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. 2013 Jun;18(2):137-50.
doi: 10.1037/a0031034. Epub 2013 Feb 4.

Mediation analysis allowing for exposure-mediator interactions and causal interpretation: theoretical assumptions and implementation with SAS and SPSS macros

Linda Valeri  1 , Tyler J Vanderweele
Affiliations

Mediation analysis allowing for exposure-mediator interactions and causal interpretation: theoretical assumptions and implementation with SAS and SPSS macros

Linda Valeri et al. Psychol Methods. 2013 Jun.

Erratum in

  • Psychol Methods. 2013 Dec;18(4):474

Abstract

Mediation analysis is a useful and widely employed approach to studies in the field of psychology and in the social and biomedical sciences. The contributions of this article are several-fold. First we seek to bring the developments in mediation analysis for nonlinear models within the counterfactual framework to the psychology audience in an accessible format and compare the sorts of inferences about mediation that are possible in the presence of exposure-mediator interaction when using a counterfactual versus the standard statistical approach. Second, the work by VanderWeele and Vansteelandt (2009, 2010) is extended here to allow for dichotomous mediators and count outcomes. Third, we provide SAS and SPSS macros to implement all of these mediation analysis techniques automatically, and we compare the types of inferences about mediation that are allowed by a variety of software macros.

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Figures

Figure 1
Figure 1
Mediation model in Baron and Kenny 1986 paper.
Figure 2
Figure 2
Causal Diagram for Mediation and Confounding
See this image and copyright information in PMC

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