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Cited by 931Evolution and Paleontology StudiesMorphological variations and asymmetryGenomics and Phylogenetic Studies

Phylogenetic signal and linear regression on species data: Phylogenetic regression

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Revell, Liam J.·2010·Methods in Ecology and Evolution
DOI 10.1111/j.2041-210x.2010.00044.x
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Abstract

1. A common procedure in the regression analysis of interspecies data is to first test the independent and dependent variables X and Y for phylogenetic signal, and then use the presence of signal in one or both traits to justify regression analysis using phylogenetic methods such as independent contrasts or phylogenetic generalized least squares. 2. This is incorrect, because phylogenetic regression assumes that the residual error in the regression model (not in the original traits) is distributed according to a multivariate normal distribution with variances and covariances proportional to the historical relations of the species in the sample. 3. Here, I examine the consequences of justifying and applying the phylogenetic regression incorrectly. I find that when used improperly the phylogenetic regression can have poor statistical performance, even under some circumstances in which the type I error rate of the method is not inflated over its nominal level. 4. I also find, however, that when tests of phylogenetic signal in phylogenetic regression are applied properly, and in particular when phylogenetic signal in the residual error is simultaneously estimated with the regression parameters, the phylogenetic regression outperforms equivalent non-phylogenetic procedures.

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  • The problem of species non-independence still arises when examining evolutionary labile traits that evolve very fast or are the product of very recent events.

    “The problem of species non-independence still arises when examining evolutionary labile traits that evolve very fast or are the product of very recent events.”

    From A phylogenetic approach to comparative genomics (2025) · cites this paper as [44]

    The Introduction says species are statistically non-independent because of shared history and explains that phylogenetic dependence in regression residuals can remain even when the traits themselves show very low phylogenetic signal. That supports the general caution, but the paper does not specifically establish it for rapidly evolving traits or traits produced by very recent events. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

  • A total lack of phylogenetic signal is at one end of a spectrum and not a reason not to avoid phylogenetic comparative methods.

    “A total lack of phylogenetic signal is at one end of a spectrum and not a reason not to avoid phylogenetic comparative methods44,54–56.”

    From A phylogenetic approach to comparative genomics (2025) · cites this paper as [44]

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Authors
Revell, L. J.
Affiliations
Duke University (US)
Corresponding author
Revell, Liam J.
ORCID
Revell, Liam J.
Venue
Methods in Ecology and Evolution
Publisher
Wiley
Published
2010-06-30
Volume
1
Issue
4
Pages
319-329
ISSN
2041-210X (ISSN-L)
DOI
10.1111/j.2041-210x.2010.00044.x
OpenAlex
W1523391828
Cited by
931
References
2
Citations by year
2026: 49 · 2025: 58 · 2024: 60 · 2023: 60 · 2022: 54 · 2021: 100 · 2020: 68 · 2019: 68 · 2018: 59 · 2017: 54 · 2016: 66 · 2015: 74 · 2014: 66 · 2013: 43 · 2012: 38
FWCI
19.48
Type
journal article
Language
en
Open access
Licence
Locations
Methods in Ecology and Evolution (publishedVersion)
Funders
  • National Science Foundation (0423641)
  • National Evolutionary Synthesis Center (NSF EF-0423641, #EF-0423641)
  • Division of Emerging Frontiers (EF-04-23641, 0423641)
Topics
  • Physical Sciences › Earth and Planetary Sciences › Paleontology › Evolution and Paleontology Studies
  • Physical Sciences › Mathematics › Geometry and Topology › Morphological variations and asymmetry
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords
phylogenetic signal, phylogenetic regression, phylogenetic generalized least squares, independent contrasts, type I error rate, statistical power, phylogenetic comparative analysis

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