Subject: CAUSAL MECHANISMS | NATURAL DIRECT | Mathematics and Statistics | EFFECT DECOMPOSITION | Article | R1
The mediation formula for the identification of natural (in)direct effects has facilitated mediation analyses that better respect the nature of the data, with greater consideration of the need for confounding control. The default assumptions on which it relies are stron... View more
VanderWeele TJ, Vansteelandt S, Robins JM. E↵ect decomposition in the presence of an exposure-induced mediator-outcome confounder. Epidemiology. 2014;25:300-6.
Robins JM, Greenland S. Identifiability and exchangeability for direct and indirect e↵ects. Epidemiology. 1992;3:143-55.
Pearl J. Direct and indirect e↵ects. In: Proceedings of the Seventeenth Conference on Uncertainty and Artificial Intelligence. San Francisco: Morgan Kaufmann; 2001. p. 411-420.
VanderWeele TJ, Vansteelandt S. Conceptual issues concerning mediation, interventions and composition. Statistics and its Interface. 2009;2:457-468.
Vanderweele TJ, Vansteelandt S. Odds ratios for mediation analysis for a dichotomous outcome. Am J Epidemiol. 2010;172:1339-48.
Imai K, Keele L, Tingley D. A general approach to causal mediation analysis. Psychol Methods. 2010;15:309-34.
Robins JM, Richardson TS. Alternative graphical causal models and the identification of direct e↵ects. In: Shrout PE, Keyes KM, Ornstein K, editors. Causality and psychopathology. Oxford: Oxford University Press; 2011. .
Naimi AI, Kaufman JS, MacLehose RF. Mediation misgivings: ambiguous clinical and public health interpretations of natural direct and indirect e↵ects. Int J Epidemiol. 2014;43:1656-61.
Didelez V, Dawid AP, Geneletti S. Direct and indirect e↵ects of sequential treatments. In: Proceedings of the 22nd Annual Conference on Uncertainty in Artificial Intelligence; 2006. p. 138-146.
Imai K, Tingley D, Yamamoto T. Experimental designs for identifying causal mechanisms. Journal of the Royal Statistical Society: Series A (Statistics in Society). 2013;176:5- 51.