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A simple method for visualization of influential landmarks when using euclidean distance matrix analysis

Bibliographic Data

ID5186192
AuthorsTheodore M Cole Iii, Theodore M Cole (University of Missouri–Kansas City, corresponding author), Joan T Richtsmeier (0000-0002-0239-5822, Johns Hopkins University)
Year1998
Volume107
Issue3
Pages273-283
Publication date1998-11-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueAmerican Journal of Physical Anthropology (JOURNAL)
Journal identifiersISSN: 0002-9483 • E-ISSN: 1096-8644
PublisherWiley (PUBLISHER • GB)
DOI10.1002/(sici)1096-8644(199811)107:3<273::aid-ajpa4>3.0.co;2-1
PMID9821492
OpenAlexW2109609078
LanguageEN
Citations received4
References cited25

Euclidean distance matrix analysis (EDMA) differs from most other morphometric methods for the analysis of landmark coordinate data in that it is coordinate-system invariant. However, strict adherence to coordinate-system invariance (for both biological and statistical reasons) introduces some difficulty in using graphic aids for the analysis and interpretation of EDMA results. We present a simple and effective graphic method to help localize important differences in form, growth, or shape by identifying "influential" landmarks. Examples are presented using simulated data and real data involving both children with craniofacial dysmorphologies and sexual dimorphism in adult Macaca fascicularis.

Algorithm · Combinatorics · Distance matrices in phylogeny · Distance matrix · Euclidean distance · Euclidean distance matrix · Euclidean geometry · Geometry · Matrix (chemical analysis) · Simple (philosophy) · Visualization · Artificial Intelligence · Categorization, perception, and language · Computer Science · Mathematics · Morphological variations and asymmetry · Spatial Cognition and Navigation

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Unique citing works4
Citations per year0,16
Citation span2001 - 2008 (8)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 3

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