ScheffeTest(x, ...)
## S3 method for class 'aov':
ScheffeTest(x, which = NULL, contrasts = NULL,
conf.level = 0.95, ...)
## S3 method for class 'default':
ScheffeTest(x, g = NULL, which = NULL,
contrasts = NULL, conf.level = 0.95, ...)
aov
fit, when g is left to NULL
or a response variable to be evalutated by g (which mustn't be NULL
then).r
is the number of factor levels and c
the number of contrasts. Each column must contain a full contrast ("sum") adding up to 0. Note that the argument wh
c("PostHocTest")
, with one component for each term requested in which
. Each component is a matrix with columns diff
giving the difference in the observed means, lwr.ci
giving the lower end point of the interval, upr.ci
giving the upper end point and pval
giving the p-value after adjustment for the multiple comparisons.
There are print and plot methods for class "PostHocTest"
. The plot method does not accept xlab
, ylab
or main
arguments and creates its own values for each plot.pairwise.t.test
, TukeyHSD
fm1 <- aov(breaks ~ wool + tension, data = warpbreaks)
ScheffeTest(x=fm1)
ScheffeTest(x=fm1, which="tension")
TukeyHSD(fm1)
# some special contrasts
y <- c(7,33,26,27,21,6,14,19,6,11,11,18,14,18,19,14,9,12,6,
24,7,10,1,10,42,25,8,28,30,22,17,32,28,6,1,15,9,15,
2,37,13,18,23,1,3,4,6,2)
group <- factor(c(1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,3,3,3,3,3,
3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6))
r.aov <- aov(y ~ group)
ScheffeTest(r.aov, contrasts=matrix( c(1,-0.5,-0.5,0,0,0,
0,0,0,1,-0.5,-0.5), ncol=2) )
# just p-values:
ScheffeTest(r.aov, conf.level=NA)
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