Glm

0th

Percentile

rms Version of glm

This function saves rms attributes with the fit object so that anova.rms, Predict, etc. can be used just as with ols and other fits. No validate or calibrate methods exist for Glm though.

Keywords
models, regression
Usage
Glm(formula, family = gaussian, data = list(), weights = NULL, subset =
NULL, na.action = na.fail, start = NULL, offset = NULL, control =
glm.control(...), model = TRUE, method = "glm.fit", x = FALSE, y = TRUE,
contrasts = NULL, ...)

## S3 method for class 'Glm': print(x, digits=4, \dots)

Arguments
formula
family
data
weights
subset
na.action
start
offset
control
model
method
x
y
contrasts
see glm; for print, x is the result of Glm
...
ignored for print
digits
number of significant digits to print
Value

  • a fit object like that produced by glm but with rms attributes and a class of "rms", "Glm", and "glm" or "glm.null".

See Also

glm,rms

Aliases
  • Glm
  • print.Glm
Examples
## Dobson (1990) Page 93: Randomized Controlled Trial :
counts <- c(18,17,15,20,10,20,25,13,12)
outcome <- gl(3,1,9)
treatment <- gl(3,3)
f <- glm(counts ~ outcome + treatment, family=poisson())
f
anova(f)
summary(f)
f <- Glm(counts ~ outcome + treatment, family=poisson())
# could have had rcs( ) etc. if there were continuous predictors
f
anova(f)
summary(f, outcome=c('1','2','3'), treatment=c('1','2','3'))
Documentation reproduced from package rms, version 2.0-2, License: GPL (>= 2)

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