TAM-package | R Documentation |
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>.
See http://www.edmeasurementsurveys.com/TAM/Tutorials/ for tutorials of the TAM package.
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>
Adams, R. J., Wilson, M., & Wang, W. C. (1997). The multidimensional random coefficients multinomial logit model. Applied Psychological Measurement, 21(1), 1-23. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/0146621697211001")}
Adams, R. J., Wilson, M., & Wu, M. (1997). Multilevel item response models: An approach to errors in variables regression. Journal of Educational and Behavioral Statistics, 22(1), 47-76. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3102/10769986022001047")}
Adams, R. J., & Wu, M. L. (2007). The mixed-coefficients multinomial logit model. A generalized form of the Rasch model. In M. von Davier & C. H. Carstensen (Eds.): Multivariate and mixture distribution Rasch models: Extensions and applications (pp. 55-76). New York: Springer. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/978-0-387-49839-3_4")}
Formann, A. K. (1982). Linear logistic latent class analysis. Biometrical Journal, 24(2), 171-190. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/bimj.4710240209")}
Formann, A. K. (1992). Linear logistic latent class analysis for polytomous data. Journal of the American Statistical Association, 87(418), 476-486. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/01621459.1992.10475229")}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.