#図3-2の分析
library(lavaan)
#パッケージMBESSを使用（要パッケージインストール）
library(MBESS)
data(HS.data)
hsdata<-HS.data
colnames(hsdata)
<- c("x1", "x2", "x3","x4",
"x5", "x6","x7", "x8",
"x9","x10", "x11",
"x12","x13", "x14", "x15","x16",
"x17", "x18","x19", "x20",
"x21","x22", "x23",
"x24","x25", "x26",
"x27","x28", "x29", "x30",
"x31", "x32")
#モデル指定
model.fig3.2
<- '
f1
=~ 1*x7+x8+x9+x10
#f1→x7のパス係数を1に固定
f2
=~ 1*x11+x12+x13+x14+x15 #f2→x11のパス係数を1に固定
f3
=~ 1*x16+x17+x18+x19
#f3→x16のパス係数を1に固定
f4
=~ 1*x20+x21+x22+x23+x24+x25
#f4→x20のパス係数を1に固定
x7
~~ x7
x8
~~ x8
x9
~~ x9
x10
~~ x10
x11
~~ x11
x12
~~ x12
x13
~~ x13
x14
~~ x14
x15
~~ x15
x16
~~ x16
x17
~~ x17
x18
~~ x18
x19
~~ x19
x20
~~ x20
x21
~~ x21
x22
~~ x22
x23
~~ x23
x24
~~ x24
x25
~~ x25
f1
~~ f1 #f1の分散を1に固定していないことに注意
f2
~~ f2 #f2の分散を1に固定していないことに注意
f3
~~ f3 #f3の分散を1に固定していないことに注意
f4
~~ f4 #f4の分散を1に固定していないことに注意
f1
~~ f2
f1
~~ f3
f1
~~ f4
f2
~~ f3
f2
~~ f4
f3
~~ f4
'
#lavaanを実行する
fit.fig3.2
<- lavaan(model.fig3.2, data=hsdata[,7:25])
#結果を出力する（図3-2）
summary(fit.fig3.2,
standardized=T, rsquare=T, fit.measure=T)
#====================================================
#図3-3の分析
library(lavaan)
library(MBESS)
data(HS.data)
hsdata<-HS.data
colnames(hsdata)
<- c("x1", "x2", "x3","x4",
"x5", "x6","x7", "x8",
"x9","x10", "x11",
"x12","x13", "x14", "x15","x16",
"x17", "x18","x19", "x20",
"x21","x22", "x23",
"x24","x25", "x26",
"x27","x28", "x29", "x30",
"x31", "x32")
#モデル指定
model.fig3.3
<- '
f1
=~ 1*x7+x8+x9+x10
f2
=~ 1*x11+x12+x13+x14+x15
f3
=~ 1*x16+x17+x18+x19
f4
=~ 1*x20+x21+x22+x23+x24+x25
f5
=~ f1+f2+f3+f4
#f5は、f1〜f4によって測定される二次因子
x7
~~ x7
x8
~~ x8
x9
~~ x9
x10
~~ x10
x11
~~ x11
x12
~~ x12
x13
~~ x13
x14
~~ x14
x15
~~ x15
x16
~~ x16
x17
~~ x17
x18
~~ x18
x19
~~ x19
x20
~~ x20
x21
~~ x21
x22
~~ x22
x23
~~ x23
x24
~~ x24
x25
~~ x25
f1
~~ f1
f2
~~ f2
f3
~~ f3
f4
~~ f4
f5
~~ 1*f5
#二次因子f5の分散を1に固定
'
#lavaanを実行する
fit.fig3.3
<- lavaan(model.fig3.3, data=hsdata[,7:25])
#結果を出力する（表3-1，図3-3）
summary(fit.fig3.3,
standardized=T, rsquare=T, fit.measure=T)
#====================================================
#図3-4, 3-5の分析
library(lavaan)
library(MBESS)
data(HS.data)
hsdata<-HS.data
colnames(hsdata)
<- c("x1", "x2", "x3","x4",
"x5", "x6","x7", "x8",
"x9","x10", "x11",
"x12","x13", "x14",
"x15","x16", "x17",
"x18","x19", "x20",
"x21","x22", "x23",
"x24","x25", "x26",
"x27","x28", "x29", "x30",
"x31", "x32")
#モデル指定
model.fig3.4
<- '
f1
=~ x7+x8+x9
x7
~~ x7
x8
~~ x8
x9
~~ x9
f1
~~ 1*f1
'
#lavaanを実行する
fit.fig3.4
<- lavaan(model.fig3.4, data=hsdata[,7:9])
#結果を出力する（図3-4）
summary(fit.fig3.4,
standardized=T, rsquare=T, fit.measure=T)
#モデル指定
model.fig3.5
<- '
f1
=~ 1*x7+x8+x9
x7
~~ x7
x8
~~ x8
x9
~~ x9
f1
~~ f1
'
#lavaanを実行する
fit.fig3.5
<- lavaan(model.fig3.5, data=hsdata[,7:9])
#結果を出力する（図3-5）
summary(fit.fig3.5,
standardized=T, rsquare=T, fit.measure=T)
#====================================================
#図3-6, 3-7の分析
library(lavaan)
library(MBESS)
data(HS.data)
hsdata<-HS.data
colnames(hsdata)
<- c("x1", "x2", "x3","x4",
"x5", "x6","x7", "x8",
"x9","x10", "x11",
"x12","x13", "x14",
"x15","x16", "x17",
