Statistics & Data Science · Causal Inference
A topic within Causal Inference, itself one of 10 topics in that field and part of Statistics & Data Science.
Assumes you know the vocabulary.
Statistics and Causal Inference
Paul W. Holland · 1986
Argues causal questions should be posed as comparisons of potential outcomes under different manipulations of the same unit, and that 'attribute…
Primary sources and full treatments.
Estimating Causal Effects of Treatments in Randomized and Nonrandomized Studies
Donald B. Rubin · 1974
Defines a causal effect as the difference between the outcome a unit would show under treatment and the outcome it would show under control, and…
+1 more at this level
3 works
Paul W. Holland
Argues causal questions should be posed as comparisons of potential outcomes under different manipulations of the same unit, and that 'attribute causes' like race or sex fail this test in ways that make many causal claims about them incoherent.
link checked 17 Sept 2026Donald B. Rubin
Defines a causal effect as the difference between the outcome a unit would show under treatment and the outcome it would show under control, and shows randomisation's real job is making that unobservable comparison estimable.
link checked 17 Sept 2026Guido W. Imbens
Compares the potential-outcomes and DAG traditions on the same worked examples and argues most of the disagreement between them is notational rather than substantive, though each makes some assumptions easier to state than the other.
link checked 17 Sept 2026