IRT.expectedCounts(object, ...)

## S3 method for class 'din'
IRT.expectedCounts(object, ...)

## S3 method for class 'gdina'
IRT.expectedCounts(object, ...)

## S3 method for class 'gdm'
IRT.expectedCounts(object, ...)

## S3 method for class 'mcdina'
IRT.expectedCounts(object, ...)

## S3 method for class 'slca'
IRT.expectedCounts(object, ...)

## S3 method for class 'reglca'
IRT.expectedCounts(object, ...)

## Not run: 
#############################################################################
# EXAMPLE 1: Expected counts gdm function
#############################################################################

data(data.fraction1, package="CDM")
dat <- data.fraction1$data
theta.k <- seq( -6, 6, len=11 )   # discretized ability

#--- Model 1: Rasch model
mod1 <- CDM::gdm( dat, irtmodel="1PL", theta.k=theta.k, skillspace="normal",
               centered.latent=TRUE )
emod1 <- CDM::IRT.expectedCounts(mod1)
str(emod1)

#############################################################################
# EXAMPLE 2: Expected counts gdina function
#############################################################################

data(sim.dina, package="CDM")
data(sim.qmatrix, package="CDM")

#--- Model 1: estimation of the GDINA model
mod1 <- CDM::gdina( data=sim.dina, q.matrix=sim.qmatrix)
summary(mod1)
emod1 <- CDM::IRT.expectedCounts(mod1)
str(emod1)

#--- Model 2: GDINA model with two groups
mod2 <- CDM::gdina( data=CDM::sim.dina, q.matrix=CDM::sim.qmatrix,
                   group=rep(1:2, each=200) )
summary(mod2)
emod2 <- CDM::IRT.expectedCounts( mod2 )
str(emod2)

## End(Not run)