IRT.likelihood {CDM} | R Documentation |
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 class 'din'
IRT.likelihood(object, ...)
## S3 method for class 'din'
IRT.posterior(object, ...)
## S3 method for class 'gdina'
IRT.likelihood(object, ...)
## S3 method for class 'gdina'
IRT.posterior(object, ...)
## S3 method for class 'gdm'
IRT.likelihood(object, ...)
## S3 method for class 'gdm'
IRT.posterior(object, ...)
## S3 method for class 'mcdina'
IRT.likelihood(object, ...)
## S3 method for class 'mcdina'
IRT.posterior(object, ...)
## S3 method for class 'reglca'
IRT.likelihood(object, ...)
## S3 method for class 'reglca'
IRT.posterior(object, ...)
## S3 method for class 'slca'
IRT.likelihood(object, ...)
## S3 method for class 'slca'
IRT.posterior(object, ...)
Arguments
object |
|
... |
More arguments to be passed. |
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 |
skillspace |
Design matrix and estimated parameters for
skill space distribution (only for |
G |
Number of groups |
See Also
GDINA::indlogLik
,
GDINA::indlogPost
Examples
#############################################################################
# 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)
[Package CDM version 8.2-6 Index]