A Monte Carlo Power Study of Logrank, Wilcoxon and Normal Scores Procedures on Matched and Censored Data

The powers of several nonparametric tests for determining a treatment effect using matched censored data are compared by simulation. The tests include adaptations of two sample Prentice efficient score extensions of the Exponential Scores, Wilcoxon and Normal Scores tests with three different variance estimators. The tests are compared on simulated exponential, loglogistic and lognormal matched censored data. No test performed uniformly better than the others. However the Exponential Scores, or Logrank, test using the permutation or hypergeometric variance seemed to be more powerful in quite a few situations as well as having other advantages.