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>.

Version: 4.0-16
Depends: R (≥ 2.15.1), CDM (≥ 6.4-19)
Imports: graphics, methods, Rcpp, stats, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: coda, GPArotation, grDevices, lattice, lavaan, MASS, miceadds, mvtnorm, plyr, psych, sfsmisc, splines, WrightMap
Enhances: LSAmitR
Published: 2022-05-14
Author: Alexander Robitzsch [aut,cre] (<https://orcid.org/0000-0002-8226-3132>), Thomas Kiefer [aut], Margaret Wu [aut]
Maintainer: Alexander Robitzsch <robitzsch at ipn.uni-kiel.de>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.edmeasurementsurveys.com/TAM/Tutorials/, https://github.com/alexanderrobitzsch/TAM, https://sites.google.com/site/alexanderrobitzsch2/software
NeedsCompilation: yes
Citation: TAM citation info
Materials: README NEWS
In views: MissingData, Psychometrics
CRAN checks: TAM results

Documentation:

Reference manual: TAM.pdf

Downloads:

Package source: TAM_4.0-16.tar.gz
Windows binaries: r-devel: TAM_4.0-16.zip, r-release: TAM_4.0-16.zip, r-oldrel: TAM_4.0-16.zip
macOS binaries: r-release (arm64): TAM_4.0-16.tgz, r-oldrel (arm64): TAM_4.0-16.tgz, r-release (x86_64): TAM_4.0-16.tgz, r-oldrel (x86_64): TAM_4.0-16.tgz
Old sources: TAM archive

Reverse dependencies:

Reverse imports: immer, sirt, whomds
Reverse suggests: BIFIEsurvey, LAM, LSAmitR, miceadds, scaleAlign

Linking:

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