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Re: st: Sample size calculation


From   <slaowattana@pol.net>
To   <nshephard@gmail.com>
Subject   Re: st: Sample size calculation
Date   Wed, 26 Oct 2005 15:34:52 -0400 (EDT)

Thanks. We plan to do the experiment in humans and they will be treated
with Rebif. The expected size of difference is 2 SD (to be clinically
significant) but my understanding is that to be able to calculate the
sample size (alpha = 0.05, beta = 0.20), we have to know estimated mean
and SD? Is this not true?

> On 10/26/05, slaowattana@pol.net <slaowattana@pol.net> wrote:
>> We are planning to measure some cytokines in patients with MS
>> comparing between a group with treatment and control, but there have
>> not been literatures regarding these measurements, so we do not have
>> an estimated mean and standard deviation. Is there a way to estimate a
>> sample size? (our IRB really wants to see sample size estimate.)
>> Thanks.
>>
>> We are planning to measure some cytokines in patients with MS
>> comparing between a group with treatment and control, but there have
>> not been literatures regarding these measurements, so we do not have
>> an estimated mean and standard deviation. Is there a way to estimate a
>> sample size? (our IRB really wants to see sample size estimate.)
>
> Probably not the answer/help your looking for, but....
>
> Sample size is dependent on a number of factors.  The significance level
> at which you wish to detect differences (termed alpha), the
> power you wish your study to have (termed beta), and the size of
> effect you are expecting to see.  The type of test you are to perform
> also has an influence, and from the mention of mean and sd, its a fair
> guess your likely to use a t-test (providing the assumptions are met).
>
> You have not mentioned any of these quantities, and only you can
> determine appropriate alpha and beta levels (and tests) that are
> acceptable to your study design.  You will have to decide on these prior
> to performing any sample size calculations.
>
> You do however indicate that to your knowledge there is no literature
> regarding the measurements you wish to take.  I'm not an expert on MS,
> but since it is an autoimmune disease I believe cytokine activity is one
> facet that is commonly investigated.
>
> A search on PubMed indicates that there are 96 articles with the both
> the terms "cytokine" and "multiple sclerosis" in the title.  Obviously
> these may not be the cytokines your intersted in but they should help
> provide some information.
>
> (To duplicate this seach got to http://wwwncbi.nlm.nih.gov/, select
> PubMed as the database to search, and enter the search term 'cytokine
> multiple sclerosis' and hit return.  Now click on the 'Limits' tab and
> in the first pull-down box select 'Title' to restrict the search to
> artciles with the terms in their titles).
>
> You may also benefit from reading the OMIM (Online Mendelian
> Inherithance in Man) entry for MS which can also be accessed via NCBI
>
> However, the question still remains as to how much difference the
> treatment is likely to make to the mean, and that is presumably why you
> are carrying out the experiment.  You don't state the organism, but I'll
> guess that your working with humans.  Is the treatment with a drug?  If
> so it is highly likely to have been tested in animal models before being
> trialed in humans, and these may inform you about the expected
> difference.  What sort of effects have been reported for
> other treatment effects/cytokines in MS?
>
> If there is absolutely no prior information to inform on the expected
> size of effect then you can not possibly determine an appropriate
> sample size, and your best approach would be to determine sample sizes
> for a range of effects, see how these compare to your available
> resources (money).  That way you could say to the IRB (Independent
> Review Board?) that with a sample size of N, you would have X% power to
> detect an effect of size Y at a significance level of alpha.  You could
> even show them figures of your calculations which show that
> larger sample sizes would allow you to detect smaller differences in
> effect.
>
> HTH's
>
> Neil



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