Many thanks for your helpful suggestions and
the detailed feedback!
We will have a look at your suggestions before buying
the (quite expensive) PASS software.
-Udo
Quoting Tobias Verbeke <tobias.verb...@openanalytics.be>:
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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