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使用多元概率回归模型对菲律宾颅骨进行形态学祖先估计。

Morphoscopic ancestry estimates in Filipino crania using multivariate probit regression models.

机构信息

Department of Anthropology, University of Illinois at Urbana-Champaign, 109 Davenport Hall, 607 South Mathews Avenue, Urbana, Illinois.

SNA International, supporting the Department of Defense POW/MIA Accounting Agency, 590 Moffet Street, Building 4077, Joint Base Pearl Harbor-Hickam, Hawaii.

出版信息

Am J Phys Anthropol. 2020 Jul;172(3):386-401. doi: 10.1002/ajpa.24008. Epub 2020 Jan 14.

Abstract

OBJECTIVES

Probit has not been applied to ancestry estimation in forensic anthropology. The goals of this study were to: (1) evaluate the performance of probit analysis as a classification tool for ancestry estimation using ordinal data and (2) expand our current understanding of human cranial variation for an understudied population.

METHODS

Multivariate probit models were used to classify the ancestral affiliation of Filipino crania using morphoscopic traits. Ancestral reference populations represented Africa, Asia, and Europe in a three-group model, with the addition of Hispanics in a four-group model. Posterior probabilities across these groups were interpreted as admixture proportions of an individual. Model performance was also evaluated for individuals with missing data.

RESULTS

The overall correct classification rates for the three-group and four-group models were 72.1% and 68.6%, respectively. Filipinos classified as Asian 52.9% of the time using three ancestral reference groups and 48.6% using four groups. A large portion of Filipinos also classified as African. There were no significant differences in classification trends or accuracy rates between complete crania and crania with at least one missing variable.

CONCLUSIONS

Multivariate probit models using morphoscopic traits perform well when populations are represented in both training and test samples. Probit can also accommodate individuals with missing data. Classifying Filipinos showed only moderate success. Filipinos are more phenotypically similar to Africans than the other Asian samples used here, but still affiliate most closely as Asian. Ancestry methods would benefit from including Filipinos as a reference sample given the additional variation they provide to the continental category of Asian.

摘要

目的

Probit 尚未应用于法医人类学中的祖先估计。本研究的目的是:(1)评估概率分析作为使用有序数据进行祖先估计的分类工具的性能;(2)扩展我们对一个研究不足的人群的人类颅骨变异的现有认识。

方法

使用多元概率模型,使用形态学特征对菲律宾颅骨的祖先归属进行分类。祖先参考群体代表非洲、亚洲和欧洲的三组模型,在四组模型中增加了西班牙裔。这些群体的后验概率被解释为个体的混合比例。还评估了具有缺失数据的个体的模型性能。

结果

三组和四组模型的总体正确分类率分别为 72.1%和 68.6%。使用三个祖先参考群体,菲律宾人被归类为亚洲人的比例为 52.9%,使用四个群体的比例为 48.6%。很大一部分菲律宾人也被归类为非洲人。在完整颅骨和至少一个缺失变量的颅骨之间,分类趋势或准确率没有显着差异。

结论

在训练和测试样本中都有代表性的人群中,使用形态学特征的多元概率模型表现良好。Probit 还可以适应具有缺失数据的个体。对菲律宾人的分类仅取得了中等成功。菲律宾人在表型上与非洲人比这里使用的其他亚洲样本更相似,但仍然与亚洲人最密切相关。鉴于亚洲大陆类别提供的额外变异,将菲律宾人作为参考样本,祖先方法将受益。

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