Conceptual issues concerning mediation, interventions and composition

By Tyler J. VanderWeele, Stijn Vansteelandt. 2009

739 citations recorded by the source corpus.

Subfields: Sociology and Political Science, Statistics and Probability, Causal Inference & Discovery

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Citations in the corpus

Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Bias (2020, methodology): “The causality literature offers many avenues for continuing this line of work, including mediation analysis with non-linear models, and alternative effect decompositions (Imai et al., 2010a,b; VanderWeele and Vansteelandt, 2009).”
Causal mediation analysis in economics: Objectives, assumptions, models (2021, background): “This assumption is more plausible if the mediator occurs shortly after the treatment (VanderWeele and Vansteelandt, 2009).”
Mediation analysis allowing for exposure-mediator interactions and causal interpretation: theoretical assumptions and implementation with SAS and SPSS macros (2013, methodology): “VanderWeele and Vansteelandt (2009, 2010) showed how the notions of direct and indirect causal effects from causal inference in the counterfactual framework (Robins & Greenland, 1992; Pearl, 2001) can extend the Baron and Kenny formulae for direct and indirect effects to settings in which there is…”
Mediation Analysis with Multiple Mediators (2014, methodology): “E YaMa Ya Ma jc ¼ fθ1 þ θ3ðβ0 þ β1a þ β 02cÞgða a Þ E YaMa YaMa jc ¼ ðθ2β1 þ θ3β1aÞða a Þ: VanderWeele and Vansteelandt (2009) also derived standard errors for these effects using the delta method; alternatively bootstrapping can also be used.”
Interpretation and identification of causal mediation. (2014, neutral): “…regression equation) does not physically disable the paths going through M; it merely matches samples with equal M values and thus induces spurious correlations among other factors in the analysis (see Bullock, Green, & Ha, 2010; Cole & Hernán, 2002; Pearl, 1998; VanderWeele & Vansteelandt, 2009).”
On Partial Identification of the Pure Direct Effect (2015, background): “…al., 2005; Petersen et al., 2006; Ten Have et al., 2007; Albert, 2008; Goetgeluk et al., 2008; van der Laan and Petersen, 2008; VanderWeele, 2009; VanderWeele and Vansteelandt, 2009, 2010; Imai et al., 2010a,b; Albert and Nelson, 2011; Tchetgen Tchetgen, 2011; VanderWeele, 2011; Albert, 2012;…”
Quantifying an Adherence Path-Specific Effect of Antiretroviral Therapy in the Nigeria PEPFAR Program (2014, methodology): “onfounding, and hence our analysis will require a more general approach of mediation analysis based on counterfactuals (Robins and Greenland, 1992; Robins, 1999, 2003; Pearl, 2001; Avin et al., 2005; VanderWeele and Vansteelandt, 2009, 2010; Imai et al., 2010a,b; Tchetgen Tchetgen and Shpitser, 2012”
Investigating Gender Bias in Language Models Using Causal Mediation Analysis (2020, methodology): “The causality literature offers many avenues for continuing this line of work, including mediation analysis with non-linear models, and alternative effect decompositions (Imai et al., 2010a,b; VanderWeele and Vansteelandt, 2009).”
The Causal Mediation Formula—A Guide to the Assessment of Pathways and Mechanisms (2012, result): “analysis (by including Z in the regression equation) does not physically disable the paths going through Z ; it merely matches samples with equal Z values, and thus induces spurious correlations among other factors in the analysis (see Cole and Hernán 2002; Pearl 1998; VanderWeele and Vansteelandt 2”
Imputation Strategies for the Estimation of Natural Direct and Indirect Effects (2012, background): “Formal descriptions of these assumptions in terms of counterfactuals are for instance given in VanderWeele and Vansteelandt (2009).”
Ratio of Mediator Probability Weighting for Estimating Natural Direct and Indirect Effects (2025, background): “Using the potential outcomes framework, researchers (Holland 1988; Imai et al, 2010; Pearl, 2001; Robins and Greenland, 1992; Sobel, 2008; VanderWeele & Vansteelandt, 2009) have clarified the identification assumptions under which the above path coefficients have causal meanings.”
Causal Mediation Analysis (2011, methodology): “We can combine the estimates from the two regression models to get the following formulas for direct and indirect effects, comparing exposure levels a and a* (VanderWeele and Vansteelandt, 2009):”
Exploring U.S. Shifts in Anti-Asian Sentiment with the Emergence of COVID-19 (2020, methodology): “We obtained training data from manually labeled Sentiment140 (n = 498) [27], Kaggle (n = 7086) [28], Sanders (n = 5113) [29], and 6,481 tweets labeled by our research group.”