論文

査読有り
2013年5月

Discriminant functions for sex estimation of modern Japanese skulls

JOURNAL OF FORENSIC AND LEGAL MEDICINE
  • Yoshinori Ogawa
  • ,
  • Kazuhiko Imaizumi
  • ,
  • Sachio Miyasaka
  • ,
  • Mineo Yoshino

20
4
開始ページ
234
終了ページ
238
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1016/j.jflm.2012.09.023
出版者・発行元
ELSEVIER SCI LTD

The purpose of this study is to generate a set of discriminant functions in order to estimate the sex of modern Japanese skulls. To conduct the analysis, the anthropological measurement data of 113 individuals (73 males and 40 females) were collected from recent forensic anthropological test records at the National Research Institute of Police Science, Japan. Birth years of the individuals ranged from 1926 to 1979, and age at death was over 19 years for all individuals. A total of 10 anthropological measurements were used in the discriminant function analysis: maximum cranial length, cranial base length, maximum cranial breadth, maximum frontal breadth, basion-bregmatic height, upper facial breadth, bizygomatic breadth, bicondylar breadth, bigonial breadth, and ramal height. As a result, nine discriminant functions were established. The classification accuracy ranged from 79.0 to 89.9% when the measurements of the 113 individuals were substituted into the established functions, from 77.8 to 88.1% when a leave-one-out cross-validation procedure was applied to the data, and from 86.7 to 93.0% when the measurements of 50 new individuals (25 males and 25 females), unrelated to the establishment of the discriminant functions, were used. (C) 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

リンク情報
DOI
https://doi.org/10.1016/j.jflm.2012.09.023
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/23622466
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000319054200010&DestApp=WOS_CPL
ID情報
  • DOI : 10.1016/j.jflm.2012.09.023
  • ISSN : 1752-928X
  • PubMed ID : 23622466
  • Web of Science ID : WOS:000319054200010

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