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Assessing intrasample variation: analysis of Rapa Nui (Easter Island) museum cranial collections example.

Vincent H Stefan1

  • 1Department of Anthropology, Lehman College, CUNY, Bronx, New York 10468, USA. vstefan@lehman.cuny.edu

American Journal of Physical Anthropology
|April 16, 2004
PubMed
Summary

This study on Rapa Nui (Easter Island) crania found minimal variation among museum collections, demonstrating the effectiveness of statistical methods for analyzing pooled skeletal data.

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Area of Science:

  • Osteology
  • Physical Anthropology
  • Bioarchaeology

Background:

  • Previous osteological studies often pooled Polynesian cranial samples, potentially obscuring intrasample variation.
  • Few studies have assessed variation within pooled skeletal data from different islands or museum collections representing the same population.

Purpose of the Study:

  • To examine Easter Island (Rapa Nui) crania from various museums to determine if significant differences exist among these collections.
  • To evaluate the reliability of pooled skeletal data for representing a specific population.

Main Methods:

  • Utilized the NORM statistical program for multiple imputation of incomplete multivariate datasets.
  • Applied a variance comparison method using variance/covariance matrices to compare six Rapa Nui museum samples against a baseline reference sample.

Related Experiment Videos

  • Assessed intrasample variability in male and female Rapa Nui skeletal material.

    • Main Results:

    • The six Rapa Nui museum samples exhibited minimal intrasample variability when compared to the baseline reference sample (MAPSE).
    • This consistency was observed despite samples being collected at different times and by different individuals.
    • The study confirmed the efficacy of multiple imputation and variance comparison in handling missing data and identifying sample variation.

    Conclusions:

    • Pooled skeletal data from different Rapa Nui museum collections can reliably represent the population.
    • Statistical methodologies like multiple imputation and variance comparison are effective for analyzing and validating pooled osteological data.
    • The findings support the use of such methods in future studies of prehistoric populations.