Comment on "Causal inference without counterfactuals," by Dawid AP

By Donald B. Rubin. 2000

152 citations recorded by the source corpus.

Subfields: History and Philosophy of Science

View Paper: https://www.semanticscholar.org/paper/a0182c495f8e2387e4a0b7f803df5257a20e03c5

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In History and Philosophy of Science

Citations in the corpus

The consistency statement in causal inference: a definition or an assumption? (2009, background): “A third example with alcohol as the exposure is given by Robins and Greenland.(21) Many examples of departures from consistency can be viewed from the perspectives of study design or exposure measurement error.”
Causal Inference Under Multiple Versions of Treatment (2013, unknown): “For each individual j, we assume there is a fixed version that would have been received had the individual been given treatment a ; as with the case of stochastic counterfactuals [30], analogous results to those that follow would hold if these “counterfactual versions of treatment” were assumed stoc”
Comparative quantification of health risks: Conceptual framework and methodological issues (2003, background): “Although the statistical issues around establishing causality and estimating the effect size are similar (lack of causality is equivalent to zero excess risk) (Robins 1999a; Robins and Greenland 2000), in practice, with knowledge from multiple disciplines in establishing causality, it is often the l”
Conceptual issues concerning mediation, interventions and composition (2009, background): “Without clear interventions to change these variables, counterfactual contrasts are not necessarily welldefined or are ill-defined to the extent to which the intervention is not specified (Lewis, 1973; Robins and Greenland, 2000).”
Social Experiments and Instrumental Variables with Duration Outcomes (2005, background): “It basically equals the survivor average causal effect of Rubin (2000) in case the latter would be applied to the duration outcome itself rather than to effects on non-duration outcomes.”
Likelihood-Based Analysis of Causal Effects of Job-Training Programs Using Principal Stratification (2009, background): “A related approach is used in Lee (2005) to derive bounds on the average treatment effect on wages for the specific principal stratum of the always employed, also called the ‘‘survivor average causal effect’’ (SACE) in Rubin (1998, 2000), where the term ‘‘survivor’’ arises from the medical version o”
Alternative Graphical Causal Models and the Identification of Direct E!ects (2010, background): “causal contrasts are best thought of in terms of explicit interventions that, at least in principle, could be performed (Robins and Greenland, 2000)) he or she would then reject the PDE as a meaningful causal contrast in this context.”
Estimation of the causal effects of time-varying exposures (2008, background): “Even consistency cannot always be taken for granted in observational studies because the counterfactual outcomes themselves are sometimes not well defined, which renders causal inferences ambiguous (Robins and Greenland, 2000; Hernán, 2005).”
Principal Stratification in Causal Inference (2002, background): “The outline described in Rubin (2000) to address this problem is another special case of principal stratification.”
Estimation of Causal Effects via Principal Stratification When Some Outcomes are Truncated by “Death” (2003, methodology): “) ∑ ∑ , Zhang and Rubin As was suggested in Rubin (1998, 2000), the most meaningful inferences about the causal effects on Y can be drawn only for the GG group, because both Yi(T) and Yi(C) are defined on R only for this group.”