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Adjusting confidence intervals for paired t-tests of multiple endpoints
3 messages · Erich Studerus, Dieter Menne, Erich Studerus, Psychiatrische Uni-Klinik
1 day later
Erich Studerus <erich.studerus <at> bli.uzh.ch> writes:
Dear R-users, In a randomized placebo-controlled within-subject design, subjects recieved a psycho-active drug and placebo. Subjects filled out a questionnaire containing 15 scales on four different time points after drug administration. In order to detect drug effects on each time point, I compared scale values between placebo and drug for all time conditions and scales, which sums up to 4*15=60 comparisons.
....
Now, I want to adjust the confidence intervals for multiple comparisons.
For simple cases, see p.adjust or TukeyHSD (more limited). For complex cases, see simint and friends in package multcomp. Dieter
Thanks, but as far as I know the multcomp package and the tukeyHSD function can only handle one dependent variable, whereas I have 60 dependent variables. Regards, Erich On Sat, 28 Feb 2009 17:41:11 +0000 (UTC)
Dieter Menne <dieter.menne at menne-biomed.de> wrote:
Erich Studerus <erich.studerus <at> bli.uzh.ch> writes:
Dear R-users, In a randomized placebo-controlled within-subject design, subjects recieved a psycho-active drug and placebo. Subjects filled out a questionnaire containing 15 scales on four different time points after drug administration. In order to detect drug effects on each time point, I compared scale values between placebo and drug for all time conditions and scales, which sums up to 4*15=60 comparisons.
....
Now, I want to adjust the confidence intervals for multiple comparisons.
For simple cases, see p.adjust or TukeyHSD (more limited). For complex cases, see simint and friends in package multcomp. Dieter
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