The Causal Mediation Formula—A Guide to the Assessment of Pathways and Mechanisms

The Causal Mediation Formula—A Guide to the Assessment of Pathways and Mechanisms Recent advances in causal inference have given rise to a general and easy-to-use formula for assessing the extent to which the effect of one variable on another is mediated by a third. This Mediation Formula is applicable to nonlinear models with both discrete and continuous variables, and permits the evaluation of path-specific effects with minimal assumptions regarding the data-generating process. We demonstrate the use of the Mediation Formula in simple examples and illustrate why parametric methods of analysis yield distorted results, even when parameters are known precisely. We stress the importance of distinguishing between the necessary and sufficient interpretations of “mediated-effect” and show how to estimate the two components in nonlinear systems with continuous and categorical variables. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Prevention Science Springer Journals

The Causal Mediation Formula—A Guide to the Assessment of Pathways and Mechanisms

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Publisher
Springer US
Copyright
Copyright © 2012 by Society for Prevention Research
Subject
Medicine & Public Health; Public Health; Health Psychology; Child and School Psychology
ISSN
1389-4986
eISSN
1573-6695
D.O.I.
10.1007/s11121-011-0270-1
Publisher site
See Article on Publisher Site

Abstract

Recent advances in causal inference have given rise to a general and easy-to-use formula for assessing the extent to which the effect of one variable on another is mediated by a third. This Mediation Formula is applicable to nonlinear models with both discrete and continuous variables, and permits the evaluation of path-specific effects with minimal assumptions regarding the data-generating process. We demonstrate the use of the Mediation Formula in simple examples and illustrate why parametric methods of analysis yield distorted results, even when parameters are known precisely. We stress the importance of distinguishing between the necessary and sufficient interpretations of “mediated-effect” and show how to estimate the two components in nonlinear systems with continuous and categorical variables.

Journal

Prevention ScienceSpringer Journals

Published: Mar 15, 2012

References

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