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R squared effect-size measures and overlap between direct and indirect effect in mediation analysis

In a recent article in this journal (Fairchild, MacKinnon, Taborga & Taylor, 2009), a method was described for computing the variance accounted for by the direct effect and the indirect effect in mediation analysis. However, application of this method leads to counterintuitive results, most nota...

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Detalles Bibliográficos
Autor principal: de Heus, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer-Verlag 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3278616/
https://www.ncbi.nlm.nih.gov/pubmed/21853410
http://dx.doi.org/10.3758/s13428-011-0141-5
Descripción
Sumario:In a recent article in this journal (Fairchild, MacKinnon, Taborga & Taylor, 2009), a method was described for computing the variance accounted for by the direct effect and the indirect effect in mediation analysis. However, application of this method leads to counterintuitive results, most notably that in some situations in which the direct effect is much stronger than the indirect effect, the latter appears to explain much more variance than the former. The explanation for this is that the Fairchild et al. method handles the strong interdependence of the direct and indirect effect in a way that assigns all overlap variance to the indirect effect. Two approaches for handling this overlap are discussed, but none of them is without disadvantages.