TAM (version 2.13-15)

tam.np: Unidimensional Nonparametric Item Response Model

Description

Conducts nonparametric estimation of a unidimensional item response model for a single group allowing polytomous item responses (Rossi, Wang & Ramsay, 2002).

Usage

tam.np(dat, probs_init=NULL, pweights=NULL, control=list())

Arguments

dat

Matrix of integer item responses (starting from zero)

probs_init

Array containing initial probabilities

pweights

Optional vector of person weights

control

List of control arguments, see tam.mml.

Value

List containing several entries

rprobs

Item response probabilities

theta

Used nodes for approximation of \(\theta\) distribution

n.ik

Expected counts

like

Individual likelihood

hwt

Individual posterior

…

Further values

References

Rossi, N., Wang, X., & Ramsay, J. O. (2002). Nonparametric item response function estimates with the EM algorithm. Journal of Educational and Behavioral Statistics, 27(3), 291-317.

See Also

Nonparametric item response models can also be estimated with the mirt::itemGAM function in the mirt package and the KernSmoothIRT::ksIRT in the KernSmoothIRT package.

See tam.mml and tam.mml.2pl for parametric item response models.

Examples

# NOT RUN {
#############################################################################
# EXAMPLE 1: Nonparametric estimation polytomous data
#############################################################################

data(data.cqc02, package="TAM")
dat <- data.cqc02

#** nonparametric estimation
mod <- TAM::tam.np( dat )

#** extractor functions for objects of class 'tam.np'
lmod <- IRT.likelihood(mod)
pmod <- IRT.posterior(mod)
rmod <- IRT.irfprob(mod)
emod <- IRT.expectedCounts(mod)
# }