Donner A, Klar N
Department of Epidemiology and Biostatistics, University of Western Ontario, London, Canada.
J Clin Epidemiol. 1996 Apr;49(4):435-9. doi: 10.1016/0895-4356(95)00511-0.
Community intervention trials are often characterized by the allocation of intact social units to different intervention groups. The assessment of adequate sample size for such trials must take into account the statistical dependencies among responses observed within an allocated unit. However, the small numbers of units typically involved in such trials imply that many methods of analysis that have been proposed for analyzing correlated data, particularly in the case of a dichotomous outcome variable, are not applicable to such designs. In this article we investigate this issue and determine the minimum number of units required per group, for the case of both a dichotomous and a continuous outcome variable, needed to provide adequate statistical power for detecting various levels of treatment effect. The use of significance testing as a method of detecting intracluster correlation is also investigated, and, in general, discouraged.
社区干预试验的特点通常是将完整的社会单位分配到不同的干预组。对此类试验足够样本量的评估必须考虑在分配单位内观察到的反应之间的统计相关性。然而，此类试验通常涉及的单位数量较少，这意味着许多已提出的用于分析相关数据的分析方法，特别是在二分结果变量的情况下，不适用于此类设计。在本文中，我们研究了这个问题，并确定了对于二分和连续结果变量的情况，每组所需的最小单位数量，以提供足够的统计功效来检测不同水平的治疗效果。还研究了将显著性检验用作检测聚类内相关性的方法，总体而言，不鼓励使用这种方法。
