CookD: Calculates and plots Cook's distances for a Linear (Mixed)...

In predictmeans: Predicted Means for Linear and Semiparametric Models

Calculates and plots Cook's distances for a Linear (Mixed) Model

Description

This function produces Cook's distance plots for a linear model obtained from functions aov, lm, glm, gls, lme, or lmer.

Usage

CookD(model, group=NULL, plot=TRUE, idn=3, newwd=TRUE)

Arguments

model	Model object returned by aov, lm, glm, gls, lme, and lmer.
group	Name (in "quotes") for indicating how observations are deleted for Cook's distance calculation. If group!=NULL then deletions will be along levels of group variable, otherwise, will be along individual observations.
plot	A logical variable; if it is true, a plot of Cook's distance will be presented. The default is TRUE.
idn	An integer indicating the number of top Cook's distances to be labelled in the plot. The default value is 3.
newwd	A logical variable to indicate whether to print graph in a new window. The default value is TRUE.

Author(s)

Dongwen Luo, Siva Ganesh and John Koolaard

Examples

library(predictmeans)
Oats$nitro <- factor(Oats$nitro)
fm <- lme(yield ~ nitro*Variety, random=~1|Block/Variety, data=Oats)
# library(lme4)
# fm <- lmer(yield ~ nitro*Variety+(1|Block/Variety), data=Oats)
CookD(fm)

predictmeans documentation built on May 29, 2024, 9:49 a.m.