Abstract
Background/Objectives: The identification of a decedent through skeletal analysis is dependent on accurate estimation of demographic characteristics, including biological sex. The most well-known sex estimation technique using the pubic bone is the Phenice method. In 2012, it was revised by Klales and colleagues and a logistic regression equation to predict sex was applied. Later, a program that estimates sex from Klales’ scoring with a random forest model, MorphoPASSE, was developed by Klales. Methods: Here we compare the accuracy of the original and revised methods, along with MorphoPASSE, using a contemporary sample of Northern Italians with documented sex. We further test the assertions by Phenice that his method is easy to employ for new observers and that ambiguity can be applied when characteristics do not morphologically fit into the categories of the method. Accuracy, error, bias, sensitivity, and specificity were calculated for each approach, along with McNemar’s tests for paired data, which compared documented sex and estimated sex. A linear weighted Cohen’s Kappa measured the differences in scoring between a new observer and an experienced observer. Results: Phenice’s method achieved higher accuracy (97%) than the Klales method and MorphoPASSE (86% each), as well as higher sensitivity and specificity, and lower error and bias. All McNemar’s tests conducted were not significant. The new observer demonstrated a similar accuracy (93%) to the experienced observer (97%). Furthermore, comparisons of Phenice’s scoring with ambiguity indicate its superior performance for capturing variation over the Klales method and MorphoPASSE. Conclusions: Phenice’s method is recommended in forensic anthropology and bioarchaeological contexts, particularly in Milan.