hov

From HH v3.1-39 by Richard Heiberger

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 = sys.parent(), 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 (2004b). Statistical Analysis and Data Display: An Intermediate Course with Examples in S-Plus, R, and SAS. Springer Texts in Statistics. Springer. ISBN 0-387-40270-5.

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

Examples

# NOT RUN {
data(turkey)

hov(wt.gain ~ diet, data=turkey)
hovPlot(wt.gain ~ diet, data=turkey)
# }

Documentation reproduced from package HH, version 3.1-39, License: GPL (>= 2)

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