Sex estimation using nonmetric variables: Application of R functions

Efthymia Nikita; Julieta G. García-Donas; Panos Nikitas; Zuzana Obertová; Elena F. Kranioti

doi:10.1016/B978-0-12-815764-0.00004-6

Sex estimation using nonmetric variables: Application of R functions

Efthymia Nikita, Julieta G. García-Donas, Panos Nikitas, Zuzana Obertová, Elena F. Kranioti

Research output: Chapter in Book/Conference paper › Chapter › peer-review

1 Citation (Scopus)

Abstract

The aim of this paper is to provide a methodological guide on how to select, test, and use statistical procedures for sex estimation using morphological traits of the cranium expressed on an ordinal scale. R functions were developed to implement binary logistic regression (BLR) and linear discriminant analysis (LDA), and step-by-step instructions with examples from Cretan and Cypriot modern identified skeletal samples were provided to illustrate the potential and limitations of each method. Even though the current case study focused on cranial traits, the R functions provided may be used for any morphological skeletal trait.

Original language	English
Title of host publication	Statistics and Probability in Forensic Anthropology
Editors	Zuzana Obertova, Alistair Stewart, Cristina Cattaneo
Publisher	Elsevier
Chapter	4.1
Pages	139-153
Number of pages	15
ISBN (Electronic)	9780128157640
ISBN (Print)	9780128157657
DOIs	https://doi.org/10.1016/B978-0-12-815764-0.00004-6
Publication status	Published - 1 Jan 2020

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10.1016/B978-0-12-815764-0.00004-6

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title = "Sex estimation using nonmetric variables: Application of R functions",

abstract = "The aim of this paper is to provide a methodological guide on how to select, test, and use statistical procedures for sex estimation using morphological traits of the cranium expressed on an ordinal scale. R functions were developed to implement binary logistic regression (BLR) and linear discriminant analysis (LDA), and step-by-step instructions with examples from Cretan and Cypriot modern identified skeletal samples were provided to illustrate the potential and limitations of each method. Even though the current case study focused on cranial traits, the R functions provided may be used for any morphological skeletal trait.",

keywords = "Accuracy, Biological profile, Discriminant function, Ordinal scale, Regression analysis",

author = "Efthymia Nikita and Garc{\'i}a-Donas, {Julieta G.} and Panos Nikitas and Zuzana Obertov{\'a} and Kranioti, {Elena F.}",

note = "Funding Information: This study was supported by the University of Ss. Cyril and Methodius in Trnava grant FPPV-04-2019 and is the result of the project implementation supported by the Research and Development Operational Programme funded by the ERDF (ITMS 26240220086). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: {\textcopyright} 2020 Elsevier Inc. All rights reserved.",

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doi = "10.1016/B978-0-12-815764-0.00004-6",

language = "English",

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TY - CHAP

T1 - Sex estimation using nonmetric variables

T2 - Application of R functions

AU - Nikita, Efthymia

AU - García-Donas, Julieta G.

AU - Nikitas, Panos

AU - Obertová, Zuzana

AU - Kranioti, Elena F.

N1 - Funding Information: This study was supported by the University of Ss. Cyril and Methodius in Trnava grant FPPV-04-2019 and is the result of the project implementation supported by the Research and Development Operational Programme funded by the ERDF (ITMS 26240220086). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: © 2020 Elsevier Inc. All rights reserved.

PY - 2020/1/1

Y1 - 2020/1/1

N2 - The aim of this paper is to provide a methodological guide on how to select, test, and use statistical procedures for sex estimation using morphological traits of the cranium expressed on an ordinal scale. R functions were developed to implement binary logistic regression (BLR) and linear discriminant analysis (LDA), and step-by-step instructions with examples from Cretan and Cypriot modern identified skeletal samples were provided to illustrate the potential and limitations of each method. Even though the current case study focused on cranial traits, the R functions provided may be used for any morphological skeletal trait.

AB - The aim of this paper is to provide a methodological guide on how to select, test, and use statistical procedures for sex estimation using morphological traits of the cranium expressed on an ordinal scale. R functions were developed to implement binary logistic regression (BLR) and linear discriminant analysis (LDA), and step-by-step instructions with examples from Cretan and Cypriot modern identified skeletal samples were provided to illustrate the potential and limitations of each method. Even though the current case study focused on cranial traits, the R functions provided may be used for any morphological skeletal trait.

KW - Accuracy

KW - Biological profile

KW - Discriminant function

KW - Ordinal scale

KW - Regression analysis

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U2 - 10.1016/B978-0-12-815764-0.00004-6

DO - 10.1016/B978-0-12-815764-0.00004-6

M3 - Chapter

AN - SCOPUS:85122780298

SN - 9780128157657

SP - 139

EP - 153

BT - Statistics and Probability in Forensic Anthropology

A2 - Obertova, Zuzana

A2 - Stewart, Alistair

A2 - Cattaneo, Cristina

PB - Elsevier

ER -

Sex estimation using nonmetric variables: Application of R functions

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Statistics and probability in forensic anthropology

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