The Large Sample Distribution of the Weighted Log Rank Statistic under General Local Alternatives

被引：36

作者：

Ewell M. ^{[1
]}

Ibrahim J.G. ^{[2
,3
]}

机构：

[1] Department of Biostatistics, Harvard School of Public Health, Dana Farber Cancer Institute, Boston, MA 02115

[2] Division of Biostatistics, Dana Farber Cancer Institute, Boston, MA 02115

来源：

Lifetime Data Analysis | 1997年 / 3卷 / 1期

基金：

美国国家卫生研究院;

关键词：

Clinical trial; Cure rate model; Power; Sample size; Weighted log rank;

D O I：

10.1023/A:1009690200504

中图分类号：

学科分类号：

摘要：

We derive the large sample distribution of the weighted log rank statistic under a general class of local alternatives in which both the cure rates and the conditional distribution of time to failure among those who fail are assumed to vary in the two treatment arms. The analytic result presented here is important to data analysts who are designing clinical trials for diseases such as non-Hodgkins lymphoma, leukemia and melanoma, where a significant proportion of patients are cured. We present a numerical illustration comparing powers obtained from the analytic result to those obtained from simulations.

引用

页码：5 / 12

页数：7

共 14 条

[1]

Farewell V.T., The use of mixture models for the analysis of survival data with long-term survivors, Biometrics, 38, pp. 1041-1046, (1982)

[2]

Farewell V.T., Mixture models in survival analysis: Are they worth the risk?, Canadian Journal of Statistics, 14, pp. 257-262, (1986)

[3]

Gill R.D., Censoring and stochastic integrals, Mathematical Centre Tracts 124

[4]

Goldman A.I., Survivorship analysis when cure is a possibility: A Monte Carlo study, Statistics in Medicine, 3, pp. 153-163

[5]

Gray R.J., Tsiatis A.A., A linear rank test for use when the main interest is in differences in cure rates, Biometrics, 45, pp. 899-904, (1989)

[6]

Halpern J., Brown Jr. B.W., Cure rate models: Power of the log rank and generalized Wilcoxon tests, Statistics in Medicine, 6, pp. 483-489, (1987)

[7]

Halpern J., Brown Jr. B.W., Designing clinical trials with arbitrary specification of survival functions and for the log rank or generalized Wilcoxon test, Controlled Clinical Trials, 8, pp. 177-189, (1987)

[8]

Harrington D.P., Fleming T.R., A class of rank test procedures for censored survival data, Biometrika, 69, pp. 553-566, (1982)

[9]

Kuk A.Y.C., Chen C.-H., A mixture model combining logistic regression with proportional hazards regression, Biometrika, 79, pp. 531-541, (1992)

[10]

Laska E.M., Meisner M.J., Nonparametric estimation and testing in a cure rate model, Biometrics, 48, pp. 1223-1234, (1992)

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