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...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2009
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/26956
- Acceso en línea:
- https://doi.org/10.1111/j.1558-5646.2009.00804.x
https://repository.urosario.edu.co/handle/10336/26956
- Palabra clave:
- Data transformation
Evolutionary regression
Least squares
Linear regression
PCA
Phylogenetic comparative methods
Principal components analysis
- Rights
- License
- Abierto (Texto Completo)
Summary: | 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. |
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