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Statistics and Causal Inference

Holland, Paul W.
Publication Year:
Report Number:
RR-85-40, PSRTR-85-63
ETS Research Report
Document Type:
Page Count:
Subject/Key Words:
Attribution Theory, Behavior Theories, Influences, Models, Philosophy, Statistical Analysis


Problems involving causal inference have dogged the heels of Statistics since its earliest days. Correlation does not imply causation and yet causal conclusions drawn from a carefully designed experiment are often valid. What can a statistical model say about causation? This question is addressed by using a particular model for causal inference (Rubin, 1974; Holland & Rubin, 1983) to critique the discussions of other writers on causation and causal inference. These include selected philosophers, medical researchers, statisticians, econometricians, and proponents of causal modelling. (76pp.)

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