© 1982 by Biometrika Trust
Effective sample size for tests of censored survival data
1Department of Medicine, University of Washington Seattle, Washington, U.S.A
2Department of Biomathematics, University of California Los Angeles, California, U.S.A
3Children's Cancer Study Group, University of Southern California Los Angeles, California, U.S.A
4Rand Corporation, Santa Monica California, U.S.A
5Boeing C. Services, Energy Technology Division Seattle, Washington, U.S.A.
When survival experience of two groups is compared in the presence of arbitrary right censoring, the effective sample size for determining the power of the test used is usually taken to be the number of uncensored observations. This convention is examined through a Monte Carlo study. Empirical powers of the generalized Savage test and generalized Wilcoxon test with uncensored data are compared to those with censored data containing approximately the same number of uncensored observations. Large sample relative efficiencies are calculated for a Lehmann family of alternatives. It is shown that, depending on the underlying distribution and censoring mechanism, censored observations can add appreciably to the power of either test.
Key Words: Asymptotic relative efficiency • Censored survival data • Effective sample size • Exponential distribution • Gamma distribution • Generalized Savage teat • Generalized Wilcoxon test • Power