STATISTICAL METHODOLOGY FOR PAIRED CLUSTER DESIGNS1

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Abstract
Recently developed methodology is applied to the analysis of data arising from a design in which an experimental intervention is assigned at random to one of two clusters in a matched pair. Standard statistical techniques do not apply to such data, since they do not take to account variation arising from differences among clusters as well as within clusters. The methodology presented provides a significance test over k pairs of clusters with respect to a dichotomous outcome variable while controlling for confounding. The investigation of interaction effects is also discussed.