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Methods for Synthesizing Findings on Moderation Effects Across Multiple Randomized Trials

Abstract  

This paper presents new methods for synthesizing results from subgroup and moderation analyses across different randomized
trials. We demonstrate that such a synthesis generally results in additional power to detect significant moderation findings
above what one would find in a single trial. Three general methods for conducting synthesis analyses are discussed, with two
methods, integrative data analysis and parallel analyses, sharing a large advantage over traditional methods available in
meta-analysis. We present a broad class of analytic models to examine moderation effects across trials that can be used to
assess their overall effect and explain sources of heterogeneity, and present ways to disentangle differences across trials
due to individual differences, contextual level differences, intervention, and trial design.

  • Content Type Journal Article
  • Pages 1-13
  • DOI 10.1007/s11121-011-0207-8
  • Authors
    • C. Hendricks Brown, University of Miami, Miller School of Medicine, Miami, FL USA
    • Zili Sloboda, JBS International, Rockville, MD USA
    • Fabrizio Faggiano, Avogadro University, Novara, Italy
    • Brent Teasdale, Georgia State University, Atlanta, GA USA
    • Ferdinand Keller, University of Ulm, Ulm, Germany
    • Gregor Burkhart, European Monitoring Centre for Drugs and Drug Addiction, Lisbon, Portugal
    • Federica Vigna-Taglianti, Piedmont Centre for Drug Addiction Epidemiology, Grugliasco, Italy
    • George Howe, George Washington University, Washington, DC USA
    • Katherine Masyn, Harvard University, Cambridge, MA USA
    • Wei Wang, University of South Florida, Tampa, FL USA
    • Bengt Muthén, UCLA, Los Angeles, CA USA
    • Peggy Stephens, Akron University, Akron, OH USA
    • Scott Grey, Kent State University, Kent, OH USA
    • Tatiana Perrino, University of Miami, Miller School of Medicine, Miami, FL USA
    • Prevention Science and Methodology Group
    • Journal Prevention Science
    • Online ISSN 1573-6695
    • Print ISSN 1389-4986
Posted in: Meta-analyses - Systematic Reviews on 03/02/2011 | Link to this post on IFP |
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