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三种“因果概率”的方差估计量。

Variance estimators for three "probabilities of causation".

作者信息

Cai Zhihong, Kuroki Manabu

机构信息

Kyoto University, Biostatistics, Kyoto, Japan.

出版信息

Risk Anal. 2005 Dec;25(6):1611-20. doi: 10.1111/j.1539-6924.2005.00696.x.

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.

摘要

本文介绍了Pearl(1999)提出的三种“因果概率”的定义,这些定义用于评估流行病学研究中暴露因素对疾病的因果效应。Pearl(1999)以及Tian和Pearl(2000a,2000b)在某些假设下从统计数据中给出了三种“因果概率”的识别公式。为了研究估计准确性问题,本文推导了与Pearl(1999)中每种情况相对应的三种“因果概率”的方差估计量,同时阐明了它们的性质。此外,我们进行了模拟实验,结果表明所提出的方法能够充分逼近“因果概率”的方差。本文的结果提供了一个完整的框架,以便在流行病学研究中有效地使用“因果概率”来分析责任和易感性。

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