View source: R/IRT.expectedCounts.R
IRT.expectedCounts | R Documentation |
This S3 method extracts expected counts from model output.
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, ...)
object |
Object of classes |
... |
More arguments to be passed. |
An array with expected counts. The dimensions are items, categories, latent classes and groups.
## 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)
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