R help - Sep 2009 - No parametric methods

Hello I am interested  in finding out a method of power analysis (effect
size and sample size calculation ) using R in non parametric methods?

I am running  R  2.8.1 running on linux open SUSE

Any libraries or documentation , I was not bale to google up any.

Thanks in Advance,

Ben-Ari Alon, MD
University of Pittsburgh.

	[[alternative HTML version deleted]]

On Sep 22, 2009, at 11:35 AM, Alon Ben-Ari wrote:
> Hello I am interested  in finding out a method of power analysis  
> (effect
> size and sample size calculation ) using R in non parametric methods?
>
> I am running  R  2.8.1 running on linux open SUSE
>
> Any libraries or documentation , I was not bale to google up any.
I suspect that the reason no one has yet offered ideas is that the  
question is a bit (well, OK, ... extremely) vague. You have not  
described in any detail what the question might be. That said there  
are several functions for power calculations in the context of  
survival analysis in the Hmisc package, some of which probably reduce  
to simple cases (such as the Wilcoxon rank sum test) in the absence of  
censoring.

-- 

David Winsemius, MD
Heritage Laboratories
West Hartford, CT

For power studies you need to think about what the data will look like under the
alternative hypothesis.  Is the data shifted over a certain amount? (the most
common assumption), or scaled? Or both? Or a completely different shape? Etc.

My preferred method for power studies in this case is to use simulation:

1. decide what you data is likely to look like (based on previous data,
assumptions, ...)
2. decide how you will analyze the data (possibly iterate between 1 and 2)
3. write a function that simulates data under the alternative hypothesis, then
analyzes it (using decisions from 1 and 2) and returns the p-value or test
statistic.  The function will often have a parameter for sample size and a
parameter for the size of the difference (scale, etc.).
4. use the replicate function to run your function a bunch of times.
5. the proportion of times that the above gives significant results is an
estimate of the power.

Hope this helps,  

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Alon Ben-Ari
> Sent: Tuesday, September 22, 2009 9:35 AM
> To: r-help at r-project.org
> Subject: [R] No parametric methods
> 
> Hello I am interested  in finding out a method of power analysis
> (effect
> size and sample size calculation ) using R in non parametric methods?
> 
> I am running  R  2.8.1 running on linux open SUSE
> 
> Any libraries or documentation , I was not bale to google up any.
> 
> Thanks in Advance,
> 
> Ben-Ari Alon, MD
> University of Pittsburgh.
> 
> 	[[alternative HTML version deleted]]
> 
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