447.8 28 280000 279972 8.51
## kurtosis se
## X1 83.13 1285.86
##
## $yes
## vars n mean sd median trimmed mad min max range skew
## X1 1 57 24438.6 7171.42 23000 24212.77 4447.8 7000 50000 43000 0.61
## kurtosis se
## X1 2.58 949.88
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$h1)## Warning: describe.by is deprecated. Please use the describeBy function## $`0`
## vars n mean sd median trimmed mad min max range
## X1 1 134 25082.09 23507.17 23000 23101.85 4447.8 7000 280000 273000
## skew kurtosis se
## X1 9.55 100.33 2030.71
##
## $`1`
## vars n mean sd median trimmed mad min max range skew
## X1 1 224 24868.43 18200.43 22000 23438.89 4447.8 28 2e+05 199972 7.93
## kurtosis se
## X1 73.68 1216.07
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$b16a)## Warning: describe.by is deprecated. Please use the describeBy function## $`0`
## vars n mean sd median trimmed mad min max range
## X1 1 45 28555.56 38851.44 22000 23189.19 4447.8 8000 280000 272000
## skew kurtosis se
## X1 6.01 35.99 5791.63
##
## $`1`
## vars n mean sd median trimmed mad min max range skew
## X1 1 312 24347.85 16001.12 22000 23324 4447.8 28 2e+05 199972 8.51
## kurtosis se
## X1 90.48 905.89
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$b18a)## Warning: describe.by is deprecated. Please use the describeBy function## $Good
## vars n mean sd median trimmed mad min max range
## X1 1 129 26108.53 23151.75 23000 23495.24 4447.8 7000 2e+05 193000
## skew kurtosis se
## X1 6.54 46.39 2038.4
##
## $bad
## vars n mean sd median trimmed mad min max range
## X1 1 227 24191.75 18594.36 22000 23125.68 4447.8 28 280000 279972
## skew kurtosis se
## X1 11.51 155.06 1234.15
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$label1)## Warning: describe.by is deprecated. Please use the describeBy function## $`0`
## vars n mean sd median trimmed mad min max range skew
## X1 1 307 24447.97 16165.23 23000 23340.08 4447.8 28 2e+05 199972 8.38
## kurtosis se
## X1 88 922.6
##
## $`1`
## vars n mean sd median trimmed mad min max range skew
## X1 1 50 27920 36939.47 22000 22950 3706.5 8000 280000 272000 6.35
## kurtosis se
## X1 40.38 5224.03
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$ant)## Warning: describe.by is deprecated. Please use the describeBy function## $`0`
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 1 10000 NA 10000 10000 0 10000 10000 0 NA NA NA
##
## $`1`
## vars n mean sd median trimmed mad min max range skew
## X1 1 125 24952 24582.27 22000 22594.06 4447.8 6000 280000 274000 8.96
## kurtosis se
## X1 89.83 2198.71
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$freeEn)## Warning: describe.by is deprecated. Please use the describeBy function## $`0`
## vars n mean sd median trimmed mad min max range skew
## X1 1 274 25823.09 22949 22500 23550 3706.5 28 280000 279972 8.15
## kurtosis se
## X1 76.25 1386.4
##
## $`1`
## vars n mean sd median trimmed mad min max range skew
## X1 1 83 22240.96 5575.62 22000 22865.67 4447.8 6000 35000 29000 -0.93
## kurtosis se
## X1 1.24 612
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$c7ad)## Warning: describe.by is deprecated. Please use the describeBy function## $`0`
## vars n mean sd median trimmed mad min max range
## X1 1 238 26182.77 24262.39 23000 23765.62 4447.8 6000 280000 274000
## skew kurtosis se
## X1 7.88 69.5 1572.7
##
## $`1`
## vars n mean sd median trimmed mad min max range skew
## X1 1 120 22500.23 7544.12 22000 22541.67 2965.2 28 70000 69972 1.85
## kurtosis se
## X1 12.61 688.68
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)describe.by(newdata2$b11a2, newdata2$p)## Warning: describe.by is deprecated. Please use the describeBy function## $`1`
## vars n mean sd median trimmed mad min max range skew
## X1 1 45 23888.89 10045.85 24000 23648.65 5930.4 7000 45000 38000 0.15
## kurtosis se
## X1 -0.73 1497.55
##
## $`2`
## vars n mean sd median trimmed mad min max range skew
## X1 1 80 25550 29854.46 22000 22515.62 4447.8 6000 280000 274000 7.76
## kurtosis se
## X1 63.03 3337.83
##
## attr(,"call")
## by.default(data = x, INDICES = group, FUN = describe, type = type)library(foreign)
r=read.dta("C:/Users/BINH THANG/Dropbox/Korea/STudy/Thesis/data management/DataR/dataR5.dta")
r1 <- r
attach(r1)## The following object is masked _by_ .GlobalEnv:
##
## a## The following objects are masked from newdata2 (pos = 3):
##
## a1, advice, ag, age_group, anticam, b1, b10, b10a1, b10a2,
## b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2, b11a3,
## b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a, b1a, b2,
## b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3, b6a4, b6a5,
## b6a6, b6a7, b6a7a, b7, b8, b9, br, branch, branch1, branch2,
## branch3, c1, c2, c23a, c3, c4, c5, c6, c7, c8, c9, COST,
## cost_inc, cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3,
## d3a, d4, d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1,
## educ2, f1, ghi1, ghi2, ghiro2, giadinhkoUH, group_age,
## group_age1, h1, h10a, h10a1, h10a10, h10a11, h10a11a, h10a2,
## h10a3, h10a4, h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a,
## h12a_1, h12log, h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000,
## itc1, itc2, l1, l2, l3, l4, l5, l6, label1, moneyspent, msdt,
## n01, n02, n03, n05, n06, n07, n08, n1, n10, n100, n101, n102,
## n103, n11, n12, n13, n14, n15, n16, n1b, n2, n3, n35, n36,
## n37, n38, n39, n3posterb, n4, n40, n41, n42, n43, n44, n45,
## n46, n47, n48, n49, n5, n50, n51, n52, n53, n54, n55, n56,
## n57, n58, n59, n6, n60, n61, n61a, n62, n62a, n63, n63a, n64,
## n64a, n65, n65a, n66, n66a, n67, n67a, n68, n68a, n7, n77,
