Lachin John M
The Biostatistics Center, Departments of Epidemiology and Biostatistics, and Statistics, The George Washington University, 6110 Executive Boulevard, Suite 750, Rockville, Maryland, USA. 20852.
Stat Med. 2013 Nov 10;32(25):4413-25. doi: 10.1002/sim.5839. Epub 2013 May 13.
I describe general expressions for the evaluation of sample size and power for the K group Mantel-logrank test or the Cox proportional hazards (PH) model score test. Under an exponential model, the method of Lachin and Foulkes for the 2 group case is extended to the K ⩾2 group case using the non-centrality parameter of the K - 1 df chi-square test. I also show similar results to apply to the K group score test in a Cox PH model. Lachin and Foulkes employed a truncated exponential distribution to provide for a non-linear rate of enrollment. I present expressions for the mean time of enrollment and the expected follow-up time in the presence of exponential losses to follow-up. When used with the expression for the noncentrality parameter for the test, equations are derived for the evaluation of sample size and power under specific designs with r years of recruitment and T years total duration. I also describe sample size and power for a stratified-adjusted K group test and for the assessment of a group by stratum interaction. Similarly, I describe computations for a stratified-adjusted analysis of a quantitative covariate and a test of a stratum by covariate interaction in the Cox PH model.
我描述了用于评估K组Mantel - logrank检验或Cox比例风险(PH)模型得分检验的样本量和检验效能的一般表达式。在指数模型下,将Lachin和Foulkes用于两组情况的方法,利用K - 1自由度卡方检验的非中心参数扩展到K⩾2组的情况。我还展示了类似的结果适用于Cox PH模型中的K组得分检验。Lachin和Foulkes采用截断指数分布来考虑非线性入组率。我给出了存在指数失访情况下的平均入组时间和预期随访时间的表达式。当与检验的非中心参数表达式一起使用时,推导出了在r年招募期和T年总时长的特定设计下评估样本量和检验效能的方程。我还描述了分层调整的K组检验以及组间分层交互作用评估的样本量和检验效能。同样,我描述了Cox PH模型中定量协变量分层调整分析以及协变量分层交互作用检验的计算方法。