So that a bit lower than the 77 above but
implies that 42,207 would be needed.
--
David.
>
> Thanks a lot everybody again for your suggestions,
> if anybody has other comments, they are always welcome.
>
> Best,
>
> Giulio
>
>
> > Subject: Re: [R] Sample size c
ybody again for your suggestions,
if anybody has other comments, they are always welcome.
Best,
Giulio
> Subject: Re: [R] Sample size calculation for differences between two very
> small proportions (Fisher's exact test or others)?
> From: marc_schwa...@me.com
> Date: Mon, 8 Nov
Hi,
I don't have access to the article, but must presume that they are doing
something "radically different" if you are "only" getting a total sample size
of 20,000. Or is that 20,000 per arm?
Using the G*Power app that Mitchell references below (which I have used
previously, since they have a
On Nov 8, 2010, at 11:16 AM, Mitchell Maltenfort wrote:
Not with R,
Really?
require(sos)
findFn("power exact test")
found 54 matches; retrieving 3 pages
2 3
These look on point:
http://finzi.psych.upenn.edu/R/library/statmod/html/power.html
http://finzi.psych.upenn.edu/R/library/binom/htm
Not with R, but look for G*Power3, a free tool for power calc,
includes FIsher's test.
http://www.psycho.uni-duesseldorf.de/abteilungen/aap/gpower3
On Mon, Nov 8, 2010 at 10:52 AM, Giulio Di Giovanni
wrote:
>
>
> Hi,
> I'm try to compute the minimum sample size needed to have at least an 80% of
Hi,
I'm try to compute the minimum sample size needed to have at least an 80% of
power, with alpha=0.05. The problem is that empirical proportions are really
small: 0.00154 in one case and 0.00234. These are the estimated failure
proportion of two medical treatments.
Thomas and Conlon (1992)
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