"x18","x19", "x20",
"x21","x22", "x23",
"x24","x25", "x26",
"x27","x28", "x29", "x30",
"x31", "x32")
#モデル指定
model.fig3.6
<- '
f1
=~ 1*x7+x8+x9+x10
f2
=~ 1*x11+x12+x13+x14+x15
f3
=~ 1*x16+x17+x18+x19
x7
~~ x7
x8
~~ x8
x9
~~ x9
x10
~~ x10
x11
~~ x11
x12
~~ x12
x13
~~ x13
x14
~~ x14
x15
~~ x15
x16
~~ x16
x17
~~ x17
x18
~~ x18
x19
~~ x19
f1
~~ f1
f2
~~ f2
f3
~~ f3
f1
~~ f2
f1
~~ f3
f2
~~ f3
'
#lavaanを実行する
fit.fig3.6
<- lavaan(model.fig3.6, data=hsdata[,7:19])
#結果を出力する（図3-6）
summary(fit.fig3.6,
standardized=T, rsquare=T, fit.measure=T)
#モデル指定
model.fig3.7
<- '
f1
=~ 1*x7+x8+x9+x10
f2
=~ 1*x11+x12+x13+x14+x15
f3
=~ 1*x16+x17+x18+x19
f4
=~ f1+f2+f3
x7
~~ x7
x8
~~ x8
x9
~~ x9
x10
~~ x10
x11
~~ x11
x12
~~ x12
x13
~~ x13
x14
~~ x14
x15
~~ x15
x16
~~ x16
x17
~~ x17
x18
~~ x18
x19
~~ x19
f1
~~ f1
f2
~~ f2
f3
~~ f3
f4
~~ 1*f4
'
#lavaanを実行する
fit.fig3.7
<- lavaan(model.fig3.7, data=hsdata[,7:19])
#結果を出力する（図3-7）
summary(fit.fig3.7,
standardized=T, rsquare=T, fit.measure=T)
#====================================================
#図3-8, 3-9の分析
library(lavaan)
library(MBESS)
data(HS.data)
hsdata<-HS.data
colnames(hsdata)
<- c("x1", "x2", "x3","x4",
"x5", "x6","x7", "x8",
"x9","x10", "x11",
"x12","x13", "x14",
"x15","x16", "x17",
"x18","x19", "x20",
"x21","x22", "x23",
"x24","x25", "x26",
"x27","x28", "x29", "x30",
"x31", "x32")
#モデル指定
model.fig3.8
<- '
f1
=~ 1*x7+x8+x9+x10
f2
=~ 1*x11+x12+x13+x14+x15
x7
~~ x7
x8
~~ x8
x9
~~ x9
x10
~~ x10
x11
~~ x11
x12
~~ x12
x13
~~ x13
x14
~~ x14
x15
~~ x15
f1
~~ f1
f2
~~ f2
f1
~~ f2
'
#lavaanを実行する
fit.fig3.8
<- lavaan(model.fig3.8, data=hsdata[,7:15])
#結果を出力する（図3-8）
summary(fit.fig3.8,
standardized=T, rsquare=T, fit.measure=T)
#モデル指定
model.fig3.9
<- '
f1
=~ 1*x7+x8+x9+x10
f2
=~ 1*x11+x12+x13+x14+x15
f3
=~ a*f1+a*f2
x7
~~ x7
x8
~~ x8
x9
~~ x9
x10
~~ x10
x11
~~ x11
x12
~~ x12
x13
~~ x13
x14
~~ x14
x15
~~ x15
f1
~~ f1
f2
~~ f2
f3
~~ 1*f3
'
#lavaanを実行する
fit.fig3.9
<- lavaan(model.fig3.9, data=hsdata[,7:15])
#結果を出力する（図3-9）
summary(fit.fig3.9,
standardized=T, rsquare=T, fit.measure=T)
#====================================================
#図3-10の分析
library(lavaan)
library(psych)
#NAを含むデータを除外する
bfi2<-na.omit(bfi)
#逆転項目の処理
bfi2$A1<-bfi2$A1*-1+7
bfi2$C4<-bfi2$C4*-1+7
bfi2$C5<-bfi2$C5*-1+7
bfi2$E1<-bfi2$E1*-1+7
bfi2$E2<-bfi2$E2*-1+7
bfi2$O2<-bfi2$O2*-1+7
bfi2$O5<-bfi2$O5*-1+7
#モデル指定
model.fig3.10
<- '
f1
=~ 1*A1+A2+A3+A4+A5
f2
=~ 1*C1+C2+C3+C4+C5
f3
=~ 1*E1+E2+E3+E4+E5
f4
=~ 1*N1+N2+N3+N4+N5
f5
=~ 1*O1+O2+O3+O4+O5
f12
=~ f1+f2
f35
=~ f3+f5
A1
~~ A1
A2
~~ A2
A3
~~ A3
A4
~~ A4
A5
~~ A5
C1
~~ C1
C2
~~ C2
C3
~~ C3
C4
~~ C4
C5
~~ C5
E1
~~ E1
E2
~~ E2
E3
~~ E3
E4
~~ E4
E5
~~ E5
N1
~~ N1
N2
~~ N2
N3
~~ N3
N4
~~ N4
N5
~~ N5
O1
~~ O1
O2
~~ O2
O3
~~ O3
O4
~~ O4
O5
~~ O5
f1
~~ f1
f2
~~ f2
f3
~~ f3
f4
~~ f4
f5
~~ f5
f12
~~ 1*f12
f35
~~ 1*f35
f12
~~ f4
f12
~~ f35
f4
~~ f35
'
#lavaanを実行する
fit.fig3.10
<- lavaan(model.fig3.10, data=bfi2[,1:25])
#結果を出力する（図3-10）
summary(fit.fig3.10,
standardized=T, rsquare=T, fit.measure=T)
#====================================================
#2014.09.15 尾崎幸謙・荘島宏二郎