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Independent contrasts and regression through the origin.
Pierre Legendre1, Yves Desdevises
1Département de Sciences Biologiques, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Québec, Canada H3C 3J7. pierre.legendre@umontreal.ca
Regression through the origin is crucial for phylogenetic comparative analysis using independent contrasts. New permutation tests are introduced and validated through simulations, offering robust methods for analyzing evolutionary data.
Area of Science:
- Phylogenetics
- Evolutionary Biology
- Statistical Modeling
Background:
- Phylogeneticists commonly use regression through the origin for analyzing comparative data with independent contrasts.
- The theoretical underpinnings and necessity of this method for such data have been re-examined.
Purpose of the Study:
- To revisit the rationale for using regression through the origin in phylogenetic comparative analysis.
- To develop and evaluate permutation tests for regression coefficients and coefficient of determination in this context.
Main Methods:
- Formulation of permutation tests for regression through the origin.
- Simulations under two data generation models (regression models I and II) to assess type I error and power.
- Investigation of two permutation strategies: permuting response variable (y) and permuting residuals.
- Application to two biological examples: fish parasite non-specificity and mammal parasite richness.
Main Results:
- Parametric and permutation tests are reliable for normally distributed errors, common in independent contrast studies.
- Permutation of the response variable (y) is recommended for highly asymmetric error distributions.
- Parametric tests are suitable when extreme values are present in covariables.
Conclusions:
- The study validates and extends statistical methods for phylogenetic comparative analysis.
- Provides guidance on selecting appropriate statistical tests based on error distribution and data characteristics.
- Demonstrates the utility of these methods with real-world biological data on host-parasite relationships.
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