Abstract
Interval-censored recurrent event data can exhibit considerable between subject heterogeneity in the event rate, and frequently there is a proportion of individuals experiencing no events. We consider a likelihood based analysis of bivariate interval-censored recurrent event data in which a random effect is used to accommodate heterogeneity in the rate of events, and bivariate mover–stayer indicators are introduced to accommodate a non susceptible sub-population for each type of event. The model facilitates the estimation of the joint distribution of two mover–stayer indicators and hence the association in the susceptibility for two types of joint damage assessments in patients with psoriatic arthritis.
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