Incorporating Contact Network Structure in Cluster Randomized Trials.

ABSTRACT: Whenever possible, the efficacy of a new treatment is investigated by randomly assigning some individuals to a treatment and others to control, and comparing the outcomes between the two groups. Often, when the treatment aims to slow an infectious disease, clusters of individuals are assigned to each treatment arm. The structure of interactions within and between clusters can reduce the power of the trial, i.e. the probability of correctly detecting a real treatment effect. We investigate the relationships among power, within-cluster structure, cross-contamination via between-cluster mixing, and infectivity by simulating an infectious process on a collection of clusters. We demonstrate that compared to simulation-based methods, current formula-based power calculations may be conservative f

SUBMITTER: Staples PC 

PROVIDER: S-EPMC4668393 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature