Simple models for repeated ordinal responses, with an application to seasonal rhinitis clinical trial

Abstract

In contrast to other models for ordinal data, the continuation ratio model can be fitted with standard statistical software. This makes it particularly appropriate for large clinical trials with ordinal response variables. In addition, when the trials are longitudinal, this model can be applied to individual responses instead of frequencies in contingency tables. Dependence can be incorporated by conditioning on the previous response, yielding a form of Markov chain. This approach is applied to the analysis of a large seasonal rhinitis trial, where patients were observed over 28 days and six symptoms recorded as ordinal responses.