The Mediation Formula: A Guide to the Assessment of Causal Pathways in Nonlinear Models

By Judea Pearl. 2011

162 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/f0d9f39a4807aea3a8a0ca01608365ed41057fbb

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

Citations in the corpus

Semiparametric Theory for Causal Mediation Analysis: efficiency bounds, multiple robustness, and sensitivity analysis (2012, background): “In recent work, mainly motivated by Pearl’s mediation functional, several authors [Imai, Keele and Tingley (2010), Imai, Keele and Yamamoto (2010), Pearl (2011), VanderWeele (2009), Vanderweele and Vansteelandt (2010)] have demonstrated how the simple linear structural equation approach generalizes…”
3. The Foundations of Causal Inference (2010, methodology): “In addition to providing causally sound estimates for mediation effects, the Mediation Formula also enables researchers to evaluate analytically the effectiveness of various parametric specifications relative to any assumed model (Imai et al. 2008; Pearl 2010a).”
The International Journal of Biostatistics Principal Stratification — a Goal or a Tool ? (2011, unknown): “In some other cases, the direct effect of the treatment will be deemed to be nil if a small subpopulation exists for which treatment has no effect on both the outcome and the mediator (Pearl, 2011).”
The Causal Foundations of Structural Equation Modeling (2012, background): “3Causal relationships among latent variables are assessed by treating their indicators as noisy measurement of the formers (Bollen, 1989; Pearl, 2010c; Cai and Kuroki, 2008).”
Fairness in Decision-Making - The Causal Explanation Formula (2018, methodology): “The Explanation Formula in the standard model is closely related to the “Mediation Formula” used for mediation analysis, which was introduced in (Pearl 2001) and is widely popular throughout the empirical sciences (see (Pearl 2012) for a survey).”
On Pearl’s Hierarchy and the Foundations of Causal Inference (2022, methodology): “It has been made systematic and shown to be complete for the task of identification from a combination of observations and experiments [Tian and Pearl 2002a, Huang and Valtorta 2006, Shpitser and Pearl 2006, Bareinboim and Pearl 2012, Lee et al. 2019].”
Imputation Strategies for the Estimation of Natural Direct and Indirect Effects (2012, methodology): “As in Robins and Greenland (1992) and Pearl (2001) we will describe direct and indirect effects in terms of so-called nested counterfactuals, Y (a,M(a∗)), denoting the outcome that would have been observed if A were set to a and M to the value it would have taken if A were set to a∗.”
Estimation of a Semiparametric Natural Direct Effect Model Incorporating Baseline Covariates (2014, unknown): “When the effect of confounders must be modeled, inferences based on parametric structural equations (Pearl, 2011; Imai et al., 2010b; VanderWeele, 2009; VanderWeele & Vansteelandt, 2010) correspond for a particular specification of model for the outcome and the mediator densities, similar to the plu”
Interpretation and identification of causal mediation. (2014, background): “(21)–(23) would yield the following seminatural effects: SNDE = β2 + α(β4 + γ2β1) SNIE = γ1β1 TE = β2 + (γ1 + αγ2)(β3 + β1) + αβ4 TE − SNDE = γ1(β1 + β3) + β3αγ2 Figure 14 depicts the path that supports the SNDE and SNIE compared with those supporting the NDE and NIE in Eqs.”
A simple unified approach for estimating natural direct and indirect effects. (2012, methodology): “The traditional approach to estimating natural direct and indirect effects uses the mediation formula (17) to calculate E1⁄2Ya ;Ma jC 1⁄4 c as X”
A General Algorithm for Deciding Transportability of Experimental Results (2013, background): “■ Theorem 2 provides a tractable transportability condition for the CDE – a key concept in modern mediation analysis, which permits the decomposition of effects into their direct and indirect components [35, 36].”