## n78, n7tren, n8, n88, n89, n8nha, n9, n97, n98, n99, n9khach,
## noEnvi2, occup1, policy, policy_a, reasons, reasons1, s1,
## Screening, selfhealth, SH1, smostt, ter_fa1, ter_in,
## tertile_fa, tertile_indi, test, unitsdiffi1, var242, w1, w2,
## w3, w4## The following objects are masked from r1 (pos = 4):
##
## a1, advice, ag, age_group, anticam, b1, b10, b10a1, b10a2,
## b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2, b11a3,
## b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a, b1a, b2,
## b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3, b6a4, b6a5,
## b6a6, b6a7, b6a7a, b7, b8, b9, br, branch, branch1, branch2,
## branch3, c1, c2, c23a, c3, c4, c5, c6, c7, c8, c9, COST,
## cost_inc, cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3,
## d3a, d4, d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1,
## educ2, f1, ghi1, ghi2, ghiro2, giadinhkoUH, group_age,
## group_age1, h1, h10a, h10a1, h10a10, h10a11, h10a11a, h10a2,
## h10a3, h10a4, h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a,
## h12a_1, h12log, h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000,
## itc1, itc2, l1, l2, l3, l4, l5, l6, label1, moneyspent, msdt,
## n01, n02, n03, n05, n06, n07, n08, n1, n10, n100, n101, n102,
## n103, n11, n12, n13, n14, n15, n16, n1b, n2, n3, n35, n36,
## n37, n38, n39, n3posterb, n4, n40, n41, n42, n43, n44, n45,
## n46, n47, n48, n49, n5, n50, n51, n52, n53, n54, n55, n56,
## n57, n58, n59, n6, n60, n61, n61a, n62, n62a, n63, n63a, n64,
## n64a, n65, n65a, n66, n66a, n67, n67a, n68, n68a, n7, n77,
## n78, n7tren, n8, n88, n89, n8nha, n9, n97, n98, n99, n9khach,
## noEnvi2, occup1, policy, policy_a, reasons, reasons1, s1,
## Screening, selfhealth, SH1, smostt, ter_fa1, ter_in,
## tertile_fa, tertile_indi, test, unitsdiffi1, var242, w1, w2,
## w3, w4## The following objects are masked from r1 (pos = 5):
##
## a1, advice, ag, age_group, anticam, b1, b10, b10a1, b10a2,
## b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2, b11a3,
## b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a, b1a, b2,
## b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3, b6a4, b6a5,
## b6a6, b6a7, b6a7a, b7, b8, b9, br, branch, branch1, branch2,
## branch3, c1, c2, c23a, c3, c4, c5, c6, c7, c8, c9, COST,
## cost_inc, cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3,
## d3a, d4, d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1,
## educ2, f1, ghi1, ghi2, ghiro2, giadinhkoUH, group_age,
## group_age1, h1, h10a, h10a1, h10a10, h10a11, h10a11a, h10a2,
## h10a3, h10a4, h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a,
## h12a_1, h12log, h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000,
## itc1, itc2, l1, l2, l3, l4, l5, l6, label1, moneyspent, msdt,
## n01, n02, n03, n05, n06, n07, n08, n1, n10, n100, n101, n102,
## n103, n11, n12, n13, n14, n15, n16, n1b, n2, n3, n35, n36,
## n37, n38, n39, n3posterb, n4, n40, n41, n42, n43, n44, n45,
## n46, n47, n48, n49, n5, n50, n51, n52, n53, n54, n55, n56,
## n57, n58, n59, n6, n60, n61, n61a, n62, n62a, n63, n63a, n64,
## n64a, n65, n65a, n66, n66a, n67, n67a, n68, n68a, n7, n77,
## n78, n7tren, n8, n88, n89, n8nha, n9, n97, n98, n99, n9khach,
## noEnvi2, occup1, policy, policy_a, reasons, reasons1, s1,
## Screening, selfhealth, SH1, smostt, ter_fa1, ter_in,
## tertile_fa, tertile_indi, test, unitsdiffi1, var242, w1, w2,
## w3, w4## The following objects are masked from newdata2 (pos = 8):
##
## a1, advice, ag, age_group, anticam, b1, b10, b10a1, b10a2,
## b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2, b11a3,
## b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a, b1a, b2,
## b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3, b6a4, b6a5,
## b6a6, b6a7, b6a7a, b7, b8, b9, br, branch, branch1, branch2,
## branch3, c1, c2, c23a, c3, c4, c5, c6, c7, c8, c9, COST,
## cost_inc, cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3,
## d3a, d4, d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1,
## educ2, f1, ghi1, ghi2, ghiro2, giadinhkoUH, group_age,
## group_age1, h1, h10a, h10a1, h10a10, h10a11, h10a11a, h10a2,
## h10a3, h10a4, h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a,
## h12a_1, h12log, h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000,
## itc1, itc2, l1, l2, l3, l4, l5, l6, label1, moneyspent, msdt,
## n01, n02, n03, n05, n06, n07, n08, n1, n10, n100, n101, n102,
## n103, n11, n12, n13, n14, n15, n16, n1b, n2, n3, n35, n36,
## n37, n38, n39, n3posterb, n4, n40, n41, n42, n43, n44, n45,
## n46, n47, n48, n49, n5, n50, n51, n52, n53, n54, n55, n56,
## n57, n58, n59, n6, n60, n61, n61a, n62, n62a, n63, n63a, n64,
## n64a, n65, n65a, n66, n66a, n67, n67a, n68, n68a, n7, n77,
## n78, n7tren, n8, n88, n89, n8nha, n9, n97, n98, n99, n9khach,
## noEnvi2, occup1, policy, policy_a, reasons, reasons1, s1,
## Screening, selfhealth, SH1, smostt, ter_fa1, ter_in,
## tertile_fa, tertile_indi, test, unitsdiffi1, var242, w1, w2,
## w3, w4## The following objects are masked from r:
##
## a1, advice, ag, age_group, anticam, b1, b10, b10a1, b10a2,
## b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2, b11a3,
## b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a, b1a, b2,
## b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3, b6a4, b6a5,
## b6a6, b6a7, b6a7a, b7, b8, b9, br, branch, branch1, branch2,
## branch3, c1, c2, c23a, c3, c4, c5, c6, c7, c8, c9, COST,
## cost_inc, cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3,
## d3a, d4, d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1,
## educ2, f1, ghi1, ghi2, ghiro2, giadinhkoUH, group_age,
## group_age1, h1, h10a, h10a1, h10a10, h10a11, h10a11a, h10a2,
