Synthesizing Indirect Effects in Mediation Models With Meta-Analytic Methods.

Aims A mediator is a variable that explains the underlying mechanism between an independent variable and a dependent variable. The indirect effect indicates the effect from the predictor to the outcome variable via the mediator. In contrast, the direct effect represents the predictor's effort on the...

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Publicado en:Alcohol & Alcoholism Vol. 57; no. 1; pp. 5 - 16
Autor principal: Cheung, Mike W-L
Formato: equations & formulas tables/charts Journal Article
Publicado: Oxford University Press / USA Jan2022
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Oxford University Press / USA
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        atl: Synthesizing Indirect Effects in Mediation Models With Meta-Analytic Methods.
      aug:
        au: Cheung, Mike W-L
        affil: Department of Psychology , National University of Singapore , Singapore 117570
      sug:
        subj:
          Research Personnel Education
          Research, Medical
          Effect Size
          Meta Analysis
          Mediation Analysis
          Structural Equation Modeling
          Research Question
          Software
      ab: Aims A mediator is a variable that explains the underlying mechanism between an independent variable and a dependent variable. The indirect effect indicates the effect from the predictor to the outcome variable via the mediator. In contrast, the direct effect represents the predictor's effort on the outcome variable after controlling for the mediator. Methods A single study rarely provides enough evidence to answer research questions in a particular domain. Replications are generally recommended as the gold standard to conduct scientific research. When a sufficient number of studies have been conducted addressing similar research questions, a meta-analysis can be used to synthesize those studies' findings. Results The main objective of this paper is to introduce two frameworks to integrating studies using mediation analysis. The first framework involves calculating standardized indirect effects and direct effects and conducting a multivariate meta-analysis on those effect sizes. The second one uses meta-analytic structural equation modeling to synthesize correlation matrices and fit mediation models on the average correlation matrix. We illustrate these procedures on a real dataset using the R statistical platform. Conclusion This paper closes with some further directions for future studies.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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