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TestDimorph: An R package for analysis of interpopulation sexual dimorphism differences using summary statistics.

Bassam A Abulnoor1, MennattAllah Hassan Attia2, Iain R Konigsberg3

  • 1Fixed prosthodontics, Faculty of dentistry, Ain Shams University, Cairo, Egypt.

American Journal of Biological Anthropology
|September 11, 2023
PubMed
Summary
This summary is machine-generated.

TestDimorph is a new R package for comparing sexual dimorphism across samples using summary statistics. It offers univariate and multivariate analyses, enhancing bioanthropological research by providing accessible statistical testing for trait differences.

Keywords:
MANOVAR languageRelethford and Hodges and Greene's t-testquantitative traitssexual dimorphismunbalanced ANOVA

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Area of Science:

  • Bioanthropology
  • Statistical Genetics
  • Computational Biology

Background:

  • Sexual dimorphism in traits varies across populations.
  • Bioanthropological studies often report sex differences but lack statistical rigor and data sharing.
  • Quantifying and comparing the degree of sexual dimorphism across samples is crucial but methodologically challenging.

Purpose of the Study:

  • Introduce TestDimorph, the first R package for testing and comparing sexual dimorphism degrees across multiple samples.
  • Provide researchers with a robust tool to analyze inter-sample variations in sexual dimorphism using summary statistics.
  • Facilitate reproducible bioanthropological research by enabling direct comparison of dimorphism patterns.

Main Methods:

  • Implemented univariate and multivariate analytical approaches for comparing sexual dimorphism across two or more samples.
  • Utilized established statistical methods including ANOVA, mixture intersection index, dissimilarity index, and Hedges' g with confidence intervals.
  • Developed functions for data simulation and extraction of summary statistics directly within the package.

Main Results:

  • Demonstrated the application and functionality of TestDimorph using built-in datasets.
  • Showcased the package's capability to perform comprehensive analyses of sexual dimorphism from summary statistics.
  • Validated the utility of univariate and multivariate methods for inter-sample dimorphism comparisons.

Conclusions:

  • TestDimorph offers a comprehensive solution for analyzing and comparing sexual dimorphism across different samples.
  • The package enhances bioanthropological research by providing accessible, statistically sound methods for dimorphism analysis.
  • Facilitates data sharing and reproducibility by working with summary statistics and offering data simulation capabilities.