These results support the use of the TA method by researchers of varying experience levels. Further, they validate its use on forensic cases, given the low error overall.

A critical step in age-at-death estimation is to identify the age-at-death distribution to which the unknown skeletal remains most likely belong. Age estimation based on a frequentist approach assumes that the age distribution of the target population is same as that of the reference sample. In a Bayesian framework, researchers have greater flexibility, with the freedom to specify mortality information via a prior distribution and integrate it with osteological data to produce more accurate age estimates. The selection of an optimal prior remains challenging, as forensic anthropologists analyze unidentified individuals often originating from unknown populations. Understanding the effects of the prior choice on the final age produced for various populations is essential to the interpretation of these estimates.In this article we investigate the effects of three different priors on age estimates using scores of three traditional methods collected on Asian skeletal samples representing peoples from Japan and Thailand. We test a uniform prior, which assumes the equal chance of death regardless of age, as well as various informative priors, derived from a Japanese mortality database and skeletal collections. We combine each of the priors with the parameters of the cumulative probit regression model to obtain age estimates. The results of our analyses show that the informative prior outperforms when it is carefully chosen to reflect the geographic and temporal origins of the target population. While the uniform prior produces the least-biasedage estimates, one should be cautious, as it can generate unrealistically old and inaccurate ages.

In an effort to standardize data collection and analysis in age estimation, a series of computational methods utilizing high-dimensional image data of the age indicator have recently been proposed as an alternative to subjective visual, trait-to-phase matching techniques. To systematically quantify the reproducibility of such methods, we investigate the intrascan variability and within- and between-observer reliability in initial scan data capturing and editing using 3D laser scans of the Suchey-Brooks pubic symphysis casts and five shape-based computational methods. Our results show that (i) five observers with various training background and experience levels edited the scans consistently for all three trials and the derived shape measures and age estimates were in excellent agreement among observers, and (ii) the computational methods are robust to a measured degree of scan trimming error. This study supports the application of computational methods to 3D laser scanned images for reliable age-at-death estimation, with reduced subjectivity.

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The pubic symphysis is among the most commonly used bilateral age indicators. Because of potential differences between right and left sides, it is necessary to investigate within-individual asymmetry, which can inflate age estimation error. This study uses 3D laser scans of paired pubic symphyses for 88 documented White males. Scan data are analyzed by numerical shape algorithms, proposed as an alternative to traditional visual assessment techniques. Results are used to quantify the within-individual asymmetry, evaluating if one side produces a better age-estimate. Relationships between the asymmetry and advanced age, weight, and stature are examined. This analysis indicates that the computational, shape-based techniques are robust to asymmetry (>80% of paired differences are within 10 years and >90% are within 15 years). For notably more asymmetric cases, differences in estimates are not associated with life history factors. Based on this study, either side can be used for age-at-death estimation by the computational methods.