Phylogenies and the Comparative Method

In the citing paper

“We calculated standardized independent contrasts (FIC: Felsenstein 1985) for each of the above factors (territoriality, shoulder height, body mass, habitat openness and group size) using the PDTREE module (Midford et al. 2005) in Mesquite 2.5 (Maddison & Maddison 2008) to account for shared ancestry.”

In the citing paper

“To test the effects of shared ancestry on trait correlations, we also carried out EMMLi analysis on the phylogenetic independent contrasts (45) of the landmark configurations. This analysis supported the same most likely model and relative strength of correlations within and among modules as the analysis of the raw data did.”

In the citing paper

“Firstly, because of shared phylogenetic descent, species data are likely not to represent statistically independent points.This results in overestimation of degrees of freedom and an increased Type I error rate.”

In the citing paper

“Felsenstein also noted that the problem of nonindependence does not occur if”

In the citing paper

“He then evolved traits according to a BM process along the phylogeny; he recovered a significant regression slope using Ordinary Least Squares (OLS) despite there being no evolutionary covariance between the traits.”

In the citing paper

“As stated above, the IC method is based on the BM model of trait evolution.”

In the citing paper

“This led to the development of numerous methods that take phylogeny into account and control for the non-independence of species16,18,19,33.”

In the citing paper

“The fact that species cannot be considered independent data points was first recognized in the 1970s by evolutionary biologists studying the evolution of life history traits such as sexual dimorphism and home range in primates16,18,30–32.”

In the citing paper

“However, species, genomes and genes cannot be considered as independent data points within statistical tests.”

In the citing paper

“Closely related species tend to be similar because they share genes by common descent, which must be accounted for in analyses.”

In the citing paper

“There is no simple and robust alternative to controlling for phylogeny, and consequently, the best effort possible must be made to take phylogeny into account, to be able to detect real effects and avoid false positives.”

In the citing paper

“Collecting many more data points from the same phylogenetic cluster could increase any bias due to phylogenetic non-independence (Fig. 1)16,18,20.”

In the citing paper

“Instead, controlling for phylogeny can reduce the chance of detecting a significant result that is not real (Type II error or ‘false positive’)18,42.”

In the citing paper

“Controlling for confounding variables such as phylogeny does not reduce statistical power, because such variables should be accounted for before making any estimates of power18,114,115.”

In the citing paper

“Phylogenetic independent contrasts were also calculated from the data to examine scaling relationships while controlling for the effects of phylogenetic relatedness in the data set (59).”

In the citing paper

“With a phylogeny, it becomes possible to examine correlated evolutionary change directly along the branches of the tree, for example with the method of independent contrasts (Felsenstein 1985; Garland et al. 1992; Nunn and Barton 2001). Alternatively, one can use the phylogeny to statistically control for nonindependence in the underlying data, for example by using phylogenetic generalized least”