Description
Test Analysis Modules.
Description
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>.
README.md
TAM
Test Analysis Modules
If you use TAM and have suggestions for improvement or have found bugs, please email me at [email protected]. Please always provide a minimal dataset, necessary to demonstrate the problem, a minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and all necessary information on the used librarys, the R version, and the OS it is run on, perhaps a sessionInfo().
CRAN version
The official version of TAM is hosted on CRAN and may be found here. The CRAN version can be installed from within R using:
utils::install.packages("TAM")
GitHub version
The version hosted here is the development version of TAM. The GitHub version can be installed using devtools as
devtools::install_github("alexanderrobitzsch/TAM")
or alternatively use
utils::install.packages('TAM', repos = c('https://alexanderrobitzsch.r-universe.dev', 'https://cloud.r-project.org'))