# hov

##### Homogeneity of Variance

Oneway analysis of variance makes the assumption that the variances of the groups are equal. Brown and Forsyth, 1974 present the recommended test of this assumption. The Brown and Forsyth test statistic is the \(F\) statistic resulting from an ordinary one-way analysis of variance on the absolute deviations from the median.

- Keywords
- models

##### Usage

`hov(x, data=NULL, method = "bf") ## x is a formula`## users will normally use the formula above and will not call the
## method directly.
hov.bf(x, group, ## x is the response variable
y.name = deparse(substitute(x)),
group.name = deparse(substitute(group)))

##### Arguments

- x
Formula appropriate for oneway anova in

`hov`

. Response variable in`hov.bf`

.- data
data.frame

- method
Character string defining method. At this time the only recognized method is

`"bf"`

for the Brown--Forsyth method.- group
factor.

- y.name
name of response variable, defaults to variable name in formula.

- group.name
name of factor, defaults to variable name in formula.

##### Value

`"htest"`

object for the hov test.

##### References

Heiberger, Richard M. and Holland, Burt (2015).
*Statistical Analysis and Data Display: An Intermediate Course with Examples in R*.
Second Edition.
Springer-Verlag, New York.
https://www.springer.com/us/book/9781493921218

Brown, M.~B. and Forsyth, A.~B. (1974).
*Robust tests for equality of variances*.
*Journal of the American Statistical Association*, 69:364--367.

##### See Also

##### Examples

```
# NOT RUN {
data(turkey)
hov(wt.gain ~ diet, data=turkey)
hovPlot(wt.gain ~ diet, data=turkey)
# }
```

*Documentation reproduced from package HH, version 3.1-43, License: GPL (>= 2)*