[R] Power analysis for MANOVA?

[Charles C. Berry]

On Mon, 26 Jan 2009, Adam D. I. Kramer wrote:

>
> On Mon, 26 Jan 2009, Charles C. Berry wrote:
>
>>
>>  If you know what a 'general linear hypothesis test' is see
>>
>>   http://cran.r-project.org/src/contrib/Archive/hpower/hpower_0.1-0.tar.gz
>> 
>
> I do, and am quite interested, however this package will not install on R
> 2.8.1: First, it said that there was no "maintainer" in the description, so
> I added one (figuring that the 1991 date of the package was to blame),
> however it still will not compile:
>
> parmesan:tmp$ sudo R CMD INSTALL hpower/
> * Installing to library '/usr/local/lib/R/library'
> * Installing *source* package 'hpower' ...
> ** R
> ** preparing package for lazy loading
> Error in parse(n = -1, file = file) : unexpected '{' at
> 5: ##
> 6: pfnc_function(q,df1,df2,lm,iprec=c(6)) {
_________^_________

AHA!

That underscore is the old 'assignment' operator - now no longer allowed.

Do a global replace of '_' with ' <- ' in the R/*.R files and it should 
install.

HTH,

Chuck


> Calls: <Anonymous> -> code2LazyLoadDB -> sys.source -> parse
> Execution halted
> ERROR: lazy loading failed for package 'hpower'
> ** Removing '/usr/local/lib/R/library/hpower'
> parmesan:tmp$
>
> ...any tips?
>
> --Adam
>
>>  HTH,
>>
>>  Chuck
>>
>>  On Mon, 26 Jan 2009, Adam D. I. Kramer wrote:
>> 
>> > 
>> >  On Mon, 26 Jan 2009, Stephan Kolassa wrote:
>> > 
>> > >   My (and, judging from previous traffic on R-help about power 
>> > >   analyses,
>> > >   also some other people's) preferred approach is to simply simulate an
>> > >   effect size you would like to detect a couple of thousand times, run 
>> > >   your
>> > >   proposed analysis and look how often you get significance.  In your 
>> > >  simple
>> > >   case, this should be quite easy.
>> > 
>> >  I actually don't have much experience running monte-carlo designs like
>> >  this...so while I'd certainly prefer a bootstrapping method like this 
>> >  one,
>> >  simulating the effect size given my constraints isn't something I've 
>> >  done
>> >  before.
>> > 
>> >  The MANOVA procedure takes 5 dependent variables, and determines what
>> >  combination of the variables best discriminates the two levels of my
>> >  independent variable...then the discrimination rate is represented in 
>> >  the
>> >  statistic (Pillai's V=.00019), which is then tested (F[5,18653] = 0.71). 
>> >  So
>> >  coming up with a set of constraints that would produce V=.00019 given my
>> >  data set doesn't quite sound trivial...so I'll go for the "par" library
>> >  reference mentioned earlier before I try this.  That said, if anyone can
>> >  refer me to a tool that will help me out (or an instruction manual for 
>> >  RNG),
>> >  I'd also be much obliged.
>> > 
>> >  Many thanks,
>> >  Adam
>> > 
>> > 
>> > > 
>> > >   HTH,
>> > >   Stephan
>> > > 
>> > > 
>> > >   Adam D. I. Kramer schrieb:
>> > > >   Hello,
>> > > > >       I have searched and failed for a program or script or method 
>> > > > >       to
>> > > >   conduct a power analysis for a MANOVA. My interest is a fairly 
>> > > >   simple > 
>> > >  case
>> > > >   of 5 dependent variables and a single two-level categorical 
>> > > >   predictor
>> > > >   (though the categories aren't balanced).
>> > > > >       If anybody happens to know of a script that will do this in 
>> > > > >       R, 
>> > >  I'd
>> > > >   love to know of it! Otherwise, I'll see about writing one myself.
>> > > > >       What I currently see is this, from help.search("power"):
>> > > > >   stats::power.anova.test
>> > > >                           Power calculations for balanced one-way
>> > > >                           analysis of variance tests
>> > > >   stats::power.prop.test
>> > > >                           Power calculations two sample test for
>> > > >                           proportions
>> > > >   stats::power.t.test     Power calculations for one and two sample t
>> > > >                           tests
>> > > > >       Any references on power in MANOVA would also be helpful, 
>> > > > >       though 
>> > >  of
>> > > >   course I will do my own lit search for them myself.
>> > > > >   Cordially,
>> > > >   Adam D. I. Kramer
>> > > > >   ______________________________________________
>> > > >   R-help at r-project.org mailing list
>> > > >   https://stat.ethz.ch/mailman/listinfo/r-help
>> > > >   PLEASE do read the posting guide > 
>> > >  http://www.R-project.org/posting-guide.html
>> > > >   and provide commented, minimal, self-contained, reproducible code.
>> > > > 
>> > > 
>> > 
>> >  ______________________________________________
>> >  R-help at r-project.org mailing list
>> >  https://stat.ethz.ch/mailman/listinfo/r-help
>> >  PLEASE do read the posting guide 
>> >  http://www.R-project.org/posting-guide.html
>> >  and provide commented, minimal, self-contained, reproducible code.
>> > 
>> > 
>>
>>  Charles C. Berry                            (858) 534-2098
>>                                             Dept of Family/Preventive
>>  Medicine
>>  E mailto:cberry at tajo.ucsd.edu	            UC San Diego
>>  http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901
>> 
>> 
>> 
>
>

Charles C. Berry                            (858) 534-2098
                                             Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu	            UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901