View source: R/integration.Vrel.r
| integration.Vrel | R Documentation | 
Function quantifies the morphological integration in a set of traits
integration.Vrel(A, phy = NULL)
| A | A 3D array (p x k x n) containing Procrustes shape variables for all specimens, or a matrix (n x variables) | 
| phy | A phylogenetic tree of class = "phylo" - see  | 
The function quantifies the strength of morphological integration in a set of variables. Here the set of traits are treated as a single unit, and the overall degree of covariation in them is quantified using the relative eigenvalue index: Vrel (Pavlicev et al. 2009). Following Conaway and Adams (2022), only the non-trivial dimensions of variation are used in the calculation of Vrel. The measure is then converted to an effect size (Z-score), based on the procedures in Conaway and Adams (2022). These may be used in subsequent comparisons of the strength of integration across datasets. Input for the analysis may be a 3D array of Procrustes coordinates, of a matrix of variables. If the observations are species related by a phylogeny, the phylogeny may also be included.
Objects of class "rel.eig" from integration.Vrel return a list of the following:
| Re.obs | The observed relative eigenvalue index (Vrel). | 
| Z.obs | The associated Z-score, which represents the effect size of Vrel. | 
| ZR | The effect size translated to a positive scale (so that no integration is ZR = 0). | 
| ZR.var | The variance of the effect size. | 
Dean Adams
Pavlicev, M., J. M. Cheverud, and G. P. Wagner. 2009. Measuring morphological integration using eigenvalue variance. Evolutionary Biology 36:157-170.
Conaway, M.A., and D.C. Adams. 2022. An effect size for comparing the strength of morphological integration across studies. Evolution. 76: 2244-2259.
compare.ZVrel
## Not run: 
data(plethodon) 
Y.gpa <- gpagen(plethodon$land)    #GPA-alignment    
integration.Vrel(Y.gpa$coords)
## End(Not run)
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