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.
journal_name
Stat Medjournal_title
Statistics in medicineauthors
Pennell ML,Hade EM,Murray DM,Rhoda DAdoi
10.1002/sim.4237subject
Has Abstractpub_date
2011-07-10 00:00:00pages
1865-82issue
15eissn
0277-6715issn
1097-0258journal_volume
30pub_type
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