Proportional hazards model

Summary

A proportional hazards model describes how covariates act on the hazard function of an event time. Each covariate multiplies the hazard by a factor that does not change with time. In the Cox model, introduced by David Cox, the hazard is a baseline hazard times $e^{\beta^T x}$, and the baseline is left completely unspecified. The coefficients $\beta$ can be estimated by maximising the partial likelihood, which does not involve the baseline hazard. It is the most used regression model of survival analysis.