extended · article · 2009

IRT models with relaxed assumptions in eRm: A manual-like instruction

Reinhold Hatzinger; Thomas Rusch; Ivor W. Molenaar

Linear logistic models with relaxed assumptions (LLRA) as introduced by Fischer (1974) are a <br/>flexible tool for the measurement of change for dichotomous or polytomous responses. As opposed to <br/>the Rasch model, assumptions on dimensionality of items, their mutual dependencies and the <br/>distribution of the latent trait in the population of subjects are relaxed. Conditional maximum likelihood <br/>estimation allows for inference about treatment, covariate or trend effect parameters without taking the <br/>subjects' latent trait values into account. In this paper we will show how LLRAs based on the LLTM, <br/>LRSM and LPCM can be used to answer various questions about the measurement of change and how <br/>they can be fitted in R using the eRm package. A number of small didactic examples is provided that <br/>can easily be used as templates for real data sets. All datafiles used ...