Auricular Surface Aging: Comparing Two Methods that Assess Morphological Change in the Ilium with Bayesian Analyses.

Area of Science:

• Forensic Anthropology
• Bioarchaeology
• Statistical Modeling

Background:

• Forensic anthropology requires validated methods for skeletal age estimation.
• Current methods face challenges with bias, inaccuracy, and population specificity.
• Bayesian methodology offers a robust approach to mitigate these issues.

Purpose of the Study:

• To compare the efficacy of original and revised auricular surface aging methods using Bayesian statistics.
• To statistically model age estimation in Portuguese males.
• To provide accurate age estimation tools for forensic anthropological applications.

Main Methods:

• Application of Bayesian statistics and transition analysis.
• Utilizing American male data (n=372) and a Thai male prior (N=37).
• Modeling age estimation for Portuguese males (n=221) and assessing accuracy with cumulative binomial tests.

Main Results:

• Bayesian statistics and transition analysis significantly improved age estimation accuracy for both auricular surface methods.
• The revised auricular method demonstrated high accuracy without additional statistical modeling.
• The original method's accuracy was low without statistical modeling.
• Both auricular methods outperformed the Suchey-Brooks pubic symphysis method.

Conclusions:

• Bayesian statistical modeling enhances the reliability of skeletal age estimation methods in forensic anthropology.
• The revised auricular surface method is accurate and applicable without further statistical analysis.
• Reference tables for aging Portuguese males were generated, aiding in forensic casework.