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Performance of three mathematical models for estimating age-at-death from multiple indicators of the adult skeleton

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Abstract

The mathematical method which will achieve the most accurate and precise age-at-death estimate from the adult skeleton is often debated. Some research promotes Bayesian analysis, which is widely considered better suited to the data construct of adult age-at-death distributions. Other research indicates that methods with less mathematical complexity produce equally accurate and precise age-at-death estimates. One of the advantages of Bayesian analysis is the ability to systematically combine multiple indicators, which is reported to improve the age-at-death estimate. Few comparisons exist between Bayesian analysis and less complex mathematical models when considering multiple skeletal indicators. This study aims to evaluate the performance of a Bayesian approach compared to a phase-based averaging method and linear regression analysis using multiple skeletal indicators. The three combination methods were constructed from age-at-death data collected from 330 adult skeletons contained in the Raymond A Dart and Pretoria Bone Collections in South Africa. These methods were tested and compared using a hold-out sample of 30 skeletons. As is frequently reported in literature, a balance between accuracy and precision was difficult to obtain from the three selected methods. However, the averaging and regression analysis methods outperformed the Bayesian approach in both accuracy and precision. Nevertheless, each method may be suited to its own unique situation—averaging to inform first impressions, multiple linear regression to achieve statistically defensible accuracies and precisions and Bayesian analysis to allow for cases where category adjustments or missing indicators are necessary.

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Acknowledgements

The authors would like to acknowledge the University of the Witwatersrand and the University of Pretoria for the use of the Raymond A Dart and Pretoria Bone Collections respectively, as well as the curators of these collections. The authors would like to acknowledge the original artwork provided by TMR Houlton for Supplementary Figures 5, 6 and 7.

Funding

This research was partially funded through the financial assistance of the National Research Foundation (NRF) and the JJJ Smieszek Award.

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Authors and Affiliations

  1. Human Variation and Identification Research Unit, School of Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

    Nicolene Jooste & Maryna Steyn

  2. Independent Actuary and Researcher, Fellow of the Actuarial Society of Southern Africa, Pretoria, South Africa

    Samantha Pretorius

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  1. Nicolene Jooste
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  2. Samantha Pretorius
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  3. Maryna Steyn
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Correspondence to Nicolene Jooste.

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Ethics clearance specific to this study was not required as an ethics waiver (W-CJ-140604–1) applies to studies conducted on material donated for the purposes of training and research as stipulated in the National Health Act No 61 of 2003 of South Africa.

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Jooste, N., Pretorius, S. & Steyn, M. Performance of three mathematical models for estimating age-at-death from multiple indicators of the adult skeleton. Int J Legal Med 136, 739–751 (2022). https://doi.org/10.1007/s00414-021-02727-4

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