Dataset from Janssen and Geiser (2010)
Dataset used in Janssen and Geiser (2010).
data(data.janssen) data(data.janssen2)
data.janssen is a data frame with 346 observations on the 8
items of the following format
'data.frame': 346 obs. of 8 variables: $ PIS1 : num 1 1 1 0 0 1 1 1 0 1 ... $ PIS3 : num 0 1 1 1 1 1 0 1 1 1 ... $ PIS4 : num 1 1 1 1 1 1 1 1 1 1 ... $ PIS5 : num 0 1 1 0 1 1 1 1 1 0 ... $ SCR6 : num 1 1 1 1 1 1 1 1 1 0 ... $ SCR9 : num 1 1 1 1 0 0 0 1 0 0 ... $ SCR10: num 0 0 0 0 0 0 0 0 0 0 ... $ SCR17: num 0 0 0 0 0 1 0 0 0 0 ...
data.janssen2 contains 20 IST items:
'data.frame': 346 obs. of 20 variables: $ IST01 : num 1 1 1 0 0 1 1 1 0 1 ... $ IST02 : num 1 0 1 0 1 1 1 1 0 1 ... $ IST03 : num 0 1 1 1 1 1 0 1 1 1 ... [...] $ IST020: num 0 0 0 1 1 0 0 0 0 0 ...
Janssen, A. B., & Geiser, C. (2010). On the relationship between solution strategies in two mental rotation tasks. Learning and Individual Differences, 20(5), 473-478. doi: 10.1016/j.lindif.2010.03.002
## Not run:
#############################################################################
# EXAMPLE 1: CCT data, Janssen and Geiser (2010, LID)
# Latent class analysis based on data.janssen
#############################################################################
data(data.janssen)
dat <- data.janssen
colnames(dat)
## [1] "PIS1" "PIS3" "PIS4" "PIS5" "SCR6" "SCR9" "SCR10" "SCR17"
#*********************************************************************
#*** Model 1: Latent class analysis with two classes
tammodel <- "
ANALYSIS:
TYPE=LCA;
NCLASSES(2);
NSTARTS(10,20);
LAVAAN MODEL:
# missing item numbers (e.g. PIS2) are ignored in the model
F=~ PIS1__PIS5 + SCR6__SCR17
"
mod3 <- TAM::tamaan( tammodel, resp=dat )
summary(mod3)
# extract item response functions
imod2 <- IRT.irfprob(mod3)[,2,]
# plot class specific probabilities
ncl <- 2
matplot( imod2, type="o", pch=1:ncl, xlab="Item", ylab="Probability" )
legend( 1, .3, paste0("Class",1:ncl), lty=1:ncl, col=1:ncl, pch=1:ncl )
#*********************************************************************
#*** Model 2: Latent class analysis with three classes
tammodel <- "
ANALYSIS:
TYPE=LCA;
NCLASSES(3);
NSTARTS(10,20);
LAVAAN MODEL:
F=~ PIS1__PIS5 + SCR6__SCR17
"
mod3 <- TAM::tamaan( tammodel, resp=dat )
summary(mod3)
# extract item response functions
imod2 <- IRT.irfprob(mod3)[,2,]
# plot class specific probabilities
ncl <- 3
matplot( imod2, type="o", pch=1:ncl, xlab="Item", ylab="Probability" )
legend( 1, .3, paste0("Class",1:ncl), lty=1:ncl, col=1:ncl, pch=1:ncl )
# compare models
AIC(mod1); AIC(mod2)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.