IRT.expectedCounts: S3 Method for Extracting Expected Counts

In CDM: Cognitive Diagnosis Modeling

S3 Method for Extracting Expected Counts

Description

This S3 method extracts expected counts from model output.

Usage

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, ...)

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, 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)

CDM documentation built on Aug. 25, 2022, 5:08 p.m.