indiv_sexing: Internal function for sexing one single human os coxae using...

In PELVIS: Probabilistic Sex Estimate using Logistic Regression, Based on VISual Traits of the Human Os Coxae

Internal function for sexing one single human os coxae using revised Bruzek's method (2019)

Description

Produces a statistical sex estimate from up to eleven characters observed on the human os coxae, following Bruzek (2019), and using logistic regression models.

Usage

indiv_sexing(ref, new_ind, strategy = c("BIC", "AIC", "None"), trace = 1,
conf_level = 0.95)

Arguments

ref	A learning dataset for logistic regression models, basically the dataset ‘refData’ included in PELVIS (or any other dataset with the same variables).
new_ind	A new os coxae to be determined, with eleven observed traits (possibly with missing values).
strategy	A choice of information criterion ("BIC" or "AIC") for variable selection in logistic regression models, or "None" for no variable selection.
trace	Passed to MASS::stepAIC.
conf_level	Required posterior probability threshold to produce a sex estimate.

Value

A list with the following components:

PredictedSex	One unique character value, ‘F’, ‘I’ or ‘M’: final sex estimate for the studied os coxae.
PostProb	Posterior probability for the individual to be a male.
BestModel	Best logistic regression model for the studied os coxae according to the BIC criterion.
VariablesUsed	Names of the variables (including part or all of the nonmissing traits for the studied os coaxe) used in this best model.
cvRate	Success rate in cross-validation. Cf. Santos et al. (2019) for more details about cross-validation here.
cvIndet	Rate of individuals remaining indeterminate using the best logistic regression model.

Note

This is mostly an internal function for the R-Shiny application implemented in PELVIS.

Author(s)

Frédéric Santos, <[e-mail]>

References

Santos, F., Guyomarc'h, P., Rmoutilova, R. and Bruzek, J. (2019) A method of sexing the human os coxae based on logistic regressions and Bruzek's nonmetric traits. American Journal of Physical Anthropology 169(3), 435-447. doi: 10.1002/ajpa.23855

Examples

data(refDataBruzek02)
# Pick the first individual of the reference dataset with its 11 traits, as an example:
individual <- refDataBruzek02[1, -c(1:6)]
individual
# Compute a sex estimate for this individual:
indiv_sexing(ref = refDataBruzek02, new_ind = individual)

PELVIS documentation built on Aug. 8, 2023, 5:09 p.m.