Methods for Synthesizing Findings on Moderation Effects Across Multiple Randomized Trials

C. Hendricks Brown, Zili Sloboda, Fabrizio Faggiano, Brent Teasdale, Ferdinand Keller, Gregor Burkhart, Federica Vigna-Taglianti, George Howe, Katherine Masyn, Wei Wang, Bengt Muthén, Peggy Stephens, Scott Grey, Tatiana Perrino

Research output: Contribution to journalArticlepeer-review

48 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)144-156
Number of pages13
JournalPrevention Science
Volume14
Issue number2
DOIs
StatePublished - Jan 1 2013

Keywords

  • Integrative data analysis
  • Meta-analysis
  • Parallel data analysis
  • Subgroup analyses
  • Variation in impact

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

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