Causal Inference Without Counterfactuals: Comment

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Alternative Graphical Causal Models and the Identification of Direct E!ects (2010, background): “…Vm would have if, possibly contrary to fact, R were set to r, r ∈ R = R1 ⊗ · · · ⊗ RK , where Vm(r) is assumed to be well defined in the sense that there is reasonable agreement as to the hypothetical intervention (i.e., closest possible world) which sets R to r (Robins and Greenland, 2000).”
Identifiability and Estimation of Causal Effects by Principal Stratification With Outcomes Truncated by Death (2011, background): “For example, Robins (1995) and Robins and Greenland (2000) proposed a counterfactual analysis of death as a competing risk.”
For and Against Methodologies: Some Perspectives on Recent Causal and Statistical Inference Debates (2017, background): “…all practical uses of language and logic, including usage of ‘‘cause’’ and ‘‘effect,’’ and that potential-outcomes modeling helps pinpoint and reduce vagueness in studies of causation (Robins and Greenland 2000; Robins and Weissman 2016; Hernán 2016; VanderWeele 2016a; VanderWeele et al. 2016).”