plot.hov: Homogeneity of Variance Plot

Description

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. The plot.hov function graphs the components of the Brown and Forsyth test statistic.

Usage

plot.hov(x, data = sys.parent(), method = "bf",  ## x is a formula
         transpose.in = TRUE, ...)

## users will normally use the formula above and will not call the
## method directly.
plot.hov.bf(x, group,  ## x is the response variable
            y.name = deparse(substitute(x)),
            group.name = deparse(substitute(group)),
            transpose.in = TRUE, ...)

## users will normally use the formula above and will not call the
## panel function directly.
panel.hov(..., transpose = TRUE)

Arguments

Value

"trellis" object with three panels containing boxplots for each group: The observed data "y", the data with the median subtracted "y-med(y)", and the absolute deviations from the median "abs(y-med(y))" The Brown and Forsyth test statistic is the $F$ statistic resulting from an ordinary one-way analysis of variance on the data points in the third panel.

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

Run this code

turkey <- read.table(hh("datasets/turkey.dat"), header=FALSE)
names(turkey) <- c("diet","wt.gain")
turkey$diet <- factor(turkey$diet,
                      labels=c("control","A1","A2","B1","B2"))

hov(wt.gain ~ diet, data=turkey)
plot.hov(wt.gain ~ diet, data=turkey)