Univariate and Linear Composite Asymmetry Statistics for the “Pair-Matching” of Bone Antimeres
Univariate and Linear Composite Asymmetry Statistics for the “Pair-Matching” of Bone Antimeres
复制标题
骨反体“配对匹配”的单变量和线性复合不对称统计
DOI：
10.1111/1556-4029.13748
复制
发表时间：
2018
影响因子：
1.6
通讯作者：
Konigsberg, Lyle W.
中科院分区：
文献类型：
--
作者：
Lee, Amanda B.;Konigsberg, Lyle W.
本文考察了长骨不对称性的单变量和线性复合测量的分布特性。这篇论文的目的是检验最符合不对称性分布的模型，并对改进法医配对技术有所启示。我们使用软件R将参考数据(N=2343)和测试数据(N=71)建模为正态分布、指数幂分布和偏指数幂分布--后两种分布包括正态分布作为特例。我们的结果表明，由于数据是非正态的，所以数据最适合后两种分布。我们还展示了如何将使用边差绝对值的不对称统计数据拟合为折叠分布。这消除了对经验分布或试图将非正态分布转换为正态分布的变换的需要。这项研究的结果为改进使用比较参考数据的配对方法奠定了框架。
This paper examines the distributional properties of univariate and linear composite measures of long bone asymmetry. The goal of this paper is to examine models that best fit the distribution of asymmetries with implications for the improvement of forensic pair‐matching techniques. We use the software R to model reference data (N= 2343) and test data (N= 71) as normal distributions, an exponential power distribution, and a skew exponential power distribution—the latter two include the normal as a special case. Our results indicate that the data best fit the latter two distributions because the data are nonnormal. We also show how asymmetry statistics that use absolute values of side differences can be fit as folded distributions. This obviates the need for empirical distributions or for transformations that attempt to convert nonnormal distributions to normal distributions. The results of this study lay the framework for improving pair‐matching methods that use comparative reference data.