Proportional hazards models are a class of survival models in statistics. Survival models relate the time that passes before some event occurs to one or more covariates that may be associated with that quantity of time. In a proportional hazards model, the unique effect of a unit increase in a covariate is multiplicative with respect to the hazard rate. For example, taking a drug may halve one's hazard rate for a stroke occurring, or, changing the material from which a manufactured component is constructed may double its hazard rate for failure. Other types of survival models such as accelerated failure time models do not exhibit proportional hazards. These models could describe a situation such as a drug that reduces a subject's immediate risk of having a stroke, but where there is no reduction in the hazard rate after one year for subjects who do not have a stroke in the first year of analysis.
Read more about Proportional Hazards Models: Introduction, The Partial Likelihood, Time-varying Predictors and Coefficients, Specifying The Baseline Hazard Function, Relationship To Poisson Models, See Also
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