The Wide Variety of Regression Models for Lifetime Data

Chrys Caroni ()
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Chrys Caroni: National Technical University of Athens, Department of Mathematics

Chapter Chapter 24 in Demography of Population Health, Aging and Health Expenditures, 2020, pp 377-383 from Springer

Abstract: Abstract The dependence of lifetimes on covariates can be modelled in a regression format in various ways. In some fields, especially biostatistics, the most familiar approach is through the proportional hazards assumption. Less widely used is the proportional odds model and there are other “proportional” models in the literature, notably proportional reversed hazards and proportional mean residual life. Another approach, possessing the conceptual advantage of being based on a representation of the underlying process leading to the event (such as death or failure), is threshold regression in which (in the Inverse Gaussian case) two parameters of the underlying distribution are modelled. Burke and Mackenzie have also introduced a multi-parameter regression. I present and discuss these models, their differences and in what circumstances each is useful. Some theoretical relations are presented.

Keywords: Survival analysis; Regression models; Proportional hazards; Proportional odds; Proportional reversed hazards; Proportional mean residual life (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/978-3-030-44695-6_24

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