IRT.likelihood | R Documentation |
Functions for extracting the individual likelihood and individual posterior distribution.
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, ...)
object |
Object of classes |
... |
More arguments to be passed. |
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 |
GDINA::indlogLik
,
GDINA::indlogPost
############################################################################# # 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)
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