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IRTBEMM: Family of Bayesian EMM Algorithm for Item Response Models

Applying the family of the Bayesian Expectation-Maximization-Maximization (BEMM) algorithm to estimate: (1) Three parameter logistic (3PL) model proposed by Birnbaum (1968, ISBN:9780201043105); (2) four parameter logistic (4PL) model proposed by Barton & Lord (1981) <doi:10.1002/j.2333-8504.1981.tb01255.x>; (3) one parameter logistic guessing (1PLG) and (4) one parameter logistic ability-based guessing (1PLAG) models proposed by San Martín et al (2006) <doi:10.1177/0146621605282773>. The BEMM family includes (1) the BEMM algorithm for 3PL model proposed by Guo & Zheng (2019) <doi:10.3389/fpsyg.2019.01175>; (2) the BEMM algorithm for 1PLG model and (3) the BEMM algorithm for 1PLAG model proposed by Guo, Wu, Zheng, & Chen (2021) <doi:10.1177/0146621621990761>; (4) the BEMM algorithm for 4PL model proposed by Zheng, Guo, & Kern (2021) <doi:10.1177/21582440211052556>; and (5) their maximum likelihood estimation versions proposed by Zheng, Meng, Guo, & Liu (2018) <doi:10.3389/fpsyg.2017.02302>. Thus, both Bayesian modal estimates and maximum likelihood estimates are available.

Version: 1.0.8
Depends: R (≥ 3.5.0)
Published: 2023-06-06
DOI: 10.32614/CRAN.package.IRTBEMM
Author: Shaoyang Guo [aut, cre, cph], Chanjin Zheng [aut], Justin L Kern [aut]
Maintainer: Shaoyang Guo <syguo1992 at outlook.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: IRTBEMM citation info
Materials: README NEWS
CRAN checks: IRTBEMM results

Documentation:

Reference manual: IRTBEMM.pdf

Downloads:

Package source: IRTBEMM_1.0.8.tar.gz
Windows binaries: r-devel: IRTBEMM_1.0.8.zip, r-release: IRTBEMM_1.0.8.zip, r-oldrel: IRTBEMM_1.0.8.zip
macOS binaries: r-release (arm64): IRTBEMM_1.0.8.tgz, r-oldrel (arm64): IRTBEMM_1.0.8.tgz, r-release (x86_64): IRTBEMM_1.0.8.tgz, r-oldrel (x86_64): IRTBEMM_1.0.8.tgz
Old sources: IRTBEMM 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.