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01-11-2021

A Unification of Mediator, Confounder, and Collider Effects

Authors: David P. MacKinnon, Sophia J. Lamp

Published in: Prevention Science | Issue 8/2021

Abstract

Third-variable effects, such as mediation and confounding, are core concepts in prevention science, providing the theoretical basis for investigating how risk factors affect behavior and how interventions change behavior. Another third variable, the collider, is not commonly considered but is also important for prevention science. This paper describes the importance of the collider effect as well as the similarities and differences between these three third-variable effects. The single mediator model in which the third variable (T) is a mediator of the independent variable (X) to dependent variable (Y) effect is used to demonstrate how to estimate each third-variable effect. We provide difference in coefficients and product of coefficients estimators of the effects and demonstrate how to calculate these values with real data. Suppression effects are defined for each type of third-variable effect. Future directions and implications of these results are discussed.

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This paper describes adjustment as including an additional predictor in a regression model. Adjustment comes in other forms and names including conditioning on a variable, controlling for a variable, stratifying by a variable, and selection into a study by a variable (see Elwert & Winship, 2014 and Morgan & Winship, 2015 for more on these topics).

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Title: A Unification of Mediator, Confounder, and Collider Effects
Authors: David P. MacKinnon
Sophia J. Lamp
Publication date: 01-11-2021
Publisher: Springer US
Published in: Prevention Science / Issue 8/2021
Print ISSN: 1389-4986
Electronic ISSN: 1573-6695
DOI: https://doi.org/10.1007/s11121-021-01268-x

At a glance: The STEP trials

Springer Medicine

A Unification of Mediator, Confounder, and Collider Effects

Abstract

At a glance: The STEP trials

Springer Medicine

Abstract

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