Abstract
Frailty models are generalizations of the well-known Cox model (Cox, J Roy Stat Soc B 34:187–202, 1972), introduced by Vaupel et al. (Demography 16:439–454, 1979) which are included in a bigger class of models called transformation models. They have received considerable attention over the past couple of decades, especially for the analysis of medical and reliability data that display heterogeneity, which cannot be sufficiently explained by the Cox model. More specifically, the frailty parameter is a random effect term that acts multiplicatively on the hazard intensity function of the Cox model. In this paper we present older and recent results on frailty and transformation models in the parametric and semiparametric setting and for various observational schemes. We deal with efficient estimation of parameters in the uncensored case, right censored case and interval censored and truncated data case.
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Acknowledgments
We would like to thank the anonymous referee whose comments greatly improved the presentation and clarity of the paper.
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Vonta, F. (2012). Frailty or Transformation Models in Survival Analysis and Reliability. In: Lisnianski, A., Frenkel, I. (eds) Recent Advances in System Reliability. Springer Series in Reliability Engineering. Springer, London. https://doi.org/10.1007/978-1-4471-2207-4_17
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DOI: https://doi.org/10.1007/978-1-4471-2207-4_17
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