entropy.lca.Rd
Computes test-specific and item-specific entropy as test-diagnostic criteria of cognitive diagnostic models (Asparouhov & Muthen, 2014).
entropy.lca(object)
# S3 method for entropy.lca
summary(object, digits=2, ...)
A list with the data frame entropy
as an entry.
Asparouhov, T. & Muthen, B. (2014). Variable-specific entropy contribution. Technical Appendix. http://www.statmodel.com/7_3_papers.shtml
See cdi.kli
for test diagnostic indices based on the
Kullback-Leibler information and cdm.est.class.accuracy
for calculating the classification accuracy.
#############################################################################
# EXAMPLE 1: Entropy for DINA model
#############################################################################
data(sim.dina, package="CDM")
data(sim.qmatrix, package="CDM")
# fit DINA Model
mod1 <- CDM::din( sim.dina, q.matrix=sim.qmatrix, rule="DINA")
summary(mod1)
# compute entropy for test and items
emod1 <- CDM::entropy.lca( mod1 )
summary(emod1)
if (FALSE) {
#############################################################################
# EXAMPLE 2: Entropy for polytomous GDINA model
#############################################################################
data(data.pgdina, package="CDM")
dat <- data.pgdina$dat
q.matrix <- data.pgdina$q.matrix
# pGDINA model with "DINA rule"
mod1 <- CDM::gdina( dat, q.matrix=q.matrix, rule="DINA")
summary(mod1)
# compute entropy
emod1 <- CDM::entropy.lca( mod1 )
summary(emod1)
#############################################################################
# EXAMPLE 3: Entropy for MCDINA model
#############################################################################
data(data.cdm02, package="CDM")
dat <- data.cdm02$data
q.matrix <- data.cdm02$q.matrix
# estimate model with polytomous atribute
mod1 <- CDM::mcdina( dat, q.matrix=q.matrix )
summary(mod1)
# computre entropy
emod1 <- CDM::entropy.lca( mod1 )
summary(emod1)
}