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.

For the print method, format of output is controlled by the user previously running options(prType="lang") where lang is "plain" (the default), "latex", or "html".

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

# S3 method for Glm print(x, digits=4, coefs=TRUE, title='General Linear Model', …)

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

digits

number of significant digits to print

coefs

specify coefs=FALSE to suppress printing the table of model coefficients, standard errors, etc. Specify coefs=n to print only the first n regression coefficients in the model.

title

a character string title to be passed to prModFit

Value

a fit object like that produced by glm but with rms attributes and a class of "rms", "Glm", "glm", and "lm". The g element of the fit object is the \(g\)-index.

See Also

glm,rms,GiniMd, prModFit,residuals.glm

Aliases
  • Glm
  • print.Glm
Examples
# NOT RUN {
## 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 5.1-3.1, License: GPL (>= 2)

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