Likelihood approximations and discrete models for tied survival data
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Data
2002-01-01
Autores
Chalita, LVAS
Colosimo, E. A.
Demetrio, CGB
Título da Revista
ISSN da Revista
Título de Volume
Editor
Marcel Dekker Inc
Resumo
Ties among event times are often recorded in survival studies. For example, in a two week laboratory study where event times are measured in days, ties are very likely to occur. The proportional hazards model might be used in this setting using an approximated partial likelihood function. This approximation works well when the number of ties is small. on the other hand, discrete regression models are suggested when the data are heavily tied. However, in many situations it is not clear which approach should be used in practice. In this work, empirical guidelines based on Monte Carlo simulations are provided. These recommendations are based on a measure of the amount of tied data present and the mean square error. An example illustrates the proposed criterion.
Descrição
Palavras-chave
Breslow approximation, Cox model, Monte Carlo simulations, proportional hazards model, tied observations
Como citar
Communications In Statistics-theory and Methods. New York: Marcel Dekker Inc., v. 31, n. 7, p. 1215-1229, 2002.