This essay is an introduction to survival models in the context of generalized linear models. We introduce the hazard and survival functions and describe the most common censoring mechanisms and the resulting likelihood function. We discuss the main approaches to modeling waiting times, including accelerated life and proportional hazard models, with extensions to time-varying covariates and time-dependent effects. We then focus on the piece-wise exponential survival model and note its equivalence with Poisson regression models. We illustrate this approach with an application to the analysis of infant and child mortality in Colombia using survey data. We conclude with a brief discussion of discrete time models and their equivalence with logistic regression.
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Article provided by Quantile in its journal Quantile.