Muraki, EijiCarlson, James E.2011-11-022011-11-021995Muraki, Eiji & Carlson, James E. (1995). Full-information factor analysis for polytomous item responses. Applied Psychological Measurement, 19, 73-90. doi:10.1177/014662169501900109doi:10.1177/014662169501900109https://hdl.handle.net/11299/117440A full-information item factor analysis model for multidimensional polytomously scored item response data is developed as an extension of previous work by several authors. The model is expressed both in factor-analytic and item response theory parameters. Reckase’s multidimensional parameters for the model also are discussed as well as the related geometry. An EM algorithm for estimation of the model parameters is presented and results of the analysis of item response data by a computer program incorporating this algorithm are presented. Index terms: EM algorithm, full-information item factor analysis, multidimensional item response theory, polytomous response data.enArticle