CDM (version 8.2-6)

IRT.likelihood: S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior

Description

Functions for extracting the individual likelihood and individual posterior distribution.

Usage

IRT.likelihood(object, ...)

IRT.posterior(object, ...)

# S3 method for din IRT.likelihood(object, ...) # S3 method for din IRT.posterior(object, ...)

# S3 method for gdina IRT.likelihood(object, ...) # S3 method for gdina IRT.posterior(object, ...)

# S3 method for gdm IRT.likelihood(object, ...) # S3 method for gdm IRT.posterior(object, ...)

# S3 method for mcdina IRT.likelihood(object, ...) # S3 method for mcdina IRT.posterior(object, ...)

# S3 method for reglca IRT.likelihood(object, ...) # S3 method for reglca IRT.posterior(object, ...)

# S3 method for slca IRT.likelihood(object, ...) # S3 method for slca IRT.posterior(object, ...)

Value

For both functions IRT.likelihood and IRT.posterior, it is a matrix with 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

Arguments

object

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

...

More arguments to be passed.

See Also

GDINA::indlogLik, GDINA::indlogPost

Examples

Run this code
#############################################################################
# EXAMPLE 1: Extracting likelihood and posterior from a DINA model
#############################################################################

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

#*** estimate model
mod1 <- CDM::din( sim.dina, q.matrix=sim.qmatrix, rule="DINA")
#*** extract likelihood
likemod1 <- CDM::IRT.likelihood(mod1)
str(likemod1)
# extract theta
attr(likemod1, "theta" )
#*** extract posterior
pomod1 <- CDM::IRT.posterior( mod1 )
str(pomod1)

Run the code above in your browser using DataLab