## h10a3, h10a4, h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a,
## h12a_1, h12log, h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000,
## itc1, itc2, l1, l2, l3, l4, l5, l6, label1, moneyspent, msdt,
## n01, n02, n03, n05, n06, n07, n08, n1, n10, n100, n101, n102,
## n103, n11, n12, n13, n14, n15, n16, n1b, n2, n3, n35, n36,
## n37, n38, n39, n3posterb, n4, n40, n41, n42, n43, n44, n45,
## n46, n47, n48, n49, n5, n50, n51, n52, n53, n54, n55, n56,
## n57, n58, n59, n6, n60, n61, n61a, n62, n62a, n63, n63a, n64,
## n64a, n65, n65a, n66, n66a, n67, n67a, n68, n68a, n7, n77,
## n78, n7tren, n8, n88, n89, n8nha, n9, n97, n98, n99, n9khach,
## noEnvi2, occup1, policy, policy_a, reasons, reasons1, s1,
## Screening, selfhealth, SH1, smostt, ter_fa1, ter_in,
## tertile_fa, tertile_indi, test, unitsdiffi1, var242, w1, w2,
## w3, w4## The following objects are masked from r1 (pos = 10):
##
## a1, advice, ag, age_group, anticam, b1, b10, b10a1, b10a2,
## b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2, b11a3,
## b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a, b1a, b2,
## b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3, b6a4, b6a5,
## b6a6, b6a7, b6a7a, b7, b8, b9, br, branch, branch1, branch2,
## branch3, c1, c2, c23a, c3, c4, c5, c6, c7, c8, c9, COST,
## cost_inc, cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3,
## d3a, d4, d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1,
## educ2, f1, ghi1, ghi2, ghiro2, giadinhkoUH, group_age,
## group_age1, h1, h10a, h10a1, h10a10, h10a11, h10a11a, h10a2,
## h10a3, h10a4, h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a,
## h12a_1, h12log, h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000,
## itc1, itc2, l1, l2, l3, l4, l5, l6, label1, moneyspent, msdt,
## n01, n02, n03, n05, n06, n07, n08, n1, n10, n100, n101, n102,
## n103, n11, n12, n13, n14, n15, n16, n1b, n2, n3, n35, n36,
## n37, n38, n39, n3posterb, n4, n40, n41, n42, n43, n44, n45,
## n46, n47, n48, n49, n5, n50, n51, n52, n53, n54, n55, n56,
## n57, n58, n59, n6, n60, n61, n61a, n62, n62a, n63, n63a, n64,
## n64a, n65, n65a, n66, n66a, n67, n67a, n68, n68a, n7, n77,
## n78, n7tren, n8, n88, n89, n8nha, n9, n97, n98, n99, n9khach,
## noEnvi2, occup1, policy, policy_a, reasons, reasons1, s1,
## Screening, selfhealth, SH1, smostt, ter_fa1, ter_in,
## tertile_fa, tertile_indi, test, unitsdiffi1, var242, w1, w2,
## w3, w4r1$wtp[cost_inc >=1] <- 0
r1$wtp[is.na(r1$wtp)] <- 1
r1$highper[cost_inc<=62000] <- 0
r1$highper[cost_inc>62000] <- 1
r1$b16a[b16a == 5] <- 0
r1$freeEn[c9==1] <- 1
r1$freeEn[c9>1] <- 0
r1$h1[h1== 1] <- 1
r1$h1[h1== 2] <- 0
r1$c7ad[c7== 2] <- 0
r1$c7ad[c7== 1] <- 1
r1$c7ad[is.na(r1$c7)] <- 0
r1$ant[c5==1& c5==2 & c5==7 & c5==8 & c5==9] <- 0
r1$ant[c5==3|c5==4|c5==5] <- 1
r1$ant[is.na(r1$c5)] <- 0
r1$p1=r1$label1+r1$freeEn+r1$ant+r1$c7ad
r1$p[r1$p1==0] <- 0
r1$p[r1$p1==1] <- 1
r1$p[r1$p1>=2] <- 2
newdata2=r1
attach(newdata2 )## The following object is masked _by_ .GlobalEnv:
##
## a## The following objects are masked from r1 (pos = 3):
##
## a, a1, advice, ag, age_group, anticam, b1, b10, b10a1, b10a2,
## b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2, b11a3,
## b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a, b1a,
## b1a1, b1a2, b1a3, b2, b2a1, b3, b4, b5, b5a, b6, b6_123, b6a,
## b6a1, b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9,
## br, branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4,
## c5, c6, c6a111, c7, c8, c9, clog, clog1, COST, cost_inc,
## cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3, d3a, d4,
## d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1, educ2, f1,
## ghi1, ghi2, ghiro2, giadinhkoUH, group_age, group_age1, h1,
## h10a, h10a1, h10a10, h10a11, h10a11a, h10a2, h10a3, h10a4,
## h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a, h12a_1, h12log,
## h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000, ict1a, ict2a,
## itc1, itc2, l1, l2, l3, l4, l5, l6, label_1, label1, label1a,
## logb7, logC, logitCost, moneyspent, msdt, n01, n02, n03, n05,
## n06, n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13,
## n14, n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39,
## n3posterb, n4, n40, n41, n42, n43, n44, n45, n46, n47, n48,
## n49, n5, n50, n51, n52, n53, n54, n55, n56, n57, n58, n59, n6,
## n60, n61, n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a,
## n66, n66a, n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8,
## n88, n89, n8nha, n9, n97, n98, n99, n9khach, noE, noEnvi2,
## occup1, poli4, poli4a, policy, policy_a, policyeffect,
## reasons, reasons1, s1, Screening, selfhealth, SH1, smostt,
## taxIn, ter_fa1, ter_in, tertile_fa, tertile_indi, test,
## unitsdiffi1, var242, w1, w2, w3, w4## The following objects are masked from newdata2 (pos = 4):
##
## a1, advice, ag, age_group, ant, anticam, b1, b10, b10a1,
## b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2,
## b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a,
## b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3,
## b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br, branch,
## branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5, c6, c7,
## c7ad, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, freeEn, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, moneyspent, msdt, n01, n02, n03, n05, n06, n07, n08,
## n1, n10, n100, n101, n102, n103, n11, n12, n13, n14, n15, n16,
## n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4, n40, n41,
## n42, n43, n44, n45, n46, n47, n48, n49, n5, n50, n51, n52,
