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IRTest: Parameter Estimation of Item Response Theory with Estimation of Latent Distribution

Item response theory (IRT) parameter estimation using marginal maximum likelihood and expectation-maximization algorithm (Bock & Aitkin, 1981 <doi:10.1007/BF02293801>). Within parameter estimation algorithm, several methods for latent distribution estimation are available. Reflecting some features of the true latent distribution, these latent distribution estimation methods can possibly enhance the estimation accuracy and free the normality assumption on the latent distribution.

Version: 2.1.0
Depends: R (≥ 2.10)
Imports: betafunctions, dcurver, ggplot2, usethis
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0), gridExtra
Published: 2024-10-04
DOI: 10.32614/CRAN.package.IRTest
Author: Seewoo Li [aut, cre, cph]
Maintainer: Seewoo Li <seewooli at g.ucla.edu>
BugReports: https://github.com/SeewooLi/IRTest/issues
License: GPL (≥ 3)
URL: https://github.com/SeewooLi/IRTest
NeedsCompilation: no
Citation: IRTest citation info
Materials: README NEWS
CRAN checks: IRTest results

Documentation:

Reference manual: IRTest.pdf
Vignettes: IRT without the normality assumption (source, R code)

Downloads:

Package source: IRTest_2.1.0.tar.gz
Windows binaries: r-devel: IRTest_2.1.0.zip, r-release: IRTest_2.1.0.zip, r-oldrel: IRTest_2.1.0.zip
macOS binaries: r-release (arm64): IRTest_2.1.0.tgz, r-oldrel (arm64): IRTest_2.1.0.tgz, r-release (x86_64): IRTest_2.1.0.tgz, r-oldrel (x86_64): IRTest_2.1.0.tgz
Old sources: IRTest 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.