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35 - Mediation Analysis Is Harder Than It Looks

Published online by Cambridge University Press:  05 June 2012

By
John G. Bullock  and
Shang E. Ha
Edited by
James N. Druckman ,
Donald P. Greene ,
James H. Kuklinski  and
Arthur Lupia
John G. Bullock
Affiliation:
Yale University
Shang E. Ha
Affiliation:
City University of New York
James N. Druckman
Affiliation:
Northwestern University, Illinois
Donald P. Greene
Affiliation:
Yale University, Connecticut
James H. Kuklinski
Affiliation:
University of Illinois, Urbana-Champaign
Arthur Lupia
Affiliation:
University of Michigan, Ann Arbor
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Summary

Mediators are variables that transmit causal effects from treatments to outcomes. Those who undertake mediation analysis seek to answer “how” questions about causation: how does this treatment affect that outcome? Typically, we desire answers of the form “the treatment affects a causally intermediate variable, which in turn affects the outcome.” Identifying these causally intermediate variables is the challenge of mediation analysis.

Conjectures about political mediation effects are as old as the study of politics. But codification of procedures by which to test hypotheses about mediation is a relatively new development. The most common procedures are now ubiquitous in psychology (Quiñones-Vidal et al. 2004) and increasingly popular in the other social sciences, not least political science.

Unfortunately, the most common procedures are not very good. They call for indirect effects – the portions of treatment effects that are transmitted through mediators – to be estimated via multiequation regression frameworks. These procedures do not require experimental manipulation of mediators; instead, they encourage the study of mediation with data from unmanipulated mediators (MacKinnon et al. 2002, 86; Spencer, Zanna, and Fong 2005). The procedures are therefore prone to producing biased estimates of mediation effects. Warnings about this problem have been issued for decades by statisticians, psychologists, and political scientists.

Type
Chapter
Information
Cambridge Handbook of Experimental Political Science , pp. 508 - 522
Publisher: Cambridge University Press
Print publication year: 2011

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