The following examples demonstrate how you can use the LIFEREG procedure to fit a parametric model to failure time data.
Suppose you have a response variable y that represents failure time; a binary variable, censor, with censor=0 indicating censored values; and two linearly independent variables, x1 and x2. The following statements perform a typical accelerated failure time model analysis. Higher-order effects such as interactions and nested effects are allowed in the independent variables list, but they are not shown in this example.
proc lifereg; model y*censor(0) = x1 x2; run;
PROC LIFEREG can fit models to interval-censored data. The syntax for specifying interval-censored data is as follows:
proc lifereg; model (begin, end) = x1 x2; run;
You can also model binomial data by using the events/trials syntax for the response, as illustrated in the following statements:
proc lifereg; model r/n=x1 x2; run;
The variable n represents the number of trials, and the variable r represents the number of events.