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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 |
| Reference manual: | IRTBEMM.pdf |
| 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 |
Please use the canonical form https://CRAN.R-project.org/package=IRTBEMM to link to this page.
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.