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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
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author de Heus, Peter
author_facet de Heus, Peter
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description 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.
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spelling pubmed-32786162012-02-21 R squared effect-size measures and overlap between direct and indirect effect in mediation analysis de Heus, Peter Behav Res Methods Article 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. Springer-Verlag 2011-08-19 2012 /pmc/articles/PMC3278616/ /pubmed/21853410 http://dx.doi.org/10.3758/s13428-011-0141-5 Text en © The Author(s) 2011 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
spellingShingle Article
de Heus, Peter
R squared effect-size measures and overlap between direct and indirect effect in mediation analysis
title R squared effect-size measures and overlap between direct and indirect effect in mediation analysis
title_full R squared effect-size measures and overlap between direct and indirect effect in mediation analysis
title_fullStr R squared effect-size measures and overlap between direct and indirect effect in mediation analysis
title_full_unstemmed R squared effect-size measures and overlap between direct and indirect effect in mediation analysis
title_short R squared effect-size measures and overlap between direct and indirect effect in mediation analysis
title_sort r squared effect-size measures and overlap between direct and indirect effect in mediation analysis
topic Article
url 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
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