An analysis is presented of a longitudinal study of fluvoxamine, an antidepressant drug, with ordinal responses, regressed on a combination of discrete and continuous covariates and with a substantial proportion of dropouts. Classical methods, such as weighted least squares (SAS procedure CATMOD) and logistic regression, are not suitable for the analysis of such data. Instead, we illustrate how a recently introduced model can be used to solve most of the problems posed. The method is likelihood-based and is an extension of the bivariate Dale model to an arbitrary number of outcomes. The method is suitable for several types of designs commonly employed in clinical trials.