Statistical basis for positive identification in forensic anthropology

Dawnie Wolfe Steadman, Bradley J. Adams, Lyle W. Konigsberg

Research output: Contribution to journalArticlepeer-review


Forensic scientists are often expected to present the likelihood of DNA identifications in US courts based on comparative population data, yet forensic anthropologists tend not to quantify the strength of an osteological identification. Because forensic anthropologists are trained first and foremost as physical anthropologists, they emphasize estimation problems at the expense of evidentiary problems, but this approach must be reexamined. In this paper, the statistical bases for presenting osteological and dental evidence are outlined, using a forensic case as a motivating example. A brief overview of Bayesian statistics is provided, and methods to calculate likelihood ratios for five aspects of the biological profile are demonstrated. This paper emphasizes the definition of appropriate reference samples and of the "population at large," and points out the conceptual differences between them. Several databases are introduced for both reference information and to characterize the "population at large," and new data are compiled to calculate the frequency of specific characters, such as age or fractures, within the "population at large." Despite small individual likelihood ratios for age, sex, and stature in the case example, the power of this approach is that, assuming each likelihood ratio is independent, the product rule can be applied. In this particular example, it is over three million times more likely to obtain the observed osteological and dental data if the identification is correct than if the identification is incorrect. This likelihood ratio is a convincing statistic that can support the forensic anthropologist's opinion on personal identity in court.

Original languageEnglish (US)
Pages (from-to)15-26
Number of pages12
JournalAmerican journal of physical anthropology
Issue number1
StatePublished - Sep 2006
Externally publishedYes


  • Bayesian statistics
  • Forensic anthropology
  • Forensic odontology
  • Likelihood ratios

ASJC Scopus subject areas

  • Anatomy
  • Anthropology


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