Silveira, Liciana V. A. [UNESP]Colosimo, Enrico A.Passos, Jose Raimundo de S. [UNESP]2014-05-202014-05-202010-01-01Communications In Statistics-theory and Methods. Philadelphia: Taylor & Francis Inc, v. 39, n. 15, p. 2659-2666, 2010.0361-0926http://hdl.handle.net/11449/17136It is common to have experiments in which it is not possible to observe the exact lifetimes but only the interval where they occur. This sort of data presents a high number of ties and it is called grouped or interval-censored survival data. Regression methods for grouped data are available in the statistical literature. The regression structure considers modeling the probability of a subject's survival past a visit time conditional on his survival at the previous visit. Two approaches are presented: assuming that lifetimes come from (1) a continuous proportional hazards model and (2) a logistic model. However, there may be situations in which none of the models are adequate for a particular data set. This article proposes the generalized log-normal model as an alternative model for discrete survival data. This model was introduced by Chen (1995) and it is extended in this article for grouped survival data. A real example related to a Chagas disease illustrates the proposed model.2659-2666engDiscrete modelsInterval censoringLogistic modelProportional hazards modelArtigo10.1080/03610920903009368WOS:000280544900001Acesso restrito