Frequentist and Bayesian approaches for interval-censored data
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Interval censoring appears when the event of interest is only known to have occurred within a random time interval. Estimation and hypothesis testing procedures for interval-censored data are surveyed. We distinguish between frequentist and Bayesian approaches. Computational aspects for every proposed method are described and solutions with S-Plus, whenever are feasible, are mentioned. Three real data sets are analyzed.
Key WordsAIDS Bayesian inference Hypothesis testing Interval censoring Nonparametric methods Permutational tests
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