A Novel Method for Osteometric Reassociation Using Hamiltonian Markov Chain Monte Carlo (MCMC) Simulation

Abstract

Traditional osteometric reassociation uses an error-mitigation approach, which seeks to eliminate possible matches, rather than a predictive approach, where possible matches are directly compared. This study examines the utility of a Bayesian approach for resolving commingling by using a probabilistic framework to predict correct matches. Comparisons were grouped into three types: paired elements, articulating elements, and other elements. Ten individuals were randomly removed from the total sample (N = 833), acting as a small-scale, closed-population commingled assemblage. One element was chosen as the independent variable, with the ten possible matching elements representing the dependent variable. A Bayesian regression model was constructed using the remaining total sample, resulting in a distribution of possible values that were smoothed into a probability density, and probabilities were calculated. The element with the highest posterior probability was considered the best match. This process was repeated 500 times for each comparison. The correct match was identified 51.60% of the time. Paired elements performed the best, at 80.76%, followed by 42.10% for articulating and 33.63% for other comparisons. These results suggest that metric analysis of commingled assemblages is complex and that both elimination-based and predictionbased approaches have a role in resolving commingling. In this regard, the strength of a Bayesian approach is versatility, allowing for prediction of the correct match and elimination of possible matches, as well as integration of independent lines of evidence within one cohesive model.

A novel method for sorting and reassociating commingled human remains using deviation analysis

“…Despite the illustrated benefits of sorting mixed joint articulations, the greater part of the published literature concerns pair‐matching or elemental associations [1, 9, 18–22, 25, 27, 46–59]. Of the few studies examining the utility of sorting commingled joints, the majority focus on joint congruence at the atlanto‐occipital joint [17, 26, 29, 56, 57] or at the large joints of the body, such as the hip or knee [12, 18–20, 23, 29, 30, 60, 61].…”

“…Sorting the larger joints of the body has also received mixed results. For instance, McCormick [23] noted the correct match was identified only 42.10% of the time when using Byrd's [12] osteometric sorting models for the femorotibial, humeroulnar, and humeroradial joints. Conversely, Anastopoulou et al [30] were able to correctly identify an individual's acetabulum and articulating femora in 81.4% of cases.…”

“…The majority of methods that use joint articulation to sort commingled remains involve either linear measurements or manual techniques, such as physically fitting the bones together to determine goodness of fit [1,12,[16][17][18][19][20][21][22][23]. However, these methods can be subjective and open to observer error, dependent on years of experience with anatomy and osteology, or reliant on linear measurements, which may be limited in their ability to describe the joint surfaces being compared.…”