Alternative Graphical Causal Models and the Identification of Direct E!ects

By James M. Robins, Thomas S. Richardson. 2010

281 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0c9b91da73d83a77959090251daee7c531140225

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In Statistics and Probability

Citations in the corpus

IDENTIFYING CAUSAL MECHANISMS (PRIMARILY) BASED ON INVERSE PROBABILITY WEIGHTING (2014, background): “…and M(d) for possibly distinct d00, d0, d (i.e. also for potential outcomes and potential mediator states defined on opposite treatments).9 This 9 Robins and Richardson (2010) present a DGP in their Appendix B, where indeed FRCISTG holds, while our stronger restriction is not satisfied.”
The Mediation Formula: A Guide to the Assessment of Causal Pathways in Nonlinear Models (2011, background): “More refined counterfactual conditions for identification are derived in Petersen et al. (2006), Imai et al. (2010c), and Robins and Richardson (2011).”
Identification and Sensitivity Analysis for Multiple Causal Mechanisms: Revisiting Evidence from Framing Experiments (2013, background): “Some scholars (e.g., Robins and Richardson 2010) consider this distinction to be important because one can conceive of a randomized experiment on a separate exchangeable population with which Assumption 2 can be tested, while such an experiment does not exist for Assumption 1 (Section 7) even as a…”
Quantifying an Adherence Path-Specific Effect of Antiretroviral Therapy in the Nigeria PEPFAR Program (2014, unknown): “As such, while often practically meaningful, thePEMY path-specific effect must be interpreted with care and not blindly substituted for the NIE.”
Semiparametric Theory for Causal Mediation Analysis: efficiency bounds, multiple robustness, and sensitivity analysis (2012, background): “…the literature [Robins and Greenland (1992), Pearl (2001), van der Laan and Petersen (2005), Hafeman and Vanderweele (2011)]; however, we note that Robins and Richardson (2012) disagree with the label “sequential ignorability” because its terminology has previously carried a different…”
On Partial Identification of the Pure Direct Effect (2015, methodology): “However, such an independence is neither experimentally verifiable nor enforceable (Robins and Richardson, 2010).”
Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies (2011, methodology): “In such cases the proposed sensitivity analysis will not be helpful, and instead the researcher should consider alternative research designs (see Alternative Research Design for Credible Inference), or other identification strategies (e.g., Robins and Richardson 2010).”
Mediation analysis allowing for exposure-mediator interactions and causal interpretation: theoretical assumptions and implementation with SAS and SPSS macros (2013, background): “Technical examples can be constructed where one set of identification assumptions holds and another does not (see also Robins & Richardson, 2010), but on a causal diagram corresponding to a set of nonparametric structural equations, whenever one set of the assumptions among those in This document…”
CAUSAL INFERENCE WITH A GRAPHICAL HIERARCHY OF INTERVENTIONS (2014, background): “In this paper, we leave the issues of applicability of edge interventions and mediation analysis in particular settings aside [19], and consider, in subsequent sections, questions of identification and the form of resulting functionals.”
For and Against Methodologies: Some Perspectives on Recent Causal and Statistical Inference Debates (2017, background): “These assumptions are usually covered under the causal Markov assumption, and require no formal definition of ‘‘cause’’ or ‘‘effect’’ (Spirtes et al. 2001; Robins and Richardson 2011).”
The Causal Mediation Formula—A Guide to the Assessment of Pathways and Mechanisms (2012, background): “For discussions regarding policy implications of NDE versus CDE, see (Albert and Nelson 2011; Hafeman and Schwartz 2009; Joffe et al. 2007; Kaufman 2010; Pearl 2001, 2009, p. 132; Robins 2003; Robins and Richardson 2011).”
Single World Intervention Graphs ( SWIGs ) : A Unification of the Counterfactual and Graphical Approaches to Causality (2013, methodology): “We impose on these error terms the independence assumptions of the FFRCISTG model of Robins (1986); Robins and Richardson (2011).”
Limitations of individual causal models, causal graphs, and ignorability assumptions, as illustrated by random confounding and design unfaithfulness (2015, background): “ordinary causal graphs, see Richardson and Robins [21, 22].”