TAM (version 1.995-0)

data.janssen: Dataset from Janssen and Geiser (2010)

Description

Dataset used in Janssen and Geiser (2010).

Usage

data(data.janssen)
data(data.janssen2)

Format

• 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 ...

References

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.

Examples

## 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 <- 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 <- 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)