Statistics and Causal Inference

Statistics and Causal Inference,10.1080/01621459.1986.10478354,Journal of The American Statistical Association,Paul W. Holland

Statistics and Causal Inference   (Citations: 938)
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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 (Holland and Rubin 1983; Rubin 1974) to critique the discussions of other writers on causation and causal inference. These include selected philosophers, medical researchers, statisticians, econometricians, and proponents of causal modeling.
Journal: Journal of The American Statistical Association - J AMER STATIST ASSN , vol. 81, no. 396, pp. 945-960, 1986
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