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A Bayesian analysis of correlated interval-censored data. (English) Zbl 1109.62113

Summary: In epidemiological studies where subjects are seen periodically on follow-up visits, interval-censored data occur naturally. The exact time the change of state (such as HIV seroconversion) occurs is not known exactly, only that it occurred within some time interval. In multi-stage sampling or partner tracing studies, individuals are grouped into smaller subgroups. Individuals within a subgroup share an unobservable specific frailty which induces correlation within the subgroup. We consider a Bayesian model for analysing correlated interval-censored data. Parameters are estimated using Markov chain Monte Carlo methods, specifically the Gibbs sampler.

MSC:

62P10 Applications of statistics to biology and medical sciences; meta analysis
62N02 Estimation in survival analysis and censored data
62F15 Bayesian inference
62N01 Censored data models
65C40 Numerical analysis or methods applied to Markov chains
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