We consider a latent variable model for multivariate ordinal responses accounting
for dependencies among items. Time-dependent latent variables and random
effects account for the inter-dependencies of the multivariate ordinal items.
Model estimation is usually obtained using the full maximum likelihood via the
EM algorithm. However, computationally problems can arise due to the calculation
of multiple integrals involved in the likelihood. The paper proposes a pseudolikelihood
approach which involves only bivariate marginal probabilities. The proposed
estimation method is evaluated by means of a little simulation study. A real
data example illustrates the performance of both the full and the limited information
estimation method
