Bayesian semiparametric inference for multivariate doubly-interval-censored data

摘要

Based on a data set obtained in a dental longitudinal study, conducted inFlanders (Belgium), the joint time to caries distribution of permanent firstmolars was modeled as a function of covariates. This involves an analysis ofmultivariate continuous doubly-interval-censored data since: (i) the emergencetime of a tooth and the time it experiences caries were recorded yearly, and(ii) events on teeth of the same child are dependent. To model the jointdistribution of the emergence times and the times to caries, we propose adependent Bayesian semiparametric model. A major feature of the proposedapproach is that survival curves can be estimated without imposing assumptionssuch as proportional hazards, additive hazards, proportional odds oraccelerated failure time.