Imai, Kosuke, Luke Keele, Dustin Tingley, and Teppei Yamamoto. (2011). ``Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies.'' American Political Science Review, Vol. 105, No. 4 (November), pp. 765-789. Reprinted in Advances in Political Methodology, R. Franzese, Jr. ed., Edward Elger, 2017.
Identifying causal mechanisms is a fundamental goal of social science. Researchers seek to study not only whether one variable affects another but also how such a causal relationship arises. Yet, commonly used statistical methods for identifying causal mechanisms rely upon untestable assumptions and are often inappropriate even under those assumptions. Randomizing treatment and intermediate variables is also insufficient. Despite these difficulties, study of causal mechanisms is too important to abandon. We make three contributions to improve research on causal mechanisms. First, we present a minimum set of assumptions required under standard designs of experimental and observational studies and develop a general algorithm for estimating causal mediation effects. Second, we provide a method to assess sensitivity of conclusions to potential violations of a key assumption. Third, we offer alternative research designs for identifying causal mechanisms under weaker assumptions. The proposed approach is illustrated using media framing experiments and incumbency advantage studies. |
Imai, Kosuke, and Zhichao Jiang
(2020).
``Identification and Sensitivity Analysis of Contagion Effects in Randomized Placebo-Controlled Trials.''
Journal of the Royal Statistical Society, Series A (Statistics in Society), Vol. 183, No. 4 (October), pp. 1637-1657.
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Imai, Kosuke, Luke Keele, Dustin Tingley, and Teppei Yamamoto
(2014).
``Comment on Pearl: Practical Implications of Theoretical Results for Causal Mediation Analysis.''
Psychological Methods, Vol. 19, No. 4 (December), 482-487.
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Tingley, Dustin, Teppei Yamamoto, Luke Keele, and Kosuke Imai
(2014).
``mediation: R Package for Causal Mediation Analysis.''
Journal of Statistical Software, Vol. 59, No. 5 (August), pp. 1-38.
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Imai, Kosuke and Teppei Yamamoto
(2013).
``Identification and Sensitivity Analysis for Multiple Causal Mechanisms: Revisiting Evidence from Framing Experiments.''
Political Analysis, Vol. 21, No. 2 (Spring), pp. 141-171.
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Imai, Kosuke, Dustin Tingley, and Teppei Yamamoto
(2013).
``Experimental Designs for Identifying Causal Mechanisms.''
(with discussions) Journal of the Royal Statistical Society, Series A (Statistics in Society), Vol. 176, No. 1 (January), pp. 5-51. Read before the Royal Statistical Society in March, 2012.
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Imai, Kosuke, Luke Keele, and Dustin Tingley
(2010).
``A General Approach to Causal Mediation Analysis.''
Psychological Methods, Vol. 15, No. 4 (December), pp. 309-334.
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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.
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Imai, Kosuke, Luke Keele, and Teppei Yamamoto
(2010).
``Identification, Inference, and Sensitivity Analysis for Causal Mediation Effects.''
Statistical Science, Vol. 25, No. 1 (February), pp. 51-71.
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Chan, K.C.G, K. Imai, S.C.P. Yam, Z. Zhang
``Efficient Nonparametric Estimation of Causal Mediation Effects.''
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