A Generalized Log-Normal Model for Grouped Survival Data
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Taylor & Francis Inc
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Article
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Abstract
It 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.
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English
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Communications In Statistics-theory and Methods. Philadelphia: Taylor & Francis Inc, v. 39, n. 15, p. 2659-2666, 2010.
