Estimation of Sex from the Upper Limb in Modern Cretans with the Aid of ROC-Analysis: A Technical Report

Abstract

Discriminant function analysis is one of the most popular methods employed for grouping specimens according to optimal combination of linear measurements. Many studies have used this method with the objective of producing population specific formulae for sex estimation from different skeletal parts of the skeleton. This study focuses on the long bones of the upper limb using Receiving operation characteristics (ROC) curves. A total of 173 well preserved skeletons of Cretan origin were used. A total of 12 measurements are taken from the bones of the upper limn. The diagnostic value of the single variables was evaluated using the Area Under the Curve (AUC). The cut-off values and the diagnostic characteristics of each variable (Sensitivity, Specificity, Positive and Negative predictive values) are presented. The correlation of normally distributed the variables will be tested with the method Pearson correlation coefficient. The level of statistical significance is set to p<0.05 (a-error). Means, standard deviations and F-ratios for all single dimensions are calculated by performing ANOVA with SPSS 13.0. All measurements are found statistically significant at the level of 0.0001. The best discriminatory variables was found to be radius length (91.3%) followed by humerus head vertical diameter (90.2%) and ulnar length (89%). Comparison with published standards for mainland Greece reaffirms a scope for developing additional standards for modern Cretans. Traditional methods use discriminant function analysis to study sexual dimorphism. Herein a different approach is proposed. ROC curves, known to be very effective in medical decision making, are employed in the evaluation of several variables as effective markers for sex identification. The method should complement multivariate statistical analyses.