The use of generalized linear models and generalized estimating equations in bioarchaeological studies

• Published in: American journal of physical anthropology Vol. 153; no. 3; pp. 473 - 483
• Main Author: Nikita, Efthymia
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01.03.2014; Wiley Subscription Services, Inc
• Subjects: Adolescent; Adult; Anthropology, Physical - methods; Anthropometry; archaeological collections; Archaeological sites; Covariance; entheses; Experimental archaeology; Female; generalized linear models; Humans; Linear Models; Male; Middle Aged; Models, Biological; North Africa; Pelvis - anatomy & histology; Physical anthropology; Population; Pubic Symphysis - anatomy & histology; Statistical analysis; Statistics as Topic; Young Adult; archaeological collections; generalized linear models; statistical analysis; entheses
• ISSN: 0002-9483; 1096-8644; 1096-8644; 2692-7691
• DOI: 10.1002/ajpa.22448

The current article explores whether the application of generalized linear models (GLM) and generalized estimating equations (GEE) can be used in place of conventional statistical analyses in the study of ordinal data that code an underlying continuous variable, like entheseal changes. The analysis of artificial data and ordinal data expressing entheseal changes in archaeological North African populations gave the following results. Parametric and nonparametric tests give convergent results particularly for P values <0.1, irrespective of whether the underlying variable is normally distributed or not under the condition that the samples involved in the tests exhibit approximately equal sizes. If this prerequisite is valid and provided that the samples are of equal variances, analysis of covariance may be adopted. GLM are not subject to constraints and give results that converge to those obtained from all nonparametric tests. Therefore, they can be used instead of traditional tests as they give the same amount of information as them, but with the advantage of allowing the study of the simultaneous impact of multiple predictors and their interactions and the modeling of the experimental data. However, GLM should be replaced by GEE for the study of bilateral asymmetry and in general when paired samples are tested, because GEE are appropriate for correlated data. Am J Phys Anthropol 153:473–483, 2014. © 2013 Wiley Periodicals, Inc.