In survival analysis, the proportional hazard model, also called the Cox model, is a classical semi-parameter method. It relates the time to an event, usually death or failure, to a number of explanatory variables known as covariates. Some of the observations are right-censored, that is the exact time to failure is not known, only that it is greater than a known time.
Following a CoxPHM Analysis, we obtain the parameter estimates and other statistics that are associated with the Cox Proportional hazards model for fixed covariates. From the result of Cox analysis, you can forecast changes in the hazard rate along with a variety of fixed covariates.
If there are missing values in the Time/Censor/Covariate range, the whole case will be excluded in the analysis
To compute the Cox Proportional Hazards regression:
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