'ability.R' 'estimate.R' 'itemfit.R' 'nonpar.R' 'readin.R'
'scale.R' 'tracelines.R' 'utils.R' 'irtoys-package.R'

Provides a simple common interface to the estimation of item
parameters in IRT models for binary responses with three different programs
(ICL, BILOG-MG, and ltm, and a variety of functions useful with IRT models.

A Collection of Functions Related to Item Response Theory (IRT)
A collection of functions useful in learning and practicing IRT,
which can be combined into larger programs. Provides basic CTT analysis,
a simple common interface to the estimation of item
parameters in IRT models for binary responses with three different programs
(ICL, BILOG-MG, and ltm), ability estimation (MLE, BME, EAP, WLE, plausible
values), item and person fit statistics, scaling methods (MM, MS, Stocking-Lord,
and the complete Hebaera method), and a rich array of parametric and
non-parametric (kernel) plots. Estimates and plots Haberman's interaction model
when all items are dichotomously scored.
'ability.R' 'estimate.R' 'itemfit.R' 'nonpar.R' 'readin.R'
'scale.R' 'tracelines.R' 'utils.R' 'irtoys-package.R'
'interaction.R'

c(person("Ivailo", "Partchev", email = "partchev@gmail.com", role = c("aut","cre")),
person("Gunter", "Maris", email = "Gunter.Maris@act.org", role = "aut"),
person("Tamaki", "Hattori", role = "ctb"))
Ivailo Partchev [aut, cre],
Gunter Maris [aut],
Tamaki Hattori [ctb]

Power Analysis for IRT Models Using the Wald, LR, Score, and
Gradient Statistics
c(
person("Felix", "Zimmer", , "felix.zimmer@mail.de", role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-8127-0007")),
person("Rudolf", "Debelak", , "rudolf.debelak@psychologie.uzh.ch", role = c("aut"),
comment = c(ORCID = "0000-0001-8900-2106"))
)
Implementation of analytical and sampling-based power analyses for
the Wald, likelihood ratio (LR), score, and gradient tests. Can be applied
to item response theory (IRT) models that are fitted using marginal maximum
likelihood estimation. The methods are described in our paper
(Zimmer et al. (2022) <doi:10.1007/s11336-022-09883-5>).
mirt, Deriv, digest, spatstat.random, ggplot2, methods