Sven-Erik Johansson posted: "Is there any option or STB available for pairwise
comparisons in an oneway ANOVA with repeated measurements?"
George Hoffman suggested prcomp, but it seems to assume independent samples, not
paired observations.
I think that the most commonly recommended way (see, for example,
http://sobek.colorado.edu/LAB/STATS/SPSS/spss195.html or
http://sobek.colorado.edu/LAB/STATS/SPSS/spss395.html passim) is to perform paired
Student's t-tests, since this assures that the correct covariance is used for each
comparison, something that cannot always be assured with a pooled error term from the
repeated-measures analysis of variance table. Adjustments for multiple testing can
then be done with -_mtest- (see -help undocumented-). I've illustrated the technique in
the do-file below using a dataset from B. J. Winer, D. R. Brown and K. M. Michels,
_Statistical Principles in Experimental Design_. Third Edition. (New York: McGraw-Hill,
1991), p. 228. In the illustration, I happen to use Holm's method for multiple
adjustment.
As an alternative, although I'm not sure what advantage there would be over multiple
paired Student's t-tests, Sven-Erik could use -manova- in conjuction with -manovatest,
ytransform()-s with the pairwise contrasts specified in transformation matrixes.
Adjustment for multiplicity would still be in order.
Joseph Coveney
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clear
set more off
infile byte rctime1 byte rctime2 byte rctime3 byte rctime4 using ///
http://www.uni-koeln.de/themen/Statistik/data/winer/win_228.txt
preserve // Displaying the omnibus randomized-blocks ANOVA
generate byte person = _n
reshape long rctime, i(person) j(drug)
anova rctime drug person, repeated(drug) // Note epsilons as index of sphericity
restore // Individual comparisons begins next
matrix A = J(1, 3, 0)
local testno = 0
forvalues i = 1/3 {
local j = `i' + 1
forvalues k = `j'/4 {
quietly ttest rctime`i' = rctime`k'
matrix B = (`i', `k', r(p))
if `testno' == 0 {
matrix A = B
}
else {
matrix A = A \ B
}
local rownamesA = "`rownamesA'" + "testpair`++testno' "
}
}
matrix rownames A = `rownamesA'
matrix colnames A = onedrug otherdrug unadjustp
_mtest adjust A, mtest(holm) pindex(3) append
matrix list r(result)
exit
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