This sounds a lot like a Dunnett test that compares k (=3) treatments to
a control. You can check works on multiple testing such as R. Miller
(an old one) or try googling Dunnett's test.
Tony
Peter A. Lachenbruch
Department of Public Health
Oregon State University
Corvallis, OR 97330
Phone: 541-737-3832
FAX: 541-737-4001
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Scott
Strassels
Sent: Wednesday, December 26, 2007 12:49 PM
To: [email protected]
Subject: st: sample size for multiple group study
Hello,
I have a question about estimating the sample size needed for a 4-arm
(placebo and 3 comparators) clinical study. I've been reading the
Statalist archives, Stata's FAQs, and the sampsi command, but I'm
still a bit confused. I'm running Stata 9.2 on a Mac. Any help or
suggestions would be very much appreciated.
I want to estimate the number of folks needed for a study in which
there are 4 groups, one of which is placebo, and the other 3 are
different drugs. Ideally, I'd like to compare each group to each
other, but the main goal is to compare each drug to the placebo.
There will be one pre-intervention assessment, and one post-
intervention assessment. The outcome is pain intensity, measured on
a 0-10 numeric rating scale. The mean pre-intervention score for
everyone is expected to be 6.0, with an SD = 2.0. The mean post-
intervention scores are expected to be 4.5 (SD 2.0) for people who
receive placebo, and 2.5 (SD 1.5) in each of the other 3 groups. I'd
like the power to be 0.9 and alpha to be 0.05.
From the Stata documentation, it looks like my question is best
addressed by the section on clinical trials with repeated measures,
using a post approach, but I'm unsure how to handle to extra groups,
since the sampsi command assumes two groups, and calculating sample
size by hand is giving me dramatically different (and much larger)
responses--roughly 90 people per group to detect a 3-unit
difference. From a previous study, the correlation between pre-
intervention and post-intervention scores was 0.49.
sampsi 4.5 2.5, sd1(2.0) sd2(1.5) method(post) pre(1) post(1) r01(0.49)
Estimated sample size for two samples with repeated measures
Assumptions:
alpha = 0.0500 (two-sided)
power = 0.9000
m1 = 4.5
m2 = 2.5
sd1 = 2
sd2 = 1.5
n2/n1 = 1.00
number of follow-up measurements = 1
number of baseline measurements = 1
correlation between baseline & follow-up = 0.490
Method: POST
relative efficiency = 1.000
adjustment to sd = 1.000
adjusted sd1 = 2.000
adjusted sd2 = 1.500
Estimated required sample sizes:
n1 = 17
n2 = 17
Thank you,
Scott
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