Statistical considerations in the design and analysis of community intervention trials

Abstract

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.