Wallenstein S, Wittes J
Department of Biomathematics, Mount Sinai Medical School, New York, New York 10029.
Biometrics. 1993 Dec;49(4):1077-87.
The Mantel-Haenszel test for grouped failure time data (MHF test) compares the distribution of failure times in two cohorts followed for an interval of time when the data are collected in discrete subintervals. This paper derives approximations to the power of the Mantel-Haenszel test for arbitrary failure time distributions in the presence of censoring. The approximations are appropriate for both equal and nonequal odds ratios in the constituent tables, and can be used for arbitrary subdivisions of time. Four approximations are proposed. They differ from each other according to whether the parameter measuring treatment effect is an odds ratio or a difference in proportions, and whether the survival distributions are calculated under the null or alternative hypothesis. In addition, we demonstrate that when the hazards are constant, increasing the number of subintervals often produces only a negligible increase in the power of the MHF test. On the other hand, for arbitrary hazards and nonconstant hazard ratios, the choice of frequency and actual times of measurement can have important effects on power. Finally, the paper presents simple expressions for power under exponential failure and censoring models.
用于分组失效时间数据的Mantel-Haenszel检验（MHF检验），在数据按离散子区间收集时，比较两个队列在一段时间内随访的失效时间分布。本文推导了在存在删失情况下，针对任意失效时间分布的Mantel-Haenszel检验功效的近似值。这些近似值适用于构成表中比值比相等和不相等的情况，并且可用于时间的任意细分。提出了四种近似值。它们彼此不同之处在于，测量治疗效果的参数是比值比还是比例差异，以及生存分布是在原假设还是备择假设下计算的。此外，我们证明，当风险恒定时，增加子区间的数量通常只会使MHF检验的功效产生可忽略不计的增加。另一方面，对于任意风险和非恒定风险比，测量频率和实际时间的选择可能会对功效产生重要影响。最后，本文给出了指数失效和删失模型下功效的简单表达式。