## n53, n54, n55, n56, n57, n58, n59, n6, n60, n61, n61a, n62,
## n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a, n67, n67a,
## n68, n68a, n7, n77, n78, n7tren, n8, n88, n89, n8nha, n9, n97,
## n98, n99, n9khach, noEnvi2, occup1, p, p1, policy, policy_a,
## reasons, reasons1, s1, Screening, selfhealth, SH1, smostt,
## ter_fa1, ter_in, tertile_fa, tertile_indi, test, unitsdiffi1,
## var242, w1, w2, w3, w4## The following objects are masked from r1 (pos = 5):
##
## a1, advice, ag, age_group, ant, anticam, b1, b10, b10a1,
## b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2,
## b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a,
## b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3,
## b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br, branch,
## branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5, c6, c7,
## c7ad, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, freeEn, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, moneyspent, msdt, n01, n02, n03, n05, n06, n07, n08,
## n1, n10, n100, n101, n102, n103, n11, n12, n13, n14, n15, n16,
## n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4, n40, n41,
## n42, n43, n44, n45, n46, n47, n48, n49, n5, n50, n51, n52,
## n53, n54, n55, n56, n57, n58, n59, n6, n60, n61, n61a, n62,
## n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a, n67, n67a,
## n68, n68a, n7, n77, n78, n7tren, n8, n88, n89, n8nha, n9, n97,
## n98, n99, n9khach, noEnvi2, occup1, p, p1, policy, policy_a,
## reasons, reasons1, s1, Screening, selfhealth, SH1, smostt,
## ter_fa1, ter_in, tertile_fa, tertile_indi, test, unitsdiffi1,
## var242, w1, w2, w3, w4## The following objects are masked from r1 (pos = 6):
##
## a1, advice, ag, age_group, anticam, b1, b10, b10a1, b10a2,
## b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2, b11a3,
## b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a, b1a, b2,
## b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3, b6a4, b6a5,
## b6a6, b6a7, b6a7a, b7, b8, b9, br, branch, branch1, branch2,
## branch3, c1, c2, c23a, c3, c4, c5, c6, c7, c8, c9, COST,
## cost_inc, cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3,
## d3a, d4, d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1,
## educ2, f1, ghi1, ghi2, ghiro2, giadinhkoUH, group_age,
## group_age1, h1, h10a, h10a1, h10a10, h10a11, h10a11a, h10a2,
## h10a3, h10a4, h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a,
## h12a_1, h12log, h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000,
## itc1, itc2, l1, l2, l3, l4, l5, l6, label1, moneyspent, msdt,
## n01, n02, n03, n05, n06, n07, n08, n1, n10, n100, n101, n102,
## n103, n11, n12, n13, n14, n15, n16, n1b, n2, n3, n35, n36,
## n37, n38, n39, n3posterb, n4, n40, n41, n42, n43, n44, n45,
## n46, n47, n48, n49, n5, n50, n51, n52, n53, n54, n55, n56,
## n57, n58, n59, n6, n60, n61, n61a, n62, n62a, n63, n63a, n64,
## n64a, n65, n65a, n66, n66a, n67, n67a, n68, n68a, n7, n77,
## n78, n7tren, n8, n88, n89, n8nha, n9, n97, n98, n99, n9khach,
## noEnvi2, occup1, policy, policy_a, reasons, reasons1, s1,
## Screening, selfhealth, SH1, smostt, ter_fa1, ter_in,
## tertile_fa, tertile_indi, test, unitsdiffi1, var242, w1, w2,
## w3, w4## The following objects are masked from newdata2 (pos = 9):
##
## a1, advice, ag, age_group, ant, anticam, b1, b10, b10a1,
## b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2,
## b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a,
## b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3,
## b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br, branch,
## branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5, c6, c7,
## c7ad, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, freeEn, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, moneyspent, msdt, n01, n02, n03, n05, n06, n07, n08,
## n1, n10, n100, n101, n102, n103, n11, n12, n13, n14, n15, n16,
## n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4, n40, n41,
## n42, n43, n44, n45, n46, n47, n48, n49, n5, n50, n51, n52,
## n53, n54, n55, n56, n57, n58, n59, n6, n60, n61, n61a, n62,
## n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a, n67, n67a,
## n68, n68a, n7, n77, n78, n7tren, n8, n88, n89, n8nha, n9, n97,
## n98, n99, n9khach, noEnvi2, occup1, p, p1, policy, policy_a,
## reasons, reasons1, s1, Screening, selfhealth, SH1, smostt,
## ter_fa1, ter_in, tertile_fa, tertile_indi, test, unitsdiffi1,
## var242, w1, w2, w3, w4, wtp## The following objects are masked from r:
##
## a1, advice, ag, age_group, anticam, b1, b10, b10a1, b10a2,
## b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2, b11a3,
## b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a, b1a, b2,
## b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3, b6a4, b6a5,
## b6a6, b6a7, b6a7a, b7, b8, b9, br, branch, branch1, branch2,
## branch3, c1, c2, c23a, c3, c4, c5, c6, c7, c8, c9, COST,
## cost_inc, cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3,
## d3a, d4, d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1,
## educ2, f1, ghi1, ghi2, ghiro2, giadinhkoUH, group_age,
## group_age1, h1, h10a, h10a1, h10a10, h10a11, h10a11a, h10a2,
## h10a3, h10a4, h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a,
## h12a_1, h12log, h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000,
## itc1, itc2, l1, l2, l3, l4, l5, l6, label1, moneyspent, msdt,
## n01, n02, n03, n05, n06, n07, n08, n1, n10, n100, n101, n102,
## n103, n11, n12, n13, n14, n15, n16, n1b, n2, n3, n35, n36,
## n37, n38, n39, n3posterb, n4, n40, n41, n42, n43, n44, n45,
## n46, n47, n48, n49, n5, n50, n51, n52, n53, n54, n55, n56,
