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In psoriatic arthritis, it is important to understand the joint activity(represented by swelling and pain) and damage processes because both arerelated to severe physical disability. This paper aims to provide acomprehensive investigation in to both processes occurring over time, inparticular their relationship, by specifying a joint multi-state model at theindividual hand joint-level, which also accounts for many of their importantfeatures. As there are multiple hand joints, such an analysis will be based onthe use of clustered multi-state models. Here we consider an observation-levelrandom effects structure with dynamic covariates and allow for the possibilitythat a subpopulation of patients are at minimal risk of damage. Such ananalysis is found to provide further understanding of the activity-damagerelationship beyond that provided by previous analyses. Consideration is alsogiven to the modelling of mean sojourn times and jump probabilities. Inparticular, a novel model parameterization which allows easily interpretablecovariate effects to act on these quantities is proposed.

Clustered multi-state models with observation-level random effects,  mover-stayer effects and dynamic covariates: Modelling transition intensities  and sojourn times in a study of psoriatic arthritis