IRT.irfprob: S3 Methods for Extracting Item Response Functions

In CDM: Cognitive Diagnosis Modeling

S3 Methods for Extracting Item Response Functions

Description

This S3 method extracts item response functions evaluated at a grid of abilities (skills). Item response functions can be plotted using the IRT.irfprobPlot function.

Usage

IRT.irfprob(object, ...)

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

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

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

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

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

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

Arguments

object	Object of classes din, gdina, mcdina, gdm, slca, reglca.
...	More arguments to be passed.

Value

An array with item response probabilities (items \times categories \times skill classes [\times group]) and attributes

theta	Uni- or multidimensional skill space (theta grid in item response models).
prob.theta	Probability distribution of theta
skillspace	Design matrix and estimated parameters for skill space distribution (only for IRT.posterior.slca)
G	Number of groups

See Also

Plot functions for item response curves: IRT.irfprobPlot.

For extracting the individual likelihood or posterior see IRT.likelihood or IRT.posterior.

Examples

## Not run: 
#############################################################################
# EXAMPLE 1: Extracting item response functions mcdina model
#############################################################################

data(data.cdm02, package="CDM")

dat <- data.cdm02$data
q.matrix <- data.cdm02$q.matrix

#-- estimate model
mod1 <- CDM::mcdina( dat, q.matrix=q.matrix)
#-- extract item response functions
prmod1 <- CDM::IRT.irfprob(mod1)
str(prmod1)

## End(Not run)

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