Pairwise- and marginal-likelihood estimation for the mixed Rasch model with binary data
A marginal-pairwise-likelihood estimation approach is examined in the mixed Rasch model with the binary response and logit link. This method belonging to the broad class of composite likelihood provides estimators with desirable asymptotic properties such as consistency and asymptotic normality. We study the performance of the proposed methodology when the random effect distribution is misspecified. A simulation study was conducted to compare this approach with the maximum marginal likelihood. The different results are also illustrated with an analysis of the real data set from a quality-of-life study.
rasch model binary data composite likelihood random effects marginal likelihood quality-of-life fixed effects generalized linear mixed model marginal-pairwise likelihood variance component