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Bert Gunter
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On Mon, Sep 4, 2017 at 10:31
Hi
In R,how to do sample size calculation for three-way incomplete block
crossover study where within subject residual standard deviation,treatment
difference and power is given.
Thanks in advance.
Regards
Jose
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__
Hi,
I'm trying to determine a sample size calculation for a mock RCT. I want to
compare the event rate (proportion) between two unequal groups.
Thanks!
--
View this message in context:
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Hello Everyone,
I need to perform a sample size calculation using a drop the loser/keep the
winner design. I've been searching for examples of how to do this using R but
haven't found much.
The most promising possibility thus far is an R function called DrpLsrNRst.
This appears in the book
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)
The obvious:
Take a small sample, say 25-50. Get an estimate of your distribution
from that. Then use this to determine how many more (if any)
additional samples you need for desired precision. This latter can
probably easily be done via simulation/bootstrap if you don't want to
specify a paramet
Basically, we have a population of 4,392 documents and we want to find out
the number of patents per document. We don’t want to go through all 4,392
documents, but want a reliable sample size from which to draw inferences. I
feel like this count data will not follow a normal distribution, but more
I would appreciate any help on this problem. I need to perform a sample size
analysis for a study comparing the performances of 2 different methods of
diagnostic classification. Assume that method 1 has an accuracy of p1
against known truths (a reference classification, as multiple categories),
an
ath.ethz.ch
Gesendet: Dienstag, den 26. Mai 2009, 16:43:09 Uhr
Betreff: Re: [R] Sample size calculation proportions with EpiR: Discrepancy to
other calculators
On Tue, 26 May 2009, Chuck Cleland wrote:
> On 5/26/2009 2:53 AM, Karl Knoblick wrote:
>> Hallo!
>>
>> I have done a sam
On Tue, 26 May 2009, Chuck Cleland wrote:
On 5/26/2009 2:53 AM, Karl Knoblick wrote:
Hallo!
I have done a sample size calculation for proportions with EpiR. The input is:
treatment group rate p=0.65
control group rate p=0.50
significance level 0.95
power 0.80
two-sided
ration group 1 and 2: 1.
On 5/26/2009 2:53 AM, Karl Knoblick wrote:
> Hallo!
>
> I have done a sample size calculation for proportions with EpiR. The input is:
> treatment group rate p=0.65
> control group rate p=0.50
> significance level 0.95
> power 0.80
> two-sided
> ration group 1 and 2: 1.0
>
> I have done this in t
Hallo!
I have done a sample size calculation for proportions with EpiR. The input is:
treatment group rate p=0.65
control group rate p=0.50
significance level 0.95
power 0.80
two-sided
ration group 1 and 2: 1.0
I have done this in the following way:
library(epiR)
epi.studysize(treat = 0.65, cont
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