[R] Comprehensive power analysis/sample size package in R?

Tobias Verbeke tobias.verbeke at openanalytics.be
Wed Jul 15 23:12:06 CEST 2009


Frank E Harrell Jr wrote:
> Greg Snow wrote:
>> I don't know of a single package that is comparable to PASS, but the R 
>> system itself is the most comprehensive tool available for power and 
>> sample size computations.
>>
>> For the simple cases you already found the pwr package, there are also 
>> some power functions in the stats package and in some other packages 
>> and these will be comparable to the equivalent (or possibly better) 
>> than the simple ones in PASS.

FYI, Russ Lenth is porting his piface package

http://www.cs.uiowa.edu/~rlenth/Power/

to R

http://r-forge.r-project.org/projects/piface/

Best,
Tobias

>> When things get a bit more complicated then there are a few different 
>> options for what to do next:
>>
>> 1. Don't provide anything for the more complicated cases.
>> 2. Provide a minimal set of routines for more complicated cases based 
>> on programmer assumptions rather than information from someone 
>> familiar with the source of the data (assumptions often hidden).
>> 3. Provide many different routines encompassing every alternative set 
>> of assumptions that the programmer can think of forcing the user to 
>> sort through all the options to find the one that is closest (and 
>> maybe the same) as what they want to do.
>> 4  Provide a full programming language so that the people familiar 
>> with the question(s) of interest and the source of the data can 
>> explicitly spell out the desired analysis and assumptions.
>> 5. possible others, but I can't think of any.
>>
>> It looks like PASS uses option 3, giving many different routines that 
>> any one user in only likely to use a few of.
>>
>> R is option 4.  You can decide what assumptions you want to make about 
>> the data (and later change any of those assumptions), decide how you 
>> plan to analyze the data, then by simulation you can work out the 
>> power/sample size/etc. knowing exactly what assumptions went into the 
>> analysis.
>>
> 
> As one example of what Greg is talking about see 
> http://bm2.genes.nig.ac.jp/RGM2/R_current/library/Hmisc/man/spower.html
>




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