CDM (version 4.991-1)

IRT.expectedCounts: S3 Method for Extracting Expected Counts

Description

This S3 method extracts expected counts from model output.

Usage

IRT.expectedCounts(object, ...)
"IRT.expectedCounts"(object, ...)
"IRT.expectedCounts"(object, ...)
"IRT.expectedCounts"(object, ...)
"IRT.expectedCounts"(object, ...)
"IRT.expectedCounts"(object, ...)

Arguments

object

Object of classes din, gdina, mcdina, gdm or slca.

...

More arguments to be passed.

Value

An array with expected counts. The dimensions are items, categories, latent classes and groups.

Examples

## Not run: 
# #############################################################################
# # EXAMPLE 1: Expected counts gdm function
# #############################################################################	
# 
# data( data.fraction1 )
# dat <- data.fraction1$data
# theta.k <- seq( -6 , 6 , len=11 )   # discretized ability
# 
# #--- Model 1: Rasch model
# mod1 <- gdm( dat , irtmodel="1PL" , theta.k=theta.k , skillspace="normal" ,
#                centered.latent=TRUE )              
# emod1 <- IRT.expectedCounts(mod1)             
# str(emod1)          
# 
# #############################################################################
# # EXAMPLE 2: Expected counts gdina function
# #############################################################################
# 
# data(sim.dina)
# data(sim.qmatrix)
# 
# #--- Model 1: estimation of the GDINA model
# mod1 <- gdina( data = sim.dina ,  q.matrix = sim.qmatrix)
# summary(mod1)
# emod1 <- IRT.expectedCounts( mod1 )
# str(emod1)
# 
# #--- Model 2: GDINA model with two groups
# mod2 <- gdina( data = sim.dina ,  q.matrix = sim.qmatrix , group = rep(1:2, each=200) )
# summary(mod2)
# emod2 <- IRT.expectedCounts( mod2 )
# str(emod2)
# ## End(Not run)