ScheffeTest {DescTools}  R Documentation 
Scheffe Test for Pairwise and Otherwise Comparisons
Description
Scheffe's method applies to the set of estimates of all possible contrasts among the factor level means, not just the pairwise differences considered by Tukey's method.
Usage
ScheffeTest(x, ...)
## S3 method for class 'formula'
ScheffeTest(formula, data, subset, na.action, ...)
## S3 method for class 'aov'
ScheffeTest(x, which = NULL, contrasts = NULL,
conf.level = 0.95, ...)
## Default S3 method:
ScheffeTest(x, g = NULL, which = NULL,
contrasts = NULL, conf.level = 0.95, ...)
Arguments
x 
either a fitted model object, usually an 
g 
the grouping variable. 
which 
character vector listing terms in the fitted model for which the intervals should be calculated. Defaults to all the terms. 
contrasts 
a 
conf.level 
numeric value between zero and one giving the confidence level to use. If this is set to NA, just a matrix with the pvalues will be returned. 
formula 
a formula of the form 
data 
an optional matrix or data frame (or similar: see

subset 
an optional vector specifying a subset of observations to be used. 
na.action 
a function which indicates what should happen when
the data contain 
... 
further arguments, currently not used. 
Value
A list of classes 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 pvalue 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.
Author(s)
Andri Signorell <andri@signorell.net>
References
Robert O. Kuehl, Steel R. (2000) Design of experiments. Duxbury
Steel R.G.D., Torrie J.H., Dickey, D.A. (1997) Principles and Procedures of Statistics, A Biometrical Approach. McGrawHill
See Also
Examples
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 pvalues:
ScheffeTest(r.aov, conf.level=NA)