stat.anova
Add Statistics Columns to an Anova Table
Description
Creates a new anova table with appropriate statistics columns.
Usage
stat.anova(table, test = c("Chisq", "F", "Cp"), scale, df.scale, n, familyName = "gaussian")
Arguments
| table |
an anova object
|
| test |
what test to use; the choices are "Chisq", "F", or "Cp"
|
| scale |
an estimate of scale, needed for all test.
|
| df.scale |
the (residual) degrees of freedom associated with the scale estimate (as in the denominator of an F-ratio).'
|
| n |
the sample size for the data underlying the anova table.
|
| familyName |
The name of the glm family being used by the object(s) in the anova.
If it is "binomial" or "poisson" and an F-test is requested
then stat.anova will warn that the test is inappropriate (since
there is not an independent estimate of dispersion) and the p-value will
be computed using df2=Inf.
|
Value
a new anova table is returned, with the appropriate statisticscolumns included.
This function relies on the names of the columns being in a small subset of allowed names.
It is mainly intended as a support function for anova(), step(), add1()
or drop1().
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
numdead <- c(1, 4, 9, 13, 18, 20, 0, 2, 6, 10, 12, 16)
sex <- factor(rep(c("M", "F"), c(6, 6)))
ldose <- rep(0:5, 2)
SF <- cbind(numdead, numalive = 20 - numdead)
budworm.lg.anv <- anova(glm(SF ~ sex*ldose, family = binomial))
stat.anova(budworm.lg.anv, test = "F", scale = 0.8, df.scale = 1.2, n = 12)
stat.anova(budworm.lg.anv, test = "Cp", scale = 0.8, df.scale = 1.2, n = 12)
stat.anova(budworm.lg.anv, test = "Chisq", scale = 0.8, df.scale = 1.2, n = 12)
stat.anova(budworm.lg.anv, test = "Chisq", scale = 1.0, df.scale = 1.2, n = 12)