A Metric Method for Sex Determination Using the Proximal Femur and Fragmentary Hipbone*^,†

Abstract

The pubic bone is considered one of the best sources of information for determining sex using skeletal remains, but can be easily damaged postmortem. This problem has led to the development of nonpelvic methods for cases when the pubic bone is too damaged for analysis. We approached this problem from a different perspective. In this article, we present an approach using new measurements and angles of the proximal femur to recreate the variation in the pubic bone. With a sample from the Terry Collection (n > 300), we use these new variables along with other traditional measurements of the femur and hipbone to develop two logistic regression equations (femur and fragmentary hipbone, and femur only) that are not population specific. Tests on an independent sample (Grant Collection; n = 37-40) with a different pattern of sexual dimorphism resulted in an allocation accuracy of 95-97% with minimal difference by sex.

Investigation on the utility of permanent maxillary molar cusp areas for sex estimation

“…In addition to discriminant function analysis, the data was subjected to binary logistic regression analysis as previous studies [44][45][46][47][48], including a recent dental investigation [49], have suggested that it may be advantageous to use both statistical methods to estimate sex. As pointed out by these authors, the benefits of binary logistic regression are that this technique generally performs as well as or better than discriminant function analysis with fewer statistical assumptions when predicting dichotomous variables such as sex, and the resulting score used to classify an unknown individual also provides a probability value for the allocation.…”

A comparison between neural network and other metric methods to determine sex from the upper femur in a modern French population

“…This is the reason why some authors have developed sex determination models using non-linear classification methods. For instance, Leguebe and Albert [3], Albanese [4], Torwalt and Hoppa [5], Francesquini et al [6] and Albanese et al [7] have analysed the predictive ability of logistic regression. Still others, such as Corsini et al [8] or Mahfouz et al [1] have analysed the ability of a neural network to build accurate models.…”

A method for sex estimation using the proximal femur

“…It is also dimorphic within the same population [5], and very useful in sexing skeletal remains. Several dimensions of the femur, including femoral head diameter, femoral length, and bicondylar breadth have been utilized for the allocation of sex in unknown skeletal individuals [1,[7][8][9][10][11][12][13].…”

“…Some geometric parameters of the proximal femur are associated with the risk of hip fractures [18][19][20], and sex differences in FNAL and FNW have long been noted in epidemiological studies [18][19][20][21][22]. Furthermore, the structural demands of the unrelated but sometimes conflictual functions of parturition and locomotion affected not only the pelvis but also the angle and length of the femoral neck [10].…”