title: Cutoff designs for community-based intervention studies.
abstract: Public health interventions are often designed to target communities defined either geographically (e.g. cities, counties) or socially (e.g. schools or workplaces). The group randomized trial (GRT) is regarded as the gold standard for evaluating these interventions. However, community leaders may object to randomization as some groups may be denied a potentially beneficial intervention. Under a regression discontinuity design (RDD), individuals may be assigned to treatment based on the levels of a pretest measure, thereby allowing those most in need of the treatment to receive it. In this article, we consider analysis, power, and sample size issues in applying the RDD and related cutoff designs in community-based intervention studies. We examine the power of these designs as a function of intraclass correlation, number of groups, and number of members per group and compare results to the traditional GRT.
authors.affiliation: Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH 43210, U.S.A. mpennell@cph.osu.edu
authors.forename: Michael L
authors.initials: ML
authors.lastname: Pennell
authors.forename: Erinn M
authors.initials: EM
authors.lastname: Hade
authors.forename: David M
authors.initials: DM
authors.lastname: Murray
authors.forename: Dale A
authors.initials: DA
authors.lastname: Rhoda
mesh_terms: D000293:Adolescent; D000704:Analysis of Variance; D053198:Child Nutrition Sciences / Q000193:education; D055812:Community-Based Participatory Research / Q000379:methods / Q000458:organization & administration*; D003430:Cross-Sectional Studies; D004032:Diet; D015340:Epidemiologic Research Design; D005260:Female; D006293:Health Promotion / Q000379:methods*; D006801:Humans; D009043:Motor Activity; D018401:Sample Size; D012574:Schools