  Based on a data set obtained in a dental longitudinal study, conducted in
Flanders (Belgium), the joint time to caries distribution of permanent first
molars was modeled as a function of covariates. This involves an analysis of
multivariate continuous doubly-interval-censored data since: (i) the emergence
time 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 joint
distribution of the emergence times and the times to caries, we propose a
dependent Bayesian semiparametric model. A major feature of the proposed
approach is that survival curves can be estimated without imposing assumptions
such as proportional hazards, additive hazards, proportional odds or
accelerated failure time.
