As Jeph says, it depends on what kind of non-normality you are going to
assume. A common alternative is the lognormal assumption, although I
don't know if that is what you want to use in your case. If we think the
data are lognormal within groups, then we test for detectable geometric
mean ratios, not detectable arithmetic mean differences.
You might like to read my paper on the -powercal- package (Newson,
2004), which discusses power calculations for a wide range of non-normal
cases, including lognormal geometric mean ratios, and even detectable
levels of Somers' D when rank methods are used. The -powercal- package
can be downloaded from SSC using the -ssc- command in Stata. If you do
not have access to The Stata Journal, then you can download a
pre-publication draft from my website (see my signature below).
I hope this helps.
Best wishes
Roger
References
Newson R. Generalized power calculations for generalized linear models
and more. The Stata Journal 2004; 4(4): 379-401. Download
pre-publication draft from my website at
www.imperial.ac.uk/nhli/r.newson/
Roger Newson
Lecturer in Medical Statistics
Respiratory Epidemiology and Public Health Group
National Heart and Lung Institute
Imperial College London
Royal Brompton campus
Room 33, Emmanuel Kaye Building
1B Manresa Road
London SW3 6LR
UNITED KINGDOM
Tel: +44 (0)20 7352 8121 ext 3381
Fax: +44 (0)20 7351 8322
Email: [email protected]
www.imperial.ac.uk/nhli/r.newson/
Opinions expressed are those of the author, not of the institution.
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Di Stefano,
Paola
Sent: 10 November 2006 16:47
To: [email protected]
Subject: st: Samspi non normality?
Dear all,
I'm trying to estimate a sample size for two-sample comparison of means
using the command sampsi.
The study is to test for a difference in effectiveness of 0.5 between
two groups, assuming a sd(1.4)
Is there any way to change the normality assumption? Is there another
way to estimate sample size?
Thanks
Paola
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