Extended Rasch Modeling: The<b>eRm</b>Package for the Application of IRT Models in<i>R</i>
Patrick Mair; Reinhold Hatzinger
Item response theory models (IRT) are increasingly becoming established in social science research, particularly in the analysis of performance or attitudinal data in psychology, education, medicine, marketing and other fields where testing is relevant. We propose the R package eRm (extended Rasch modeling) for computing Rasch models and several extensions. A main characteristic of some IRT models, the Rasch model being the most prominent, concerns the separation of two kinds of parameters, one that describes qualities of the subject under investigation, and the other relates to qualities of the situation under which the response of a subject is observed. Using conditional maximum likelihood (CML) estimation both types of parameters may be estimated independently from each other. IRT models are well suited to cope with dichotomous and polytomous responses, where the response categories m...
Patrick Mair & Reinhold Hatzinger (2007). Extended Rasch Modeling: The<b>eRm</b>Package for the Application of IRT Models in<i>R</i>. Journal of Statistical Software, 20(9). https://doi.org/10.18637/jss.v020.i09