logdiag: Diagnostic Measures of Certain Regression Estimates

In HoRM: Supplemental Functions and Datasets for "Handbook of Regression Methods"

Description

A function for computing various residual-based and influence-based quantities from a linear regression fit using lm or a generalized linear regression fit using glm.

Usage

logdiag(out)

Arguments

out	An object of class lm or glm.

Value

logdiag returns a data frame with the following columns:

r.i	The raw residuals.
p.i	The Pearson residuals.
d.i	The deviance residuals.
stud.r.i	The Studentized raw residuals.
stud.p.i	The Studentized Pearson residuals.
stud.d.i	The Studentized deviance residuals.
h.ii	The leverage values.
C.i	The Cook's distance value.
C.i.bar	The average Cook's distance value when omitting observation i.
DFDEV	The change in the deviance statistic when omitting observation i.
DFCHI	The change in the Pearson's chi-square statistic when omitting observation i.
fit	The estimated response (fitted) values.

References

Young, D. S. (2017), Handbook of Regression Methods, CRC Press.

See Also

glm, lm

Examples

 
## Diagnostic summaries for the logistic regression fit to the
## menarche dataset.

data(menarche, package = "MASS")

glm.out = glm(cbind(Menarche, Total - Menarche) ~ Age, 
              family = binomial, data = menarche)
logdiag(glm.out)

HoRM documentation built on March 11, 2021, 9:07 a.m.