dataframe_sexing: Internal function for sexing several human ossa coxae using...

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

Internal function for sexing several human ossa coxae using both original and revised Bruzek's methods (2002, 2019)

Description

Produces sex estimates from each of the ossa coxae submitted by the user through the graphical user interface of the R-Shiny application.

Usage

dataframe_sexing(data, ref, updateProgressBar = NULL, conf_level = 0.95,
strategy = c("BIC", "AIC", "None"), trace = 1)

Arguments

data	A test dataset submitted by the user throught the graphical user interface. The predictive factors (i.e. the eleven trichotomic traits) should have the same headers and levels as in the reference dataset ‘refData’ included in PELVIS. An example of valid data file can be found on Zenodo: \Sexpr[results=rd]{tools:::Rd_expr_doi("10.5281/zenodo.2586897")} (its field separator is the semicolon ";").
ref	A learning dataset for logistic regression models, basically the dataset ‘refDataBruzek02’ included in PELVIS (or any other dataset with the same variables).
updateProgressBar	Internal option for the R-Shiny application.
conf_level	0.95 by default, confidence level needed to produce a sex estimate.
strategy	A choice of information criterion ("BIC" or "AIC") for variable selection in logistic regression models, or "None" for no variable selection.
trace	See MASS::stepAIC.

Value

A complete dataframe of results displayed through the R-Shiny application.

Note

This is 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

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