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- Title
Masked analysis for small-scale cluster randomized controlled trials.
- Authors
Ferron, John M.; Nguyen, Diep; Dedrick, Robert F.; Suldo, Shannon M.; Shaunessy-Dedrick, Elizabeth
- Abstract
Researchers conducting small-scale cluster randomized controlled trials (RCTs) during the pilot testing of an intervention often look for evidence of promise to justify an efficacy trial. We developed a method to test for intervention effects that is adaptive (i.e., responsive to data exploration), requires few assumptions, and is statistically valid (i.e., controls the type I error rate), by adapting masked visual analysis techniques to cluster RCTs. We illustrate the creation of masked graphs and their analysis using data from a pilot study in which 15 high school programs were randomly assigned to either business as usual or an intervention developed to promote psychological and academic well-being in 9th grade students in accelerated coursework. We conclude that in small-scale cluster RCTs there can be benefits of testing for effects without a priori specification of a statistical model or test statistic.
- Subjects
CLUSTER randomized controlled trials; CLUSTER analysis (Statistics); FALSE positive error; PSYCHOLOGICAL well-being
- Publication
Behavior Research Methods, 2022, Vol 54, Issue 4, p1701
- ISSN
1554-351X
- Publication type
Article
- DOI
10.3758/s13428-021-01708-0