Proportional hazards model for repeated measures with monotonic ordinal response

In this paper we present a proportional hazards model to determine the effect of predictors on repeated measures data with ordinal response that is monotonic over time. The model can handle both categorical and continuous predictors. It naturally models the time spent in the response states. The assumption of proportional hazards can be partially assessed if replicates (individuals with identical covariate vectors) are available. Censoring can be incorporated into the model, although it does require additional modelling if the censoring is informative.