Analysis of counts for cluster randomized trials: Negative controls and test-negative designs.

ABSTRACT: In cluster randomized trials (CRTs), the outcome of interest is often a count at the cluster level. This occurs, for example, in evaluating an intervention with the outcome being the number of infections of a disease such as HIV or dengue or the number of hospitalizations in the cluster. Standard practice analyzes these counts through cluster outcome rates using an appropriate denominator (eg, population size). However, such denominators are sometimes unknown, particularly when the counts depend on a passive community surveillance system. We consider direct comparison of the counts without knowledge of denominators, relying on randomization to balance denominators. We also focus on permutation tests to allow for small numbers of randomized clusters. However, such approaches are subject to

SUBMITTER: Dufault SM 

PROVIDER: S-EPMC7448573 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature