Cook Richard J, Wei Wei
Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, Canada N2L 3G1.
Biostatistics. 2003 Jul;4(3):479-94. doi: 10.1093/biostatistics/4.3.479.
The design of clinical trials is typically based on marginal comparisons of a primary response under two or more treatments. The considerable gains in efficiency afforded by models conditional on one or more baseline responses has been extensively studied for Gaussian models. The purpose of this article is to present methods for the design and analysis of clinical trials in which the response is a count or a point process, and a corresponding baseline count is available prior to randomization. The methods are based on a conditional negative binomial model for the response given the baseline count and can be used to examine the effect of introducing selection criteria on power and sample size requirements. We show that designs based on this approach are more efficient than those proposed by McMahon et al. (1994).
临床试验的设计通常基于两种或更多治疗方法下主要反应的边际比较。对于高斯模型，以一个或多个基线反应为条件的模型所带来的显著效率提升已得到广泛研究。本文的目的是介绍针对反应为计数或点过程且在随机分组前有相应基线计数的临床试验的设计和分析方法。这些方法基于给定基线计数时反应的条件负二项模型，可用于检验引入选择标准对检验效能和样本量要求的影响。我们表明，基于这种方法的设计比麦克马洪等人（1994年）提出的设计更有效。
