Nothing
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>.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Alexander Robitzsch [aut,cre] (<https://orcid.org/0000-0002-8226-3132>), Thomas Kiefer [aut], Margaret Wu [aut] |
| Maintainer | Alexander Robitzsch <robitzsch@ipn.uni-kiel.de> |
| License | GPL (>= 2) |
| Version | 4.2-21 |
| URL | http://www.edmeasurementsurveys.com/TAM/Tutorials/ https://github.com/alexanderrobitzsch/TAM https://sites.google.com/view/alexander-robitzsch/software |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the TAM package in your browser
Any scripts or data that you put into this service are public.
