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一个数学证明及示例,表明贝叶斯定理是性再犯风险精算估计的基础。

A mathematical proof and example that Bayes's Theorem is fundamental to actuarial estimates of sexual recidivism risk.

作者信息

Donaldson Theodore, Wollert Richard

出版信息

Sex Abuse. 2008 Jun;20(2):206-17. doi: 10.1177/1079063208317734.

Abstract

Expert witnesses in sexually violent predator (SVP) cases often rely on actuarial instruments to make risk determinations. Many questions surround their use, however. Bayes's Theorem holds much promise for addressing these questions. Some experts nonetheless claim that Bayesian analyses are inadmissible in SVP cases because they are not accepted by the relevant scientific community. This position is illogical because Bayes's Theorem is simply a probabilistic restatement of the way that frequency data are combined to arrive at whatever recidivism rates are paired with each test score in an actuarial table. This article presents a mathematical proof and example validating this assertion. The advantages and implications of a logic model that combines Bayes's Theorem and the null hypothesis are also discussed.

摘要

性暴力捕食者(SVP)案件中的专家证人常常依靠精算工具来进行风险判定。然而,围绕这些工具的使用存在许多问题。贝叶斯定理在解决这些问题方面颇具前景。尽管如此,一些专家声称贝叶斯分析在SVP案件中不被采纳,因为它们未被相关科学界所接受。这一立场不合逻辑,因为贝叶斯定理仅仅是对频率数据组合方式的概率性重述,目的是得出与精算表中每个测试分数相对应的再犯率。本文给出了一个数学证明及示例来验证这一论断。同时还讨论了结合贝叶斯定理和零假设的逻辑模型的优势及影响。

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