I.G. Shirobokov. Do anthropologists really consider sample size in craniological research

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I.G. Shirobokov - Peter the Great Museum of Anthropology and Ethnography (the Kunstkamera) of the Russian Academy of Sciences, Universitetskaya Naberezhnaya, 3, St. Petersburg, 199034, Russia
E-mail: ivansmith@bk.ru
ORCID: 0000-0002-3555-7509


УДК 572.08
DOI: 10.31250/2658-3828-2019-1-140-153


Abstract: According to the results of my anonymous survey, most physical anthropologists believe that they take into account the possible biases related to the sample size on the research results. The analysis of more than two hundred Russian-language studies on cranial metric published from 2000 to 2018 shows that this statement is only partially valid. As a rule statistically small samples (median value of 20) frequently become the object of craniological studies. The smaller the sample size the higher the probability of its characteristics to deviate from the real characteristics of the general population. However, the sensitivity of researchers to the possible statistical biases related to the sample size is rather limited. Actually some methods of analysis are defined as associated with high risk of accepting random characteristics as representative ones. In most cases the need of using of statistical criteria for comparing empirical samples and expected values of intragroup dispersions, correlations between traits, and sexual dimorphism coefficients is ignored by researchers. Some researchers continue to use an individual-typological approach in the analysis of small series and deny the leading role of random individual variability. Probable reason for the popularity of this approach is that it increases the likelihood of finding morphological similarities between compared populations (arbitrarily divided into subgroups). The majority of links will be random but some of them can be supported by independent systems of traits. In general, the degree of researchers' confidence in the results of analysis only partly depends on the sample size and to a large extent on the researcher ability to match these results to the known outer sample context.

Keywords: craniology, sampling problem, research bias, multiple comparisons.


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