Research on Statistical Analysis of Causal Mechanisms

An important goal of social science research is the analysis of causal mechanisms. A common framework for the statistical analysis of mechanisms has been mediation analysis, routinely conducted by applied researchers in a variety of disciplines including epidemiology, political science, psychology, and sociology. The goal of such an analysis is to investigate alternative causal mechanisms by examining the roles of intermediate variables that lie in the causal path between the treatment and outcome variables. In this collection of papers we advance the statistical analysis and experimental design of causal mechanisms in several important ways. 1) We formalize mediation analysis in terms of the well established potential outcome framework for causal inference. 2) We introduce a minimal set of assumptions thatidentify the causal mediation effects. 3) We show how to conduct sensitivity analyses to violations of this identifying assumption. Our sensitivity analysis allows researchers to ask, how large a violation would be necessary before their results would be reversed. 4) We extend our proposed methods to various types of data and statistical models. Our method can accommodate linear and nonlinear relationships, parametric and nonparametric models, continuous and discrete mediators, and different types of outcome variables. 5) We show how to design randomized experiments in order to identify causal mechanisms. 6) We provide an easy to use package in the free software language R that implements everything discussed in the papers.

Imai, Kosuke, Dustin Tingley, and Teppei Yamamoto. ``Experimental Identification of Causal Mechanisms.''

Imai, Kosuke, Luke Keele, and Teppei Yamamoto. ``Identification, Inference, and Sensitivity Analysis for Causal Mediation Effects.''

Imai, Kosuke, Luke Keele, and Dustin Tingley. ``A General Approach to Causal Mediation Analysis.''

Imai, Kosuke, Luke Keele, Dustin Tingley, and Teppei Yamamoto. (2010). ``Causal Mediation Analysis Using R,'' in Advances in Social Science Research Using R, ed. H. D. Vinod, New York: Springer (Lecture Notes in Statistics), pp. 129-154.

Presentation slides that are used to describe our project at the 2009 Summer Political Methodology Conference and the Experiments in Governance and Politics Conference are available for download (PolMeth and EGAP).

Keele, Luke, Dustin Tingley, Teppei Yamamoto, and Kosuke Imai. ``mediation: R Package for Causal Mediation Analysis.'' available through The Comprehensive R Archive Network. 2009.