R: Design Version of glm

glmD {Design}

R Documentation

Design Version of glm

Description

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

Usage

glmD(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 'glmD':
print(x, digits=4, ...)

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 `glmD`
`...`	ignored for `print`
`digits`	number of significant digits to print

Value

a fit object like that produced by glm but with Design attributes and a class of "Design", "glmD", and "glm" or "glm.null".

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 <- glmD(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'))