## n57, n58, n59, n6, n60, n61, n61a, n62, n62a, n63, n63a, n64,
## n64a, n65, n65a, n66, n66a, n67, n67a, n68, n68a, n7, n77,
## n78, n7tren, n8, n88, n89, n8nha, n9, n97, n98, n99, n9khach,
## noEnvi2, occup1, policy, policy_a, reasons, reasons1, s1,
## Screening, selfhealth, SH1, smostt, ter_fa1, ter_in,
## tertile_fa, tertile_indi, test, unitsdiffi1, var242, w1, w2,
## w3, w4## The following objects are masked from r1 (pos = 11):
##
## a1, advice, ag, age_group, anticam, b1, b10, b10a1, b10a2,
## b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2, b11a3,
## b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a, b1a, b2,
## b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3, b6a4, b6a5,
## b6a6, b6a7, b6a7a, b7, b8, b9, br, branch, branch1, branch2,
## branch3, c1, c2, c23a, c3, c4, c5, c6, c7, c8, c9, COST,
## cost_inc, cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3,
## d3a, d4, d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1,
## educ2, f1, ghi1, ghi2, ghiro2, giadinhkoUH, group_age,
## group_age1, h1, h10a, h10a1, h10a10, h10a11, h10a11a, h10a2,
## h10a3, h10a4, h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a,
## h12a_1, h12log, h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000,
## itc1, itc2, l1, l2, l3, l4, l5, l6, label1, moneyspent, msdt,
## n01, n02, n03, n05, n06, n07, n08, n1, n10, n100, n101, n102,
## n103, n11, n12, n13, n14, n15, n16, n1b, n2, n3, n35, n36,
## n37, n38, n39, n3posterb, n4, n40, n41, n42, n43, n44, n45,
## n46, n47, n48, n49, n5, n50, n51, n52, n53, n54, n55, n56,
## n57, n58, n59, n6, n60, n61, n61a, n62, n62a, n63, n63a, n64,
## n64a, n65, n65a, n66, n66a, n67, n67a, n68, n68a, n7, n77,
## n78, n7tren, n8, n88, n89, n8nha, n9, n97, n98, n99, n9khach,
## noEnvi2, occup1, policy, policy_a, reasons, reasons1, s1,
## Screening, selfhealth, SH1, smostt, ter_fa1, ter_in,
## tertile_fa, tertile_indi, test, unitsdiffi1, var242, w1, w2,
## w3, w4newdata2$wtp=factor(newdata2$wtp)
newdata2$age_group=as.factor(newdata2$age_group)
newdata2$educ2=as.factor(newdata2$educ2)
newdata2$h1=as.factor(newdata2$h1)
newdata2$d1a=as.factor(newdata2$d1a)
newdata2$selfhealth=as.factor(newdata2$selfhealth)
newdata2$b18a=as.factor(newdata2$b18a)
newdata2$b16a=as.factor(newdata2$b16a)
newdata2$b6a=as.factor(newdata2$b6a)
newdata2$smostt=as.factor(newdata2$smostt)
newdata2$ter_in=as.factor(newdata2$ter_in)
newdata2$group_age1=as.factor(newdata2$group_age1)
newdata2$label1=as.factor(newdata2$label1)
newdata2$freeEn=as.factor(newdata2$freeEn)
newdata2$c7ad=as.factor(newdata2$c7ad)
newdata2$ant=as.factor(newdata2$ant)
newdata2$p=as.factor(newdata2$p)
attach(newdata2)## The following object is masked _by_ .GlobalEnv:
##
## a## The following objects are masked from newdata2 (pos = 3):
##
## a, a1, advice, ag, age_group, ant, anticam, b1, b10, b10a1,
## b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2,
## b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a,
## b1a, b1a1, b1a2, b1a3, b2, b2a1, b3, b4, b5, b5a, b6, b6_123,
## b6a, b6a1, b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8,
## b9, br, branch, branch1, branch2, branch3, c1, c2, c23a, c3,
## c4, c5, c6, c6a111, c7, c7ad, c8, c9, clog, clog1, COST,
## cost_inc, cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3,
## d3a, d4, d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1,
## educ2, f1, freeEn, ghi1, ghi2, ghiro2, giadinhkoUH, group_age,
## group_age1, h1, h10a, h10a1, h10a10, h10a11, h10a11a, h10a2,
## h10a3, h10a4, h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a,
## h12a_1, h12log, h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000,
## highper, ict1a, ict2a, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label_1, label1, label1a, logb7, logC, logitCost, moneyspent,
## msdt, n01, n02, n03, n05, n06, n07, n08, n1, n10, n100, n101,
## n102, n103, n11, n12, n13, n14, n15, n16, n1b, n2, n3, n35,
## n36, n37, n38, n39, n3posterb, n4, n40, n41, n42, n43, n44,
## n45, n46, n47, n48, n49, n5, n50, n51, n52, n53, n54, n55,
## n56, n57, n58, n59, n6, n60, n61, n61a, n62, n62a, n63, n63a,
## n64, n64a, n65, n65a, n66, n66a, n67, n67a, n68, n68a, n7,
## n77, n78, n7tren, n8, n88, n89, n8nha, n9, n97, n98, n99,
## n9khach, noE, noEnvi2, occup1, p, p1, poli4, poli4a, policy,
## policy_a, policyeffect, reasons, reasons1, s1, Screening,
## selfhealth, SH1, smostt, taxIn, ter_fa1, ter_in, tertile_fa,
## tertile_indi, test, unitsdiffi1, var242, w1, w2, w3, w4, wtp## The following objects are masked from r1 (pos = 4):
##
## a, a1, advice, ag, age_group, anticam, b1, b10, b10a1, b10a2,
## b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2, b11a3,
## b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a, b1a,
## b1a1, b1a2, b1a3, b2, b2a1, b3, b4, b5, b5a, b6, b6_123, b6a,
## b6a1, b6a2, b6a3, b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9,
## br, branch, branch1, branch2, branch3, c1, c2, c23a, c3, c4,
## c5, c6, c6a111, c7, c8, c9, clog, clog1, COST, cost_inc,
## cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3, d3a, d4,
## d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1, educ2, f1,
## ghi1, ghi2, ghiro2, giadinhkoUH, group_age, group_age1, h1,
## h10a, h10a1, h10a10, h10a11, h10a11a, h10a2, h10a3, h10a4,
## h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a, h12a_1, h12log,
## h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000, ict1a, ict2a,
## itc1, itc2, l1, l2, l3, l4, l5, l6, label_1, label1, label1a,
## logb7, logC, logitCost, moneyspent, msdt, n01, n02, n03, n05,
## n06, n07, n08, n1, n10, n100, n101, n102, n103, n11, n12, n13,
## n14, n15, n16, n1b, n2, n3, n35, n36, n37, n38, n39,
