Glm function

rms Version of glm

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.

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

Arguments

  • formula, family, data, weights, subset, na.action, start, offset, control, model, method, x, y, contrasts: see stats::glm(); for print x is the result of Glm
  • ...: ignored

Returns

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

Details

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".

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'))

See Also

stats::glm(),Hmisc::GiniMd(), prModFit(), stats::residuals.glm

  • Maintainer: Frank E Harrell Jr
  • License: GPL (>= 2)
  • Last published: 2025-01-17