R: rms Version of glm

Glm {rms}

R Documentation

rms Version of glm

Description

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.

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 class 'Glm'
print(x, digits=4, coefs=TRUE, latex=FALSE,
title='General Linear Model', ...)

## S3 method for class 'Glm'
residuals(object, ...)

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` or passed to `residuals.glm` from `residuals.Glm`
`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.
`latex`	a logical value indicating whether information should be formatted as plain text or as LaTeX markup
`title`	a character string title to be passed to `prModFit`
`object`	a fit object created by `Glm`

Value

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

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'))