# Glm

From rms v2.0-2
by Frank E Harrell Jr

##### 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

##### 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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