cfa.extract.itempars(object)

#############################################################################
# EXAMPLE 1: CFA data.Students
#############################################################################

library(lavaan)
library(CDM)

data(data.Students, package="CDM")
dat <- data.Students

dat1 <- dat[, paste0( "mj", 1:4 ) ]

#*** Model 1: Unidimensional model scale mj
lavmodel <- "
   mj=~ mj1 + mj2 + mj3 + mj4
   mj ~~ mj
     "
mod1 <- lavaan::cfa( lavmodel, data=dat1, std.lv=TRUE )
summary(mod1, standardized=TRUE, rsquare=TRUE )
# extract parameters
res1 <- TAM::cfa.extract.itempars( mod1 )

## Not run: 
#*** Model 2: Scale mj - explicit modelling of item intercepts
lavmodel <- "
   mj=~ mj1 + mj2 + mj3 + mj4
   mj ~~ mj
   mj1 ~ 1
     "
mod2 <- lavaan::cfa( lavmodel, data=dat1, std.lv=TRUE )
summary(mod2, standardized=TRUE, rsquare=TRUE )
res2 <- TAM::cfa.extract.itempars( mod2 )

#*** Model 3: Tau-parallel measurements scale mj
lavmodel <- "
   mj=~ a*mj1 + a*mj2 + a*mj3 + a*mj4
   mj ~~ 1*mj
   mj1 ~ b*1
   mj2 ~ b*1
   mj3 ~ b*1
   mj4 ~ b*1
     "
mod3 <- lavaan::cfa( lavmodel, data=dat1, std.lv=TRUE )
summary(mod3, standardized=TRUE, rsquare=TRUE )
res3 <- TAM::cfa.extract.itempars( mod3 )

#*** Model 4: Two-dimensional CFA with scales mj and sc
dat2 <- dat[, c(paste0("mj",1:4), paste0("sc",1:4)) ]
# lavaan model with shortage "__" operator
lavmodel <- "
   mj=~ mj1__mj4
   sc=~ sc1__sc4
   mj ~~ sc
   mj ~~ 1*mj
   sc ~~ 1*sc
     "
lavmodel <- TAM::lavaanify.IRT( lavmodel, data=dat2 )$lavaan.syntax
cat(lavmodel)
mod4 <- lavaan::cfa( lavmodel, data=dat2, std.lv=TRUE )
summary(mod4, standardized=TRUE, rsquare=TRUE )
res4 <- TAM::cfa.extract.itempars( mod4 )

## End(Not run)