STATISTICS AND CAUSAL INFERENCE

Problems involving causal inference have dogged at 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 and 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.

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