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Inclusion probability for DNA mixtures is a subjective one-sided match statistic unrelated to identification information

机译:DNA混合物的包含概率是与识别信息无关的主观单方面匹配统计

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Background:DNA mixtures of two or more people are a common type of forensic crime scene evidence. A match statistic that connects the evidence to a criminal defendant is usually needed for court. Jurors rely on this strength of match to help decide guilt or innocence. However, the reliability of unsophisticated match statistics for DNA mixtures has been questioned.Materials and Methods:The most prevalent match statistic for DNA mixtures is the combined probability of inclusion (CPI), used by crime labs for over 15 years. When testing 13 short tandem repeat (STR) genetic loci, the CPI-1 value is typically around a million, regardless of DNA mixture composition. However, actual identification information, as measured by a likelihood ratio (LR), spans a much broader range. This study examined probability of inclusion (PI) mixture statistics for 517 locus experiments drawn from 16 reported cases and compared them with LR locus information calculated independently on the same data. The log(PI-1) values were examined and compared with corresponding log(LR) values.Results:The LR and CPI methods were compared in case examples of false inclusion, false exclusion, a homicide, and criminal justice outcomes. Statistical analysis of crime laboratory STR data shows that inclusion match statistics exhibit a truncated normal distribution having zero center, with little correlation to actual identification information. By the law of large numbers (LLN), CPI-1 increases with the number of tested genetic loci, regardless of DNA mixture composition or match information. These statistical findings explain why CPI is relatively constant, with implications for DNA policy, criminal justice, cost of crime, and crime prevention.Conclusions:Forensic crime laboratories have generated CPI statistics on hundreds of thousands of DNA mixture evidence items. However, this commonly used match statistic behaves like a random generator of inclusionary values, following the LLN rather than measuring identification information. A quantitative CPI number adds little meaningful information beyond the analyst's initial qualitative assessment that a person's DNA is included in a mixture. Statistical methods for reporting on DNA mixture evidence should be scientifically validated before they are relied upon by criminal justice.
机译:背景:两个或多个人的DNA混合物是法医犯罪现场证据的常见类型。法庭通常需要将证据与刑事被告联系起来的比赛统计数据。陪审员依靠这种比赛的力量来帮助决定内或无罪。但是,人们一直对DNA混合物的简单匹配统计数据的可靠性提出质疑。材料和方法:DNA混合物最普遍的匹配统计数据是犯罪实验室使用超过15年的合并包含概率(CPI)。测试13个短串联重复序列(STR)遗传基因座时,无论DNA混合物的成分如何,CPI-1值通常约为一百万。但是,通过似然比(LR)衡量的实际识别信息的范围要大得多。这项研究检查了从16个报告病例中提取的517个基因座实验的纳入概率(PI)混合物统计,并将它们与在相同数据上独立计算的LR基因座信息进行了比较。结果:检查了在错误包括,错误排除,凶杀和刑事司法结果的案例中,比较了LR和CPI方法的log(PI-1)值并与相应的log(LR)值进行了比较。犯罪实验室STR数据的统计分析表明,包含物匹配统计数据显示出具有零中心的截断正态分布,与实际标识信息几乎没有相关性。根据大数定律(LLN),CPI-1随着测试的遗传基因座数量的增加而增加,而不管DNA混合物的组成或匹配信息如何。这些统计结果解释了为什么CPI相对恒定,会对DNA政策,刑事司法,犯罪成本和预防犯罪产生影响。结论:法医犯罪实验室已经对数十万个DNA混合物证据项目生成了CPI统计数据。但是,这种常用的匹配统计数据的行为就像是包含值的随机生成器,它遵循LLN而不是测量标识信息。定量的CPI数除了分析师最初对混合物中包含人的DNA进行定性评估外,几乎没有提供有意义的信息。报告DNA混合物证据的统计方法应经过科学验证,然后再由刑事司法部门采用。

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