Observed information matrix for MUB models

In this paper we derive the observed information matrix for MUB models, without and with covariates. After a review of this class of models for ordinal data and of the E-M algorithms, we derive some closed forms for the asymptotic variance covariance matrix of the maximum likelihood estimators of MUB models. Also, some new results about feeling and uncertainty parameters are presented. The work lingers over the computational aspects of the procedure with explicit reference to a matrixoriented language. Finally, the finite sample performance of the asymptotic results is investigated by means of a simulation experiment. General considerations aimed at extending the application of MUB models conclude the paper