項目反応理論
data<-read.csv("gaku1.csv")
head(data)
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data2 <- subset(data,select=c("V2","V6","V7","V8","V11","V12","V14","V15","V16","V17","V18","V19","V20","V21","V22","V23","V24","V25","V26","V29","V30","V32","V33","V34","V35","V38","V40","V44","V46","V49"))
data3 <- subset(data,select=c("V2","V6","V7"))
head(data3)
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1母数モデル
ans1<-rasch(data3)
ans1$coef[1:3,1:2]
## beta.i beta
## V2 1.1109080 0.74338
## V6 0.9659537 0.74338
## V7 1.9877085 0.74338
ans1
##
## Call:
## rasch(data = data3)
##
## Coefficients:
## Dffclt.V2 Dffclt.V6 Dffclt.V7 Dscrmn
## -1.494 -1.299 -2.674 0.743
##
## Log.Lik: -359.169
par(mfrow = c(1, 3))
plot(ans1, type = "ICC")#項目特性曲線
plot(ans1, type = "IIC")#項目情報曲線
plot(ans1, type = "IIC", items = 0)#テスト情報曲線
2母数モデル
ans2 <- ltm(data3 ~ z1)
ans2$coef[1:3,1:2]
## (Intercept) z1
## V2 1.0699909 0.5880481
## V6 0.9300407 0.5867876
## V7 2.3083251 1.2900666
ans2
##
## Call:
## ltm(formula = data3 ~ z1)
##
## Coefficients:
## Dffclt Dscrmn
## V2 -1.820 0.588
## V6 -1.585 0.587
## V7 -1.789 1.290
##
## Log.Lik: -358.96
par(mfrow = c(1, 3))
plot(ans2, type = "ICC")#項目特性曲線
plot(ans2, type = "IIC")#項目情報曲線
plot(ans2, type = "IIC", items = 0)#テスト情報曲線