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  "body": "\n## Summary\n\nA proportional hazards model describes how covariates act on the [[hazard function|Y959NKQ3XW]] of an event time.\nEach covariate multiplies the hazard by a factor that does not change with time.\nIn 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.\nThe coefficients $\\beta$ can be estimated by maximising the partial likelihood, which does not involve the baseline hazard.\nIt is the most used regression model of [[survival analysis|443ZWDX88P]].\n\n## Explanations\n\n### L1 human\n\nSuppose smokers have, at every age, twice the risk of a heart attack of non-smokers.\nThe risk itself may rise with age in a complicated way, but the ratio stays $2$.\nA proportional hazards model says exactly this: each factor scales the whole hazard curve up or down by a fixed amount.\nThe doubling corresponds to a coefficient $\\beta = \\log 2$ for the smoking indicator.\nThe method can estimate this ratio without ever estimating the shape of the age curve.\n",
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