Multivariate Regression Methods for the Analysis of Stature

Lyle W. Konigsberg, Lee Meadows Jantz

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In forensic anthropology the size of “organs” (bones) from the skeletal system is often used to estimate an individual’s stature via linear regression of stature onto one or more bones. This type of analysis is the reverse of how one usually studies size and shape in biology, where organ sizes are viewed as being dependent on body size. We show that the multivariate regression of bone sizes onto body size (stature) provides a very general framework for both the estimation of stature and for the presentation of evidence on a putative identification. We further show that using an informative prior for stature from the reference sample is completely equivalent to performing the traditional regression of stature onto long bones, that using a uniform prior for stature gives the maximum likelihood estimator for stature, and that using an informative prior stature distribution from a relevant population provides a “population specific” method.

Original languageEnglish (US)
Title of host publicationNew Perspectives in Forensic Human Skeletal Identification
EditorsKrista E Latham, Eric J Bartelink, Michael Finnegan
PublisherElsevier
Pages87-104
Number of pages18
ISBN (Electronic)9780128054291
ISBN (Print)9780128125380
DOIs
StatePublished - 2018

Keywords

  • Allometry
  • Fully stature estimation
  • Long bones
  • Markov chain monte carlo
  • OpenBUGS
  • Statistical calibration
  • WinBUGS

ASJC Scopus subject areas

  • Social Sciences(all)

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