## n3posterb, n4, n40, n41, n42, n43, n44, n45, n46, n47, n48,
## n49, n5, n50, n51, n52, n53, n54, n55, n56, n57, n58, n59, n6,
## n60, n61, n61a, n62, n62a, n63, n63a, n64, n64a, n65, n65a,
## n66, n66a, n67, n67a, n68, n68a, n7, n77, n78, n7tren, n8,
## n88, n89, n8nha, n9, n97, n98, n99, n9khach, noE, noEnvi2,
## occup1, poli4, poli4a, policy, policy_a, policyeffect,
## reasons, reasons1, s1, Screening, selfhealth, SH1, smostt,
## taxIn, ter_fa1, ter_in, tertile_fa, tertile_indi, test,
## unitsdiffi1, var242, w1, w2, w3, w4## The following objects are masked from newdata2 (pos = 5):
##
## a1, advice, ag, age_group, ant, anticam, b1, b10, b10a1,
## b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2,
## b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a,
## b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3,
## b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br, branch,
## branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5, c6, c7,
## c7ad, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, freeEn, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, moneyspent, msdt, n01, n02, n03, n05, n06, n07, n08,
## n1, n10, n100, n101, n102, n103, n11, n12, n13, n14, n15, n16,
## n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4, n40, n41,
## n42, n43, n44, n45, n46, n47, n48, n49, n5, n50, n51, n52,
## n53, n54, n55, n56, n57, n58, n59, n6, n60, n61, n61a, n62,
## n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a, n67, n67a,
## n68, n68a, n7, n77, n78, n7tren, n8, n88, n89, n8nha, n9, n97,
## n98, n99, n9khach, noEnvi2, occup1, p, p1, policy, policy_a,
## reasons, reasons1, s1, Screening, selfhealth, SH1, smostt,
## ter_fa1, ter_in, tertile_fa, tertile_indi, test, unitsdiffi1,
## var242, w1, w2, w3, w4## The following objects are masked from r1 (pos = 6):
##
## a1, advice, ag, age_group, ant, anticam, b1, b10, b10a1,
## b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2,
## b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a,
## b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3,
## b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br, branch,
## branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5, c6, c7,
## c7ad, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, freeEn, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, moneyspent, msdt, n01, n02, n03, n05, n06, n07, n08,
## n1, n10, n100, n101, n102, n103, n11, n12, n13, n14, n15, n16,
## n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4, n40, n41,
## n42, n43, n44, n45, n46, n47, n48, n49, n5, n50, n51, n52,
## n53, n54, n55, n56, n57, n58, n59, n6, n60, n61, n61a, n62,
## n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a, n67, n67a,
## n68, n68a, n7, n77, n78, n7tren, n8, n88, n89, n8nha, n9, n97,
## n98, n99, n9khach, noEnvi2, occup1, p, p1, policy, policy_a,
## reasons, reasons1, s1, Screening, selfhealth, SH1, smostt,
## ter_fa1, ter_in, tertile_fa, tertile_indi, test, unitsdiffi1,
## var242, w1, w2, w3, w4## The following objects are masked from r1 (pos = 7):
##
## a1, advice, ag, age_group, anticam, b1, b10, b10a1, b10a2,
## b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2, b11a3,
## b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a, b1a, b2,
## b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3, b6a4, b6a5,
## b6a6, b6a7, b6a7a, b7, b8, b9, br, branch, branch1, branch2,
## branch3, c1, c2, c23a, c3, c4, c5, c6, c7, c8, c9, COST,
## cost_inc, cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3,
## d3a, d4, d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1,
## educ2, f1, ghi1, ghi2, ghiro2, giadinhkoUH, group_age,
## group_age1, h1, h10a, h10a1, h10a10, h10a11, h10a11a, h10a2,
## h10a3, h10a4, h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a,
## h12a_1, h12log, h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000,
## itc1, itc2, l1, l2, l3, l4, l5, l6, label1, moneyspent, msdt,
## n01, n02, n03, n05, n06, n07, n08, n1, n10, n100, n101, n102,
## n103, n11, n12, n13, n14, n15, n16, n1b, n2, n3, n35, n36,
## n37, n38, n39, n3posterb, n4, n40, n41, n42, n43, n44, n45,
## n46, n47, n48, n49, n5, n50, n51, n52, n53, n54, n55, n56,
## n57, n58, n59, n6, n60, n61, n61a, n62, n62a, n63, n63a, n64,
## n64a, n65, n65a, n66, n66a, n67, n67a, n68, n68a, n7, n77,
## n78, n7tren, n8, n88, n89, n8nha, n9, n97, n98, n99, n9khach,
## noEnvi2, occup1, policy, policy_a, reasons, reasons1, s1,
## Screening, selfhealth, SH1, smostt, ter_fa1, ter_in,
## tertile_fa, tertile_indi, test, unitsdiffi1, var242, w1, w2,
## w3, w4## The following objects are masked from newdata2 (pos = 10):
##
## a1, advice, ag, age_group, ant, anticam, b1, b10, b10a1,
## b10a2, b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2,
## b11a3, b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a,
## b1a, b2, b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3,
## b6a4, b6a5, b6a6, b6a7, b6a7a, b7, b8, b9, br, branch,
## branch1, branch2, branch3, c1, c2, c23a, c3, c4, c5, c6, c7,
## c7ad, c8, c9, COST, cost_inc, cost1, costincrease, ct, d1,
## d10, d11, d1a, d2, d3, d3a, d4, d5, d6, d7, d8, d9, Decision,
## e1, e2, edu, educ1, educ2, f1, freeEn, ghi1, ghi2, ghiro2,
## giadinhkoUH, group_age, group_age1, h1, h10a, h10a1, h10a10,
## h10a11, h10a11a, h10a2, h10a3, h10a4, h10a5, h10a6, h10a7,
## h10a8, h10a9, h12, h12a, h12a_1, h12log, h13, h2, h3, h4, h5,
## h6, h7, h8, h9, ha000, itc1, itc2, l1, l2, l3, l4, l5, l6,
## label1, moneyspent, msdt, n01, n02, n03, n05, n06, n07, n08,
## n1, n10, n100, n101, n102, n103, n11, n12, n13, n14, n15, n16,
