Sexual Dimorphism of Human Adult Skulls by Multivariate Analysis

Abstract

Introduction: Sexual dimorphism in adult human skulls is critical in forensic anthropology and human identi𿿿cation. This study aims to assess the ef𿿿cacyof multivariate analysis in estimating sex based on cranial measurements. Methodology: A total of 108 adult skulls (58 male, 50 female) from a population in Maharashtra, India, were analyzed using 14 cranial parameters. Univariate and multivariate analyses were performed to compare the accuracy of sex determination. Descriptive statistics, identi𿿿cation points (IP), anddemarkingpoints (DP) were used to calculate ranges, means, and signi𿿿cance betweenmaleand female skulls. To improve accuracy, multivariate linear discriminant function analysis was used. Results: The results showed an overall accuracy of 76.85%, with a classi𿿿cationaccuracy of 84.48% for males and 68% for females. According to the study, males often had larger and more robust characteristics, while cranial measurements like cranial length, width, and height showed considerable sexual dimorphism. Conclusion: The results reveal that multivariate analysis remarkably improves sex determination compared to univariate methods. It is crucial to use multiple parameters for sex determination and implement population-speci𿿿c changes, which may improve accuracy even further. Overall, this study shows the importance of multivariate techniques in forensic identi𿿿cation, mainlywhenonlyskeletal remains are available for identi𿿿cation.