Variance Estimators for Three "Probabilities of Causation" |
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Authors: | Zhihong Cai Manabu Kuroki |
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Institution: | Kyoto University, Biostatistics, Kyoto, Japan. cai@pbh.med.kyoto-u.ac.jp |
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Abstract: | This article introduces the definitions of three "probabilities of causation" suggested by Pearl (1999), which are used to evaluate the causal effect of an exposure on a disease in epidemiological studies. Pearl (1999) and Tian and Pearl (2000a, 2000b) provided identification formulas for three "probabilities of causation" from statistical data under some assumptions. In order to examine the estimation accuracy problem, this article derives variance estimators for three "probabilities of causation" correspondent to each case in Pearl (1999) and at the same time clarify their properties. In addition, we conduct simulation experiments and show that the proposed method can approximate sufficiently to the variance of "probabilities of causation." The results of this article provide a complete framework for using "probabilities of causation" effectively in order to analyze responsibility and susceptibility in epidemiological studies. |
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Keywords: | Confounder adjustment counterfactual no confounding no prevention |
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