# stat.anova

##### GLM Anova Statistics

This is a utility function, used in `lm`

and
`glm`

methods for `anova(..., test != NULL)`

and should not be used by the average user.

- Keywords
- models, regression

##### Usage

```
stat.anova(table, test = c("Rao","LRT", "Chisq", "F", "Cp"),
scale, df.scale, n)
```

##### Arguments

- table
- numeric matrix as results from
`anova.glm(..., test = NULL)`

. - test
- a character string, partially matching one of
`"Rao"`

,`"LRT"`

,`"Chisq"`

,`"F"`

or`"Cp"`

. - scale
- a residual mean square or other scale estimate to be used as the denominator in an F test.
- df.scale
- degrees of freedom corresponding to
`scale`

. - n
- number of observations.

##### Value

- A matrix which is the original
`table`

, augmented by a column of test statistics, depending on the`test`

argument.

##### References

Hastie, T. J. and Pregibon, D. (1992)
*Generalized linear models.*
Chapter 6 of *Statistical Models in S*
eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole.

##### See Also

##### Examples

`library(stats)`

```
##-- Continued from '?glm':
utils::example("glm", echo = FALSE)
print(ag <- anova(glm.D93))
stat.anova(ag$table, test = "Cp",
scale = sum(resid(glm.D93, "pearson")^2)/4,
df.scale = 4, n = 9)
```

*Documentation reproduced from package stats, version 3.3, License: Part of R 3.3*

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