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irtpwr: Power Analysis for IRT Models Using the Wald, LR, Score, and Gradient Statistics

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>).

Version: 1.0.3
Imports: mirt, Deriv, digest, spatstat.random, ggplot2, methods
Suggests: testthat, knitr, rmarkdown
Published: 2023-11-20
Author: Felix Zimmer ORCID iD [aut, cre], Rudolf Debelak ORCID iD [aut], Jan Radek [ctb]
Maintainer: Felix Zimmer <felix.zimmer at mail.de>
BugReports: https://github.com/flxzimmer/irtpwr/issues
License: GPL (≥ 3)
URL: https://github.com/flxzimmer/irtpwr
NeedsCompilation: no
Materials: README NEWS
CRAN checks: irtpwr results

Documentation:

Reference manual: irtpwr.pdf
Vignettes: Adding Hypotheses
Demo
Hypothesis Templates
Power Analysis for the Wald, LR, Score, and Gradient Tests using irtpwr

Downloads:

Package source: irtpwr_1.0.3.tar.gz
Windows binaries: r-devel: irtpwr_1.0.3.zip, r-release: irtpwr_1.0.3.zip, r-oldrel: irtpwr_1.0.3.zip
macOS binaries: r-release (arm64): irtpwr_1.0.3.tgz, r-oldrel (arm64): irtpwr_1.0.3.tgz, r-release (x86_64): irtpwr_1.0.3.tgz, r-oldrel (x86_64): irtpwr_1.0.3.tgz
Old sources: irtpwr archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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