A continuation ratio random effects model for repeated ordinal responses.

This paper presents methods of analysis for ordinal repeated measures. We use a generalization of the continuation ratio model with a random effect. We handle frailty by using a normal distribution and also a non-parametric distribution. The methodology is readily implemented in existing software and flexible enough to treat large data sets with uncommon time measurements as well as different numbers of repeated measures for each individual. The models are used to investigate how a group of explanatory variables influences the overall condition of patients treated for breast cancer.

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