Size factor as one of the problems in the sex estimation of skulls: Upper Palaeolithic sample from Předmostí (Czech Republic) as an example
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Rok publikování | 2011 |
Druh | Článek v odborném periodiku |
Časopis / Zdroj | Anthropologischer Anzeiger |
Fakulta / Pracoviště MU | |
Citace | |
www | http://www.ingentaconnect.com/content/schweiz/aa/2011/00000068/00000002/art00010?token=00561a385fc4d04500275c277b42572067547d773477702e6e60592f653b672c57582a72752d7088489ec7 |
Doi | http://dx.doi.org/10.1127/0003-5548/2011/0055 |
Obor | Aplikovaná statistika, operační výzkum |
Klíčová slova | Craniometrics; discriminant analysis; population affinity; diachronic changes; Gravettian |
Popis | In this study we estimate sex and population affinity of Gravettian Předmostí (P) skulls using linear and geometric discriminant analysis (DA), and compare them with results of 2D geometric morphometrics (GM). We used the measurements of P3 and P9 males, P4 and P10 females, as originally estimated by Matiegka (1934), as well as two databases - the recent skull database of Howells and the fossil data of Henke. DA classifies the P skulls as robust and belonging to the “male” region, loosing the sensitivity of inter-population differences influenced by size factor. That is why this approach could not be applied. The geographic inter-population differences according to DA do not define P skull shapes as extreme. The influence of geographic variability could be stronger than the inter-sexual differences. Despite the chronological differences between databases and Gravettian skulls, these differences are a component of regional inter-population variability. According to our results, GM is more successful methodological approach than DA. Our previous sex estimation of P skulls with help of GM is completely in accordance with the classical morphoscopic estimation. However, an appropriate reference database is necessary in both the GM and DA approaches. For the sexing of skull with unknown population affinity, and with absence of appropriate reference database, we suggest to use the application of more subjective visual scoring methods. |
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