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Size-Correction and Principal Components for Interspecific Comparative Studies

Phylogenetic methods for the analysis of species data are widely used in evolutionary studies. However, preliminary data transformations and data reduction procedures (such as a size-correction and principal components analysis, PCA) are often performed without first correcting for nonindependence a... Full description

Journal Title: Evolution 2009-12, Vol.63 (12), p.3258-3268
Main Author: Revell, Liam J
Format: Electronic Article Electronic Article
Language: English
Subjects:
PCA
Publisher: Malden, USA: Wiley/Blackwell
ID: ISSN: 0014-3820
Link: https://www.ncbi.nlm.nih.gov/pubmed/19663993
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title: Size-Correction and Principal Components for Interspecific Comparative Studies
format: Article
creator:
  • Revell, Liam J
subjects:
  • Analysis
  • Biological taxonomies
  • Brief Communication
  • BRIEF COMMUNICATIONS
  • Cladistic analysis
  • Comparative studies
  • Correlations
  • Covariance matrices
  • Data transformation
  • Eigenvectors
  • Evolution
  • Evolution & development
  • Evolutionary biology
  • evolutionary regression
  • least squares
  • Least-Squares Analysis
  • Linear regression
  • Matrices
  • Nonnative species
  • PCA
  • phylogenetic comparative methods
  • Phylogenetics
  • Phylogeny
  • Principal Component Analysis
  • Principal components analysis
  • Research
  • Species Specificity
  • Statistical analysis
  • Usage
ispartof: Evolution, 2009-12, Vol.63 (12), p.3258-3268
description: Phylogenetic methods for the analysis of species data are widely used in evolutionary studies. However, preliminary data transformations and data reduction procedures (such as a size-correction and principal components analysis, PCA) are often performed without first correcting for nonindependence among the observations for species. In the present short comment and attached R and MATLAB code, I provide an overview of statistically correct procedures for phylogenetic size-correction and PCA. I also show that ignoring phylogeny in preliminary transformations can result in significantly elevated variance and type I error in our statistical estimators, even if subsequent analysis of the transformed data is performed using phylogenetic methods. This means that ignoring phylogeny during preliminary data transformations can possibly lead to spurious results in phylogenetic statistical analyses of species data.
language: eng
source:
identifier: ISSN: 0014-3820
fulltext: no_fulltext
issn:
  • 0014-3820
  • 1558-5646
url: Link


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descriptionPhylogenetic methods for the analysis of species data are widely used in evolutionary studies. However, preliminary data transformations and data reduction procedures (such as a size-correction and principal components analysis, PCA) are often performed without first correcting for nonindependence among the observations for species. In the present short comment and attached R and MATLAB code, I provide an overview of statistically correct procedures for phylogenetic size-correction and PCA. I also show that ignoring phylogeny in preliminary transformations can result in significantly elevated variance and type I error in our statistical estimators, even if subsequent analysis of the transformed data is performed using phylogenetic methods. This means that ignoring phylogeny during preliminary data transformations can possibly lead to spurious results in phylogenetic statistical analyses of species data.
editionReceived February 25, 2009Accepted July 21, 2009
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subjectAnalysis ; Biological taxonomies ; Brief Communication ; BRIEF COMMUNICATIONS ; Cladistic analysis ; Comparative studies ; Correlations ; Covariance matrices ; Data transformation ; Eigenvectors ; Evolution ; Evolution & development ; Evolutionary biology ; evolutionary regression ; least squares ; Least-Squares Analysis ; Linear regression ; Matrices ; Nonnative species ; PCA ; phylogenetic comparative methods ; Phylogenetics ; Phylogeny ; Principal Component Analysis ; Principal components analysis ; Research ; Species Specificity ; Statistical analysis ; Usage
ispartofEvolution, 2009-12, Vol.63 (12), p.3258-3268
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abstractPhylogenetic methods for the analysis of species data are widely used in evolutionary studies. However, preliminary data transformations and data reduction procedures (such as a size-correction and principal components analysis, PCA) are often performed without first correcting for nonindependence among the observations for species. In the present short comment and attached R and MATLAB code, I provide an overview of statistically correct procedures for phylogenetic size-correction and PCA. I also show that ignoring phylogeny in preliminary transformations can result in significantly elevated variance and type I error in our statistical estimators, even if subsequent analysis of the transformed data is performed using phylogenetic methods. This means that ignoring phylogeny during preliminary data transformations can possibly lead to spurious results in phylogenetic statistical analyses of species data.
copMalden, USA
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pmid19663993
doi10.1111/j.1558-5646.2009.00804.x
tpages11
editionReceived February 25, 2009Accepted July 21, 2009