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Causal inference; confounding; counterfactual; direct causal effect; double robust estimation; G-computation estimation; indirect causal effect; inverse probability of treatment/censoring weighted estimation; longitudinal data
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Direct Effect Models, Mark J. Van Der Laan, Maya L. Petersen
Direct Effect Models, Mark J. Van Der Laan, Maya L. Petersen
U.C. Berkeley Division of Biostatistics Working Paper Series
The causal effect of a treatment on an outcome is generally mediated by several intermediate variables. Estimation of the component of the causal effect of a treatment that is mediated by a given intermediate variable (the indirect effect of the treatment), and the component that is not mediated by that intermediate variable (the direct effect of the treatment) is often relevant to mechanistic understanding and to the design of clinical and public health interventions. Under the assumption of no-unmeasured confounders for treatment and the intermediate variable, Robins & Greenland (1992) define an individual direct effect as the counterfactual effect of …