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Masked analysis for small-scale cluster randomized controlled trials.
- Source :
- Behavior Research Methods; Aug2022, Vol. 54 Issue 4, p1701-1714, 14p
- Publication Year :
- 2022
-
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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1554351X
- Volume :
- 54
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Behavior Research Methods
- Publication Type :
- Academic Journal
- Accession number :
- 158510510
- Full Text :
- https://doi.org/10.3758/s13428-021-01708-0