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Testing complex social theories with causal mediation analysis and G-computation: toward a better way to do causal structural equation modeling

Pósch, Krisztián (2019) Testing complex social theories with causal mediation analysis and G-computation: toward a better way to do causal structural equation modeling. Sociological Methods and Research. ISSN 0049-1241

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Identification Number: 10.1177/0049124119826159

Abstract

Complex social scientific theories are conventionally tested using linear structural equation modeling (SEM). However, the underlying assumptions of linear SEM often prove unrealistic, making the decomposition of direct and indirect effects problematic. Recent advancements in causal mediation analysis can help to address these shortcomings, allowing for causal inference when a new set of identifying assumptions are satisfied. This article reviews how these ideas can be generalized to multiple mediators, with a focus on the posttreatment confounding and causal ordering cases. Using the potential outcome framework as a rigorous tool for causal inference, the application is the theory of procedural justice policing. Analysis of data from two randomized experiments shows that making similar parametric assumptions to SEMs and using G-computation improve the viability of effect decomposition. The article concludes with a discussion of how causal mediation analysis improves upon SEM and the potential limitation of the methods.

Item Type: Article
Additional Information: © 2019 The Author
Divisions: Methodology
Subjects: H Social Sciences > HM Sociology
Date Deposited: 06 Mar 2019 14:54
Last Modified: 20 Jun 2020 02:43
URI: http://eprints.lse.ac.uk/id/eprint/100222

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