TAM: Test Analysis Modules

Includes marginal maximum likelihood estimation and joint maximum likelihood estimation for unidimensional and multidimensional item response models. The package functionality covers the Rasch model, 2PL model, 3PL model, generalized partial credit model, multi-faceted Rasch model, nominal item response model, structured latent class model, mixture distribution IRT models, and located latent class models. Latent regression models and plausible value imputation are also supported. For details see Adams, Wilson and Wang, 1997 <doi:10.1177/0146621697211001>, Adams, Wilson and Wu, 1997 <doi:10.3102/10769986022001047>, Formann, 1982 <doi:10.1002/bimj.4710240209>, Formann, 1992 <doi:10.1080/01621459.1992.10475229>.

Package details

Author Alexander Robitzsch [aut,cre] (<https://orcid.org/0000-0002-8226-3132>), Thomas Kiefer [aut], Margaret Wu [aut]
MaintainerAlexander Robitzsch <robitzsch@ipn.uni-kiel.de>
LicenseGPL (>= 2)
Version4.2-21
URL http://www.edmeasurementsurveys.com/TAM/Tutorials/ https://github.com/alexanderrobitzsch/TAM https://sites.google.com/view/alexander-robitzsch/software
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("TAM")

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TAM documentation built on May 29, 2024, 2:20 a.m.