Testing treatment effect by combining weighted log-rank tests and using empirical likelihood

Song Yang and Yichuan Zhao

Statistics & Probability Letters, 2007, vol. 77, issue 12, 1385-1393

Abstract: For testing treatment effect with time to event data, combinations of several tests are often desired when the hazard functions of the two groups are nonproportional. Yang and Prentice [2005. Semiparametric analysis of short term and long term hazard ratios with two sample survival data. Biometrika 92, 1-17.] defined a new two-sample semiparametric model that accommodates nonproportional hazard functions and contains the Cox model and the proportional odds model as two submodels. They also obtained a [chi]2 test on the parameter that reduces to the [chi]2 test based on weighted log-rank tests for testing the null hypothesis of no treatment effect. In this paper, we consider a new [chi]2 test using the empirical likelihood method. Extensive simulation studies were conducted to compare the performance of the test with other related ones, for a variety of combinations of the short-term and long-term treatment effects.

Keywords: Clinical; trials; Crossing; survival; curves; Survival; analysis; Weighted; log-rank; tests (search for similar items in EconPapers)
Date: 2007
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