Effective sample size for tests of censored survival data

SUMMARY 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.

[1]  M. Sobel,et al.  CONTRIBUTIONS TO THE THEORY OF RANK ORDER STATISTICS. THE TWO-SAMPLE CENSORED CASE , 1960 .

[2]  Nathan Mantel,et al.  Chi-square tests with one degree of freedom , 1963 .

[3]  E. Gehan A GENERALIZED WILCOXON TEST FOR COMPARING ARBITRARILY SINGLY-CENSORED SAMPLES. , 1965, Biometrika.

[4]  N. Mantel Evaluation of survival data and two new rank order statistics arising in its consideration. , 1966, Cancer chemotherapy reports.

[5]  Edmund A. Gehan,et al.  The performance of some two-sample tests in small samples with and without censoring , 1969 .

[6]  N. Breslow A generalized Kruskal-Wallis test for comparing K samples subject to unequal patterns of censorship , 1970 .

[7]  J. Peto,et al.  Asymptotically Efficient Rank Invariant Test Procedures , 1972 .

[8]  Elisa T. Lee,et al.  A Monte Carlo study of the power of some two-sample tests , 1975 .

[9]  P. Armitage,et al.  Design and analysis of randomized clinical trials requiring prolonged observation of each patient. I. Introduction and design. , 1976, British Journal of Cancer.

[10]  D G Thomas,et al.  Trend and homogeneity analyses of proportions and life table data. , 1977, Computers and biomedical research, an international journal.

[11]  James H. Ware,et al.  On distribution-free tests for equality of survival distributions , 1977 .

[12]  Mitchell H. Gail,et al.  Comparison of four tests for equality of survival curves in the presence of stratification and censoring , 1979 .