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30 mars 2020

Some useful R ressources for archaeologists and anthropologists

“R packages, like friends, should be few and well chosen.” — Approximately by Charles Caleb Colton.

As far as I know (and as of march 2020), there is no CRAN task view for past sciences. Ben Marwick seems to maintain a beta version of such a task view, but this very long list of packages may be more intimidating than useful for beginners or casual R users1. Here is a much shorter, opinionated and clearly non-exhaustive list.

Age and sex estimation

  • osteomics is a great platform with many R-shiny applications, implementing various classical methods of skeletal or dental age and sex estimation.
  • PELVIS proposes a graphical user interface implementing Bruzek morphoscopic methods of sex estimation based on the os coxae [6,1].

Biodistances

  • AnthropMMD [5] allows to compute the mean measure of divergence with a graphical user interface.
  • smacof is a package implementing modern algorithms for computing multidimensional scaling (MDS), even when some distances are missing [2].
  • vegan implements various useful methods for working with biodistances (Mantel test, …) and performing NPMANOVAs.

Cross-sectional geometry

  • Diaphysator, along with its companion software Extractor, generates maps and graphs based on cortical thickness and cross-sectional geometry for the cartography of long bones diaphysis [7].
  • morphomap allow to extract cross sections from long bone meshes at specified intervals along the diaphysis, and many other things.

Data exploration

  • corrplot proposes a graphical representation of correlation matrices (and options to perform a clustering of variables), which is really useful in osteometric studies.
  • mice allows (among many other functions) to get a graphical representation of the pattern of missing values in a given dataset [8].

Inter- or intra-observer error assessment

  • irr implements numerous measures of interrater reliability and agreement for quantitative, ordinal and nominal data.

Morphometrics

I am clearly not an expert in this field, but there are several R packages I like, such as Morpho or shapes.

Multivariate analyses

  • FactoMineR is probably the best R packages to perform principal component analyses [4] and related methods (MCA, FAMD, …). It also has a great documentation, with a very complete website and video tutorials. It has also a good graphical user interface with the package Factoshiny.
  • missMDA allows to handle and impute missing data upstream of multivariate analyses [3].

References

[1] Jaroslav Bruzek. A method for visual determination of sex, using the human hip bone. American Journal of Physical Anthropology, 117(2):157--168, 2002. [ DOI ]
[2] Jan de Leeuw and Patrick Mair. Multidimensional Scaling Using Majorization: SMACOF in R. Journal of Statistical Software, 31(1):1--30, 2009. [ DOI ]
[3] Julie Josse and François Husson. missMDA : A Package for Handling Missing Values in Multivariate Data Analysis. Journal of Statistical Software, 70(1), 2016. [ DOI ]
[4] Sébastien Lê, Julie Josse, and François Husson. FactoMineR: An R Package for Multivariate Analysis. Journal of Statistical Software, 25(1), 2008. [ DOI ]
[5] Frédéric Santos. AnthropMMD: An R package with a graphical user interface for the mean measure of divergence. American Journal of Physical Anthropology, 165(1):200--205, 2018. [ DOI ]
[6] Frédéric Santos, Pierre Guyomarc'h, Rebeka Rmoutilova, and Jaroslav Bruzek. 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, 2019. [ DOI ]
[7] Frédéric Santos and Alizé Lacoste Jeanson. Diaphysator: An online application for the exhaustive cartography and user-friendly statistical analysis of long bone diaphyses. American Journal of Physical Anthropology, 0(0). [ DOI ]
[8] Stef van Buuren and Karin Groothuis-Oudshoorn. Mice: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software, 45(1):1--67, 2011. [ DOI ]

Footnotes:

1

Furthermore, many of them have a very general scope, and are perfectly dispensable for any R user.

Tags: R