# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "TAM" in publications use:' type: software license: GPL-2.0-or-later title: 'TAM: Test Analysis Modules' version: 4.3-4 identifiers: - type: doi value: 10.32614/CRAN.package.TAM - type: url value: https://sites.google.com/view/alexander-robitzsch/software abstract: 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 , Adams, Wilson and Wu, 1997 , Formann, 1982 , Formann, 1992 . authors: - family-names: Robitzsch given-names: Alexander email: robitzsch@ipn.uni-kiel.de orcid: https://orcid.org/0000-0002-8226-3132 - family-names: Kiefer given-names: Thomas - family-names: Wu given-names: Margaret preferred-citation: type: manual title: 'TAM: Test Analysis Modules' authors: - family-names: Robitzsch given-names: Alexander email: robitzsch@ipn.uni-kiel.de orcid: https://orcid.org/0000-0002-8226-3132 - family-names: Kiefer given-names: Thomas - family-names: Wu given-names: Margaret year: '2024' notes: R package version 4.3-4 url: https://CRAN.R-project.org/package=TAM repository: https://alexanderrobitzsch.r-universe.dev repository-code: https://github.com/alexanderrobitzsch/TAM commit: e47c6ae1846da7f6d47361569dfc056435071aa6 url: http://www.edmeasurementsurveys.com/TAM/Tutorials/ date-released: '2024-09-09' contact: - family-names: Robitzsch given-names: Alexander email: robitzsch@ipn.uni-kiel.de orcid: https://orcid.org/0000-0002-8226-3132