The ICLIFETEST Procedure

Recall the breast cancer data in the example in the section Getting Started: ICLIFETEST Procedure. The following statements perform the generalized log-rank test to compare the survival distributions between two treatments by using Finkelstein’s weights and save the corresponding scores to a SAS data set named Out:

proc iclifetest data=bcs impute(seed=123);
   time (ltime,rtime);
   test trt/weight=finkelstein outscore=out;
run;

Fay (1999) describes how to perform permutation tests by using these generated scores. PROC NPAR1WAY can do such tests and compute p-values based on normal theory approximation or Monte Carlo simulation. You need to specify the input data and specify SCORES=DATA, as follows:

proc npar1way data=out scores=data;
   class trt;
   var score;
   exact scores=data / mc seed=1234;
run;

The variable Trt is specified in the CLASS statement so that permutations are done for the groups formed by different levels of the variable. The MC option performs a Monte Carlo version of the permutation test and computes the p-values by using Monte Carlo samples. Output 62.4.1 shows the results from the test based on normal theory approximation.

Output 62.4.2 displays the p-values that are calculated from the Monte Carlo samples.

Output 62.4.3 displays the results of the generalized log-rank statistics from using Finkelstein’s weights. As you can see, it matches the two-sample test statistic of the permutation test.