Sex estimation from human skeletal remains is of vital importance in the buildup of a biological profile of an individual in medico-legal and bioarchaeological studies. The present study is focused on the estimation of sex from osteometric measurements of the complete femur and its fragmentary parts, and the development of a web based application related to this. Fifteen osteometric measurements were taken from 78 dry cadaveric femurs from the Faculty of Medicine, University of Kelaniya. Using R software, linear discriminant analysis and logistic regression methods were applied to build classification models with the help of the application of a stepwise procedure, to identify the best combination of measurements to estimate the sex of the femur. A cross-validation method was applied to estimate the predictive accuracy of each model. Since the linear discriminant analysis model gave more predictive accuracy than the regression model, we suggest using linear discriminant analysis to estimate the sex using osteometric measurements of the femur. From the whole femur measurements, a formula to determine sex was developed with highest total accuracy of 83 % using four parameters; epicondylar breadth, anteroposterior mid-shaft diameter, bi-trochanter length, and maximum shaft diameter. Similarly, measurements of transverse head diameter and bi-trochanter length with a total accuracy of 76 % for the proximal part of the femur, measurements of anteroposterior mid-shaft diameter with a total accuracy of 77 % for the mid-shaft, and measurements of epicondylar breadth and maximum length of the lateral condyle with a total accuracy of 70 % for the distal part of the femur were identified as significant discriminants to determine sex, and formulae were written accordingly. Average accuracy ranged from 83 % to 70 %, with male accuracy slightly higher than that of females. A web application to estimate the sex of femur using these formulae was developed and this will be of great importance for forensic medicine and bio-archaeological research in Sri Lanka.
KEY WORDS: Femur, osteometric measurements, sex, Sri Lanka, long bone.