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.

This study introduces an automated method for osteological pair-matching using two-dimensional outline form data extracted from photographs. A procedure for acquiring photographs that improve the differentiation of specimens from the background is presented along with an extraction procedure that allows the capture of form data from photographs. The raw form data are used in a two-dimensional registration procedure, which combines iterative closest point, K-nearest neighbor search, and iterations around an estimated mean. Form data are used in optimized distance calculations that minimize true-pair difference and maximize false-pair difference. The sample consists of 122 calcanei and 110 tali from the UI-Stanford collection. Performance statistics are provided for the maximum and average Segmented-Hausdorff, Hausdorff, and Procrustes distances to show the comparative statistical results for matching. Results indicate 98.36% and 98.2% accuracy in pinpointing true-pairs for the calcanei and tali, respectively, using a shortlist of one-lowest-distance.

This study compares the original osteometric sorting association method with an ordination approach across all combinations of the humerus, ulna, radius, femur, tibia, and fibula. This includes both the original prediction interval and t-statistic approaches. Standard measurements are utilized in the models with full measurements combined and without length measurements. The sample is the osteometric sorting reference from the Defense POW/MIA Accounting Agency. A full set of performance statistics is provided. Results indicate the ordination approach outperforms the original in the majority of bone combinations. Models with length measurements have more exclusion power than those without. It is recommended for the ordination approach to supersede the original when applied to large commingled assemblages.