calc.q2n.ratio: Calculate the ratio of fit predictor variables to sample size

In mmodely: Modeling Multivariate Origins Determinants - Evolutionary Lineages in Ecology

Calculate the ratio of fit predictor variables to sample size

Description

The one in ten rule of thumb for model fitting suggest at least 10 fold as many data as parametes fit. This function allows for easily calculating that ratio on model selected PGLS fits.

Usage

calc.q2n.ratio(coefs)

Arguments

coefs

a list of coefficients extracted from fit PGLS models

Value

the ratio of q to n (on average for all extracted fit models)

Examples

data.path <- system.file("extdata","primate-example.data.csv", package="mmodely")
data <- read.csv(data.path, row.names=1)
pvs <- names(data[3:5])
data$gn_sp <- rownames(data)

tree.path <- system.file("extdata","primate-springer.2012.tre", package="mmodely")
phyl <- ape::read.tree(tree.path)[[5]]

comp <- comp.data(phylo=phyl, df=data)

mods <- get.model.combos(predictor.vars=pvs, outcome.var='OC', min.q=2)

PGLSi <- pgls.iter(models=mods, phylo=phyl, df=data, k=1,l=1,d=1) 

coefs.objs <- get.pgls.coefs(PGLSi$fits, est='Estimate')

calc.q2n.ratio(coefs.objs)

mmodely documentation built on May 31, 2023, 6:47 p.m.