summary.glam: Summarizing regression models for class 'glam'

In MorphoFun/psa: Phenotypic Selection Analysis tools

Description

summary.glam provides the summary information for class glam, glm or lm. Output is similar to summary, except that an option to apply the Janzen and Stern (1998) correction for logistic regressions is available in summary.glam.

Usage

summary.glam(object, JS = FALSE, dispersion = NULL, correlation = FALSE, symbolic.cor = FALSE, ...)

Arguments

object	Object of the class 'glam'.
JS	Janzen and Stern (1998) correction factor for make logistic regression coefficients congruent with linear regression coefficients for estimating multivariate selection. Default is FALSE. Setting JS = TRUE applies the Janzen and Stern correction factor to the logistic regression coefficients.

Details

Ordinary least-squares (OLS) regressions are used to estimate selection gradients, based on methods outlined by Lande and Arnold (1983). Data with binomial fitness measures have the option of applying the Janzen and Stern (1998) correction factor to make estimates from logistic regressions congruent with those of the OLS method from Lande and Arnold (1983). Quadratic terms have already been coded, so that their regression estimates and standard errors do NOT need to be doubled (Stinchcombe et al. 2008). The code from summary.glam is based on base code base::summary, with modifications to calculate p-values using the regression estimates produced by the Janzen and Stern (1998) modifications.

References

Janzen FJ, Stern HL. 1998. Logistic regression for empirical studies of multivariate selection. Evolution 52(6): 1564-1571. http://www.jstor.org/stable/2411330?seq=1#page_scan_tab_contents

Lande R, Arnold SJ. 1983. The measurement of selection on correlated characters. Evolution 37(6): 1210-1226. http://www.jstor.org/stable/2408842

Stinchcombe JR, Agrawal AF, Hohenlohe PA, Arnold SJ, Blows MW. 2008. Estimating nonlinear selection gradients using quadratic regression coefficients: double or nothing? Evolution 62(9): 2435-2440. http://onlinelibrary.wiley.com/doi/10.1111/j.1558-5646.2008.00449.x/abstract

See Also

glam, summary

Examples

data(BumpusMales)
bm <- glam(BumpusMales[,1], BumpusMales[,3:11])
summary.glam(bm$GL)

MorphoFun/psa documentation built on Nov. 10, 2021, 7:01 a.m.