Abstract

Introduction: Sexual dimorphism in adult human skulls is critical in forensic anthropology and human identification. This study aims to assess the efficacy of 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, identification points (IP), and demarking points (DP) were used to calculate ranges, means, and significance between male and female skulls. To improve accuracy, multivariate linear discriminant function analysis was used. Results: The results showed an overall accuracy of 76.85%, with a classification accuracy 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-specific changes, which may improve accuracy even further. Overall, this study shows the importance of multivariate techniques in forensic identification, mainly when only skeletal remains are available for identification.

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