## n1b, n2, n3, n35, n36, n37, n38, n39, n3posterb, n4, n40, n41,
## n42, n43, n44, n45, n46, n47, n48, n49, n5, n50, n51, n52,
## n53, n54, n55, n56, n57, n58, n59, n6, n60, n61, n61a, n62,
## n62a, n63, n63a, n64, n64a, n65, n65a, n66, n66a, n67, n67a,
## n68, n68a, n7, n77, n78, n7tren, n8, n88, n89, n8nha, n9, n97,
## n98, n99, n9khach, noEnvi2, occup1, p, p1, policy, policy_a,
## reasons, reasons1, s1, Screening, selfhealth, SH1, smostt,
## ter_fa1, ter_in, tertile_fa, tertile_indi, test, unitsdiffi1,
## var242, w1, w2, w3, w4, wtp## The following objects are masked from r:
##
## a1, advice, ag, age_group, anticam, b1, b10, b10a1, b10a2,
## b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2, b11a3,
## b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a, b1a, b2,
## b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3, b6a4, b6a5,
## b6a6, b6a7, b6a7a, b7, b8, b9, br, branch, branch1, branch2,
## branch3, c1, c2, c23a, c3, c4, c5, c6, c7, c8, c9, COST,
## cost_inc, cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3,
## d3a, d4, d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1,
## educ2, f1, ghi1, ghi2, ghiro2, giadinhkoUH, group_age,
## group_age1, h1, h10a, h10a1, h10a10, h10a11, h10a11a, h10a2,
## h10a3, h10a4, h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a,
## h12a_1, h12log, h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000,
## itc1, itc2, l1, l2, l3, l4, l5, l6, label1, moneyspent, msdt,
## n01, n02, n03, n05, n06, n07, n08, n1, n10, n100, n101, n102,
## n103, n11, n12, n13, n14, n15, n16, n1b, n2, n3, n35, n36,
## n37, n38, n39, n3posterb, n4, n40, n41, n42, n43, n44, n45,
## n46, n47, n48, n49, n5, n50, n51, n52, n53, n54, n55, n56,
## n57, n58, n59, n6, n60, n61, n61a, n62, n62a, n63, n63a, n64,
## n64a, n65, n65a, n66, n66a, n67, n67a, n68, n68a, n7, n77,
## n78, n7tren, n8, n88, n89, n8nha, n9, n97, n98, n99, n9khach,
## noEnvi2, occup1, policy, policy_a, reasons, reasons1, s1,
## Screening, selfhealth, SH1, smostt, ter_fa1, ter_in,
## tertile_fa, tertile_indi, test, unitsdiffi1, var242, w1, w2,
## w3, w4## The following objects are masked from r1 (pos = 12):
##
## a1, advice, ag, age_group, anticam, b1, b10, b10a1, b10a2,
## b10a3, b10a4, b10a5, b10a6, b10a7, b11, b11a, b11a2, b11a3,
## b12, b12a, b13, b14, b15, b16, b16a, b17, b18, b18a, b1a, b2,
## b2a1, b3, b4, b5, b5a, b6, b6a, b6a1, b6a2, b6a3, b6a4, b6a5,
## b6a6, b6a7, b6a7a, b7, b8, b9, br, branch, branch1, branch2,
## branch3, c1, c2, c23a, c3, c4, c5, c6, c7, c8, c9, COST,
## cost_inc, cost1, costincrease, ct, d1, d10, d11, d1a, d2, d3,
## d3a, d4, d5, d6, d7, d8, d9, Decision, e1, e2, edu, educ1,
## educ2, f1, ghi1, ghi2, ghiro2, giadinhkoUH, group_age,
## group_age1, h1, h10a, h10a1, h10a10, h10a11, h10a11a, h10a2,
## h10a3, h10a4, h10a5, h10a6, h10a7, h10a8, h10a9, h12, h12a,
## h12a_1, h12log, h13, h2, h3, h4, h5, h6, h7, h8, h9, ha000,
## itc1, itc2, l1, l2, l3, l4, l5, l6, label1, moneyspent, msdt,
## n01, n02, n03, n05, n06, n07, n08, n1, n10, n100, n101, n102,
## n103, n11, n12, n13, n14, n15, n16, n1b, n2, n3, n35, n36,
## n37, n38, n39, n3posterb, n4, n40, n41, n42, n43, n44, n45,
## n46, n47, n48, n49, n5, n50, n51, n52, n53, n54, n55, n56,
## n57, n58, n59, n6, n60, n61, n61a, n62, n62a, n63, n63a, n64,
## n64a, n65, n65a, n66, n66a, n67, n67a, n68, n68a, n7, n77,
## n78, n7tren, n8, n88, n89, n8nha, n9, n97, n98, n99, n9khach,
## noEnvi2, occup1, policy, policy_a, reasons, reasons1, s1,
## Screening, selfhealth, SH1, smostt, ter_fa1, ter_in,
## tertile_fa, tertile_indi, test, unitsdiffi1, var242, w1, w2,
## w3, w4data1=subset(newdata2, select=c( "age_group", "d1a", "educ2", "ter_in", "selfhealth", "c1", "smostt","b6a", "h1", "b18a", "b16a","label1", "freeEn", "c7ad", "ant", "p", "wtp"))
attach(data1)## The following objects are masked from newdata2 (pos = 3):
##
## age_group, ant, b16a, b18a, b6a, c1, c7ad, d1a, educ2, freeEn,
## h1, label1, p, selfhealth, smostt, ter_in, wtp## The following objects are masked from newdata2 (pos = 4):
##
## age_group, ant, b16a, b18a, b6a, c1, c7ad, d1a, educ2, freeEn,
## h1, label1, p, selfhealth, smostt, ter_in, wtp## The following objects are masked from r1 (pos = 5):
##
## age_group, b16a, b18a, b6a, c1, d1a, educ2, h1, label1,
## selfhealth, smostt, ter_in## The following objects are masked from newdata2 (pos = 6):
##
## age_group, ant, b16a, b18a, b6a, c1, c7ad, d1a, educ2, freeEn,
## h1, label1, p, selfhealth, smostt, ter_in## The following objects are masked from r1 (pos = 7):
##
## age_group, ant, b16a, b18a, b6a, c1, c7ad, d1a, educ2, freeEn,
## h1, label1, p, selfhealth, smostt, ter_in## The following objects are masked from r1 (pos = 8):
##
## age_group, b16a, b18a, b6a, c1, d1a, educ2, h1, label1,
## selfhealth, smostt, ter_in## The following objects are masked from newdata2 (pos = 11):
##
## age_group, ant, b16a, b18a, b6a, c1, c7ad, d1a, educ2, freeEn,
## h1, label1, p, selfhealth, smostt, ter_in, wtp## The following objects are masked from r:
##
## age_group, b16a, b18a, b6a, c1, d1a, educ2, h1, label1,
## selfhealth, smostt, ter_in## The following objects are masked from r1 (pos = 13):
##
## age_group, b16a, b18a, b6a, c1, d1a, educ2, h1, label1,
## selfhealth, smostt, ter_inlibrary(moonBook)## Warning: package 'moonBook' was built under R version 3.2.5mytable(wtp~., data=data1)##
## Descriptive Statistics by 'wtp'
## _____________________________________________
## 0 1 p
## (N=461) (N=362)
## ---------------------------------------------
## age_group 0.026
## - group18-29 191 (41.4%) 111 (30.7%)
## - gr3039 76 (16.5%) 64 (17.7%)
## - gr4049 94 (20.4%) 