Cox Proportional-Hazards Regression Model
The basis for the Cox regression models comes from the survival analysis, a set of statistical methods helpful in investigating the time it takes for an event to occur. Some examples are as follows:
Time until a lead is converted to sales
Time until a product failure from the start of usage
Time after the start of the insurance policy until death
Time after diagnosing until death
Time until a warranty is claimed for a product
Time from customer registration
All these examples are some of the use cases of survival analysis. In most of the survival analysis, there are three wide-spread methods used for carrying out such time-to-event analysis:
Kaplan-Meier survival curves for analysis of different groups
The logrank test for comparing two or more survival curves
Cox proportional hazards regression to describe the effect of variables on survival
Keeping in mind the scope of this chapter and book, we will focus only on the Cox proportional hazards regression. The...