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st: sample size for multiple group study


From   Scott Strassels <scotts1@mail.utexas.edu>
To   statalist@hsphsun2.harvard.edu
Subject   st: sample size for multiple group study
Date   Wed, 26 Dec 2007 14:48:42 -0600

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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