90 (24.9%)
## - gr5059 73 (15.8%) 65 (18.0%)
## - 60plus 27 ( 5.9%) 31 ( 8.6%)
## d1a 0.301
## - none 180 (39.0%) 127 (35.3%)
## - married 281 (61.0%) 233 (64.7%)
## educ2 0.017
## - 1 96 (21.2%) 104 (29.1%)
## - 2 220 (48.7%) 144 (40.3%)
## - 3 136 (30.1%) 109 (30.5%)
## ter_in 0.108
## - 1 191 (42.2%) 125 (35.0%)
## - 2 121 (26.7%) 103 (28.9%)
## - 3 141 (31.1%) 129 (36.1%)
## selfhealth 0.526
## - notwell 254 (55.1%) 190 (52.6%)
## - good 207 (44.9%) 171 (47.4%)
## c1 0.043
## - 1 398 (86.3%) 329 (91.1%)
## - 2 63 (13.7%) 32 ( 8.9%)
## smostt 0.000
## - light 127 (27.5%) 85 (23.5%)
## - medium 173 (37.5%) 101 (28.0%)
## - heavy 161 (34.9%) 175 (48.5%)
## b6a 0.004
## - no 377 (83.2%) 325 (90.5%)
## - yes 76 (16.8%) 34 ( 9.5%)
## h1 0.038
## - 0 169 (36.7%) 159 (44.0%)
## - 1 292 (63.3%) 202 (56.0%)
## b18a 0.002
## - Good 154 (33.6%) 159 (44.3%)
## - bad 304 (66.4%) 200 (55.7%)
## b16a 0.000
## - 0 64 (13.9%) 110 (30.6%)
## - 1 395 (86.1%) 250 (69.4%)
## label1 0.001
## - 0 383 (83.3%) 265 (73.6%)
## - 1 77 (16.7%) 95 (26.4%)
## freeEn 0.305
## - 0 346 (75.4%) 284 (78.7%)
## - 1 113 (24.6%) 77 (21.3%)
## c7ad 0.242
## - 0 302 (65.5%) 252 (69.6%)
## - 1 159 (34.5%) 110 (30.4%)
## ant 0.002
## - 0 244 (52.9%) 152 (42.0%)
## - 1 217 (47.1%) 210 (58.0%)
## p 0.074
## - 0 134 (29.2%) 85 (23.6%)
## - 1 145 (31.6%) 107 (29.7%)
## - 2 180 (39.2%) 168 (46.7%)
## ---------------------------------------------out=mytable(wtp~.,data=data1)
myhtml(out) ## <head><style>
## table, th, td {
## border: 1px solid #bcbcbc;
## } </style></head>
## <table cellpadding=10 cellspacing=5><caption>Descriptive Statistics by 'wtp'</caption><tr>
## <th>wtp</th><th>0<br/>(N=461)</th><th>1<br/>(N=362)</th><th>p</th></tr>
## <tr><td>age_group </td><td></td><td></td><td>0.026</td></tr>
## <tr><td> group18-29</td><td>191 (41.4%)</td><td>111 (30.7%)</td><td></td></tr>
## <tr><td> gr3039 </td><td>76 (16.5%)</td><td>64 (17.7%)</td><td></td></tr>
## <tr><td> gr4049 </td><td>94 (20.4%)</td><td>90 (24.9%)</td><td></td></tr>
## <tr><td> gr5059 </td><td>73 (15.8%)</td><td>65 (18.0%)</td><td></td></tr>
## <tr><td> 60plus </td><td>27 ( 5.9%)</td><td>31 ( 8.6%)</td><td></td></tr>
## <tr><td>d1a </td><td></td><td></td><td>0.301</td></tr>
## <tr><td> none </td><td>180 (39.0%)</td><td>127 (35.3%)</td><td></td></tr>
## <tr><td> married </td><td>281 (61.0%)</td><td>233 (64.7%)</td><td></td></tr>
## <tr><td>educ2 </td><td></td><td></td><td>0.017</td></tr>
## <tr><td> 1 </td><td>96 (21.2%)</td><td>104 (29.1%)</td><td></td></tr>
## <tr><td> 2 </td><td>220 (48.7%)</td><td>144 (40.3%)</td><td></td></tr>
## <tr><td> 3 </td><td>136 (30.1%)</td><td>109 (30.5%)</td><td></td></tr>
## <tr><td>ter_in </td><td></td><td></td><td>0.108</td></tr>
## <tr><td> 1 </td><td>191 (42.2%)</td><td>125 (35.0%)</td><td></td></tr>
## <tr><td> 2 </td><td>121 (26.7%)</td><td>103 (28.9%)</td><td></td></tr>
## <tr><td> 3 </td><td>141 (31.1%)</td><td>129 (36.1%)</td><td></td></tr>
## <tr><td>selfhealth </td><td></td><td></td><td>0.526</td></tr>
## <tr><td> notwell </td><td>254 (55.1%)</td><td>190 (52.6%)</td><td></td></tr>
## <tr><td> good </td><td>207 (44.9%)</td><td>171 (47.4%)</td><td></td></tr>
## <tr><td>c1 </td><td></td><td></td><td>0.043</td></tr>
## <tr><td> 1 </td><td>398 (86.3%)</td><td>329 (91.1%)</td><td></td></tr>
## <tr><td> 2 </td><td>63 (13.7%)</td><td>32 ( 8.9%)</td><td></td></tr>
## <tr><td>smostt </td><td></td><td></td><td>0.000</td></tr>
## <tr><td> light </td><td>127 (27.5%)</td><td>85 (23.5%)</td><td></td></tr>
## <tr><td> medium </td><td>173 (37.5%)</td><td>101 (28.0%)</td><td></td></tr>
## <tr><td> heavy </td><td>161 (34.9%)</td><td>175 (48.5%)</td><td></td></tr>
## <tr><td>b6a </td><td></td><td></td><td>0.004</td></tr>
## <tr><td> no </td><td>377 (83.2%)</td><td>325 (90.5%)</td><td></td></tr>
## <tr><td> yes </td><td>76 (16.8%)</td><td>34 ( 9.5%)</td><td></td></tr>
## <tr><td>h1 </td><td></td><td></td><td>0.038</td></tr>
## <tr><td> 0 </td><td>169 (36.7%)</td><td>159 (44.0%)</td><td></td></tr>
## <tr><td> 1 </td><td>292 (63.3%)</td><td>202 (56.0%)</td><td></td></tr>
## <tr><td>b18a </td><td></td><td></td><td>0.002</td></tr>
## <tr><td> Good </td><td>154 (33.6%)</td><td>159 (44.3%)</td><td></td></tr>
## <tr><td> bad </td><td>304 (66.4%)</td><td>200 (55.7%)</td><td></td></tr>
## <tr><td>b16a </td><td></td><td></td><td>0.000</td></tr>
## <tr><td> 0 </td><td>64 (13.9%)</td><td>110 (30.6%)</td><td></td></tr>
## <tr><td> 1 </td><td>395 (86.1%)</td><td>250 (69.4%)</td><td></td></tr>
## <tr><td>label1 </td><td></td><td></td><td>0.001</td></tr>
## <tr><td> 0 </td><td>383 (83.3%)</td><td>265 (73.6%)</td><td></td></tr>
## <tr><td> 1 </td><td>77 (16.7%)</td><td>95 (26.4%)</td><td></td></tr>
## <tr><td>freeEn </td><td></td><td></td><td>0.305</td></tr>
## <tr><td> 0 </td><td>346 (75.4%)</td><td>284 (78.7%)</td><td></td></tr>
## <tr><td> 1 </td><td>113 (24.6%)</td><td>77 (21.3%)</td><td></td></tr>
## <tr><td>c7ad </td><td></td><td></td><td>0.242</td></tr>
## <tr><td> 0 </td><td>302 (65.5%)</td><td>252 (69.6%)</td><td></td></tr>
## <tr><td> 1 </td><td>159 (34.5%)</td><td>110 (30.4%)</td><td></td></tr>
## <tr><td>ant </td><td></td><td></td><td>0.002</td></tr>
## <tr><td> 0 </td><td>244 (52.9%)</td><td>152 (42.0%)</td><td></td></tr>
## <tr><td> 1 </td><td>217 (47.1%)</td><td>210 (58.0%)</td><td></td></tr>
## <tr><td>p </td><td></td><td></td><td>0.074</td></tr>
## <tr><td> 0 </td><td>134 (29.2%)</td><td>85 (23.6%)</td><td></td></tr>
## <tr><td> 1 </td><td>145 (31.6%)</td><td>107 (29.7%)</td><td></td></tr>
## <tr><td> 2 </td><td>180 (39.2%)</td><td>168 (46.7%)</td><td></td></tr>
## </table>