Unidentified human remains are subject to forensic anthropological assessment to facilitate positive identification. Accurate and reliable estimation of sex is an imperative
aspect of this process, and whilst osteometric disparities of the femur have been exploited for sex estimation in various populations, minimal research exists regarding those of English provenance. Therefore, this dissertation was concerned with using a sample of 27 English femora to investigate the sexual dimorphism of 10 osteometric
parameters and evaluate their utility for sex estimation, by developing stepwise and direct discriminant functions. A leave-one-out cross-validation method was employed
to evaluate the predictive performance of each function. Overall, significant sexual dimorphism was discovered within the present population, enabling the estimation of
sex from the femur. Univariate, stepwise functions yielded sex classification accuracies ranging from 70.4 – 96.3%, with maximum length emerging as the most discriminate univariate parameter. Multivariate, direct discriminant functions yielded sex classification accuracies ranging from 74.1- 92.6%, failing to outperform univariate functions. The most discriminate direct function used the parameters maximum length, transverse head diameter and trochanteric oblique length (92.6%). The present investigation affirmed the highly sexually dimorphic nature of the femur, and illustrated the utility of discriminant function analysis as means of estimating sex in a relatively unexplored population. However, limitations associated with the investigation may restrict the generalisability, applicability and accuracy of results and so should be interpreted with caution.
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