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Grouped data is a particular case of survival data with interval censoring that occurs when the observations are evaluated at the same time intervals. Generally, its associated at data with a large number of draws and, therefore, it can be analyzed considering discrete-time and tting models at the probability of an individual fails in an certain interval, given that they survived the previous one (LAWLESS, 2002). Among the possible models adapted to this type of data, we can mention the Logistic Model and Cox's Model. The purpose of this article is to compare the t of these two models using classic and bayesian model selection criteria. As an example, was used a data set related to a clinical manifestation of Chagas disease known as chagasic megacolon (ALMEIDA, 1996).
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