Comparing the accuracy and precision of three techniques used for estimating missing landmarks when reconstructing fossil hominin crania
Article first published online: 10 FEB 2009
Copyright © 2009 Wiley-Liss, Inc.
American Journal of Physical Anthropology
Volume 140, Issue 1, pages 1–18, September 2009
How to Cite
Neeser, R., Ackermann, R. R. and Gain, J. (2009), Comparing the accuracy and precision of three techniques used for estimating missing landmarks when reconstructing fossil hominin crania. Am. J. Phys. Anthropol., 140: 1–18. doi: 10.1002/ajpa.21023
- Issue published online: 11 AUG 2009
- Article first published online: 10 FEB 2009
- Manuscript Accepted: 17 DEC 2008
- Manuscript Received: 14 JUL 2008
- The National Research Foundation of South Africa
- The Paleontological Scientific Trust
- mean substitution;
- thin plate splines;
Various methodological approaches have been used for reconstructing fossil hominin remains in order to increase sample sizes and to better understand morphological variation. Among these, morphometric quantitative techniques for reconstruction are increasingly common. Here we compare the accuracy of three approaches—mean substitution, thin plate splines, and multiple linear regression—for estimating missing landmarks of damaged fossil specimens. Comparisons are made varying the number of missing landmarks, sample sizes, and the reference species of the population used to perform the estimation. The testing is performed on landmark data from individuals of Homo sapiens, Pan troglodytes and Gorilla gorilla, and nine hominin fossil specimens. Results suggest that when a small, same-species fossil reference sample is available to guide reconstructions, thin plate spline approaches perform best. However, if no such sample is available (or if the species of the damaged individual is uncertain), estimates of missing morphology based on a single individual (or even a small sample) of close taxonomic affinity are less accurate than those based on a large sample of individuals drawn from more distantly related extant populations using a technique (such as a regression method) able to leverage the information (e.g., variation/covariation patterning) contained in this large sample. Thin plate splines also show an unexpectedly large amount of error in estimating landmarks, especially over large areas. Recommendations are made for estimating missing landmarks under various scenarios. Am J Phys Anthropol 2009. © 2009 Wiley-Liss, Inc.