The Power of Exclusion using Automated Osteometric Sorting: Pair‐Matching,. Issue 2 (26th May 2017)

• Record Type: Journal Article
• Authors: Lynch, Jeffrey James; Byrd, John; LeGarde, Carrie B.
• Is Part Of: Journal of forensic sciences. Volume 63:Issue 2(2018)
• Page Start: 371
• Page End: 380
• Publication Date: 2017-05-26
• Subjects: forensic science -- osteometric sorting -- pair‐matching -- commingling -- t‐test -- normality -- fluctuating asymmetry; Medical jurisprudence -- Periodicals; Forensic sciences -- Periodicals; Forensic Medicine -- Periodicals; Gerechtelijke geneeskunde; Gerechtelijke chemie; Gerechtelijke psychiatrie; 363.2505
• DOI: 10.1111/1556-4029.13560
• Languages: English
• ISSNs: 0022-1198

Abstract

Abstract: This study compares the original pair‐matching osteometric sorting model ( J Forensic Sci 2003 ;48:717) against two new models providing validation and performance testing across three samples. The samples include the Forensic Data Bank, USS Oklahoma, and the osteometric sorting reference used within the Defense POW/MIA Accounting Agency. A computer science solution to generating dynamic statistical models across a commingled assemblage is presented. The issue of normality is investigated showing the relative robustness against non‐normality and a data transformation to control for normality. A case study is provided showing the relative exclusion power of all three models from an active commingled case within the Defense POW/MIA Accounting Agency. In total, 14, 357, 220 osteometric t ‐tests were conducted. The results indicate that osteometric sorting performs as expected despite reference samples deviating from normality. The two new models outperform the original, and one of those is recommended to supersede the original for future osteometric sorting work.