Observer error, dental wear, and the inference of new world sundadonty

Bibliographic Data

ID8317677
AuthorsC M Stojanowski (0000-0003-3866-4999, Arizona State University, corresponding author), Kent M Johnson (0000-0002-3933-6439, Center for Bioarchaeological Research School of Human Evolution and Social Change, Arizona State University AZ)
Year2015
Volume156
Issue3
Pages349-362
Publication date2015-03-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueAmerican Journal of Physical Anthropology (JOURNAL)
Journal identifiersISSN: 0002-9483 • E-ISSN: 1096-8644
PublisherWiley (PUBLISHER • GB)
DOI10.1002/ajpa.22653
PMID25363296
OpenAlexW2126538299
LanguageEN
Citations received15
References cited52

Dental morphology provides important information on human evolution and interpopulation relationships. Dental wear is one of the major limitations of morphological data analysis. Wear figures heavily in existing debates about patterns of New World dental variation with some scholars finding evidence for a more generalized dentition in early New World populations (Powell: Doctoral Dissertation, Texas A&M University, TX (1995)) and others questioning these findings based on the probable effects of dental wear on trait scores (Turner, The First Americans: the Pleistocene Colonization of the New World. San Francisco: California Academy of Sciences (2002) 123–158; Turner: Am J Phys Anthropol 130 (2006) 455–461; Turner and Scott, Handbook of paleoanthropology, Vol. III: Phylogeny of Hominids. New York: Springer (2007) 1901–1941). Here we evaluate these competing claims using data from the Early Archaic Windover sample. Results confirm the dental distinctiveness of Windover with respect to other Old World Asian (i.e., sinodont/sundadont) populations. However, comparison of our results to those of Powell (1995) also highlights significant interobserver error. Statistical analysis of matched wear and morphology scores suggests trait downgrading for some traits. Patterns of missing data present a more challenging (and potentially serious) problem. Use of Little's MCAR test for missing data mechanisms indicates a complex process of data collection in which incidental and opportunistic recording of both highly worn and unerupted teeth introduce a “missing not at random” mechanism into our dataset that biases dental trait frequencies. We conclude that patterns of missingness and formal research designs for “planned missingness” are needed to help mitigate this bias. Am J Phys Anthropol 156:349–362, 2015. © 2014 Wiley Periodicals, Inc

Archaeology · Biology · Evolutionary biology · Inference · Missing data · Optimal distinctiveness theory · Paleoanthropology · Sociology · Statistics · Trait · Artificial Intelligence · Computer Science · Demography · Forensic Anthropology and Bioarchaeology Studies · History · Mathematics · Pleistocene-Era Hominins and Archaeology · Psychology · Social Psychology · Wildlife Ecology and Conservation