Analytical techniques and software for the study of intragroup metric variation using principal component analysis
Intragroup variation in human cranial samples is much less well understood than intergroup variation. The aims of this study were to develop a flexible and assumption-free approach for detailed explorations and comparisons of intragroup metric variation in any number of samples and to create user-fr...
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Société d'Anthropologie de Paris
2021-04-01
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| Series: | Bulletins et Mémoires de la Société d’Anthropologie de Paris |
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| Online Access: | https://journals.openedition.org/bmsap/7539 |
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| author | Andrej Alexeevich Evteev Nikolai Evgenievich Staroverov Nikolai Nikolaevich Potrakhov |
| author_facet | Andrej Alexeevich Evteev Nikolai Evgenievich Staroverov Nikolai Nikolaevich Potrakhov |
| author_sort | Andrej Alexeevich Evteev |
| collection | DOAJ |
| description | Intragroup variation in human cranial samples is much less well understood than intergroup variation. The aims of this study were to develop a flexible and assumption-free approach for detailed explorations and comparisons of intragroup metric variation in any number of samples and to create user-friendly software for these purposes. We revisited the classic study design based on a comparison between the samples from Berg, Zalavar and Oslo from the W.W. Howells craniometric data set. Fourteen mid-facial dimensions were chosen for the analysis. "WorldPCA" software was employed for most of the analyses. This software implements a number of analytical functions aimed at exploring the results of principal component analysis. Our results confirm that the male sample from Berg displays a higher degree of variation. The cluster analyses have shown that intragroup variation in the three samples is mainly of a continuous nature. Arguably, the tendency to separate into distinct clusters is more pronounced in the samples from Oslo and Berg than from Zalavar. Some male individuals from Zalavar display distinct craniofacial features similar to those found in a South Siberian sample. Potential applications of these techniques and software are not restricted to cranial measurements but can be used for exploring any type of continuously varying data. No assumptions about the nature of the data should be made, and any number of samples can be compared simultaneously. |
| format | Article |
| id | doaj-art-1fbd9bdcd5934c6c95e45108b60cd413 |
| institution | Kabale University |
| issn | 1777-5469 |
| language | English |
| publishDate | 2021-04-01 |
| publisher | Société d'Anthropologie de Paris |
| record_format | Article |
| series | Bulletins et Mémoires de la Société d’Anthropologie de Paris |
| spelling | doaj-art-1fbd9bdcd5934c6c95e45108b60cd4132025-01-30T11:27:29ZengSociété d'Anthropologie de ParisBulletins et Mémoires de la Société d’Anthropologie de Paris1777-54692021-04-013310.4000/bmsap.7539Analytical techniques and software for the study of intragroup metric variation using principal component analysisAndrej Alexeevich EvteevNikolai Evgenievich StaroverovNikolai Nikolaevich PotrakhovIntragroup variation in human cranial samples is much less well understood than intergroup variation. The aims of this study were to develop a flexible and assumption-free approach for detailed explorations and comparisons of intragroup metric variation in any number of samples and to create user-friendly software for these purposes. We revisited the classic study design based on a comparison between the samples from Berg, Zalavar and Oslo from the W.W. Howells craniometric data set. Fourteen mid-facial dimensions were chosen for the analysis. "WorldPCA" software was employed for most of the analyses. This software implements a number of analytical functions aimed at exploring the results of principal component analysis. Our results confirm that the male sample from Berg displays a higher degree of variation. The cluster analyses have shown that intragroup variation in the three samples is mainly of a continuous nature. Arguably, the tendency to separate into distinct clusters is more pronounced in the samples from Oslo and Berg than from Zalavar. Some male individuals from Zalavar display distinct craniofacial features similar to those found in a South Siberian sample. Potential applications of these techniques and software are not restricted to cranial measurements but can be used for exploring any type of continuously varying data. No assumptions about the nature of the data should be made, and any number of samples can be compared simultaneously.https://journals.openedition.org/bmsap/7539intragroup variationprincipal component analysisHowells data set |
| spellingShingle | Andrej Alexeevich Evteev Nikolai Evgenievich Staroverov Nikolai Nikolaevich Potrakhov Analytical techniques and software for the study of intragroup metric variation using principal component analysis Bulletins et Mémoires de la Société d’Anthropologie de Paris intragroup variation principal component analysis Howells data set |
| title | Analytical techniques and software for the study of intragroup metric variation using principal component analysis |
| title_full | Analytical techniques and software for the study of intragroup metric variation using principal component analysis |
| title_fullStr | Analytical techniques and software for the study of intragroup metric variation using principal component analysis |
| title_full_unstemmed | Analytical techniques and software for the study of intragroup metric variation using principal component analysis |
| title_short | Analytical techniques and software for the study of intragroup metric variation using principal component analysis |
| title_sort | analytical techniques and software for the study of intragroup metric variation using principal component analysis |
| topic | intragroup variation principal component analysis Howells data set |
| url | https://journals.openedition.org/bmsap/7539 |
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