[R] multiple comparisons on a between factor

[elgoran at web.de]

   Rich,
   thanks a lot, i will definitly check it out. however, since the analysis
   mentioned above is already implemented could you or anyone tell me whether
   it contains any statistical flaws?
   best
   Lisa
       ______________________________________________________________

     Von: "Richard M. Heiberger" <rmh at temple.edu>
     Gesendet: 27.04.2011 16:58:43
     An: elgoran at web.de
     Betreff: Re: [R] multiple comparisons on a between factor

   Lisa,



   Please look at some of the demos in the HH package.

   These are built on the capabilities of the glht function in the multcomp
   package.



   ## install.packages("HH")  ## if necessary

   library(HH)



   demo("MMC.WoodEnergy-aov", package="HH") ## first
   demo("MMC.WoodEnergy", package="HH")  ## second
   Rich

   On Wed, Apr 27, 2011 at 5:02 AM, <[1]elgoran at web.de> wrote:

       Dear list,
       im facing an issue of statistical data analysis that I consider myself
       unable to resolve in R so i hope to get some valuable insights from you.
     i
       run an ANOVA with four factors; factor4 is an between factor (two
     different
       groups measured), the others are withins (tested across /all/ subjects).
       accordingly, my model looks as follows:
       fm1

     <-aov(dataSubjects~(factor1*factor2*factor3*factor4)+Error(subject/(factor
     1*
       factor2*factor3))+factor4,data=mydata)
       print(summary(fm1))
       so  far so good. i now would like to perform multiple comparisons, but
       separately for each level of factor4 (two). this is how I do it: i sort
     out
       (using subset) the levels im interested in comparing, say level 1 of
     factor
       1
       Type.lvl1 <- subset(mydata, factor1 == "lvl1")
       and then compute an uncorrected pairwise t-test between the two levels
     of
       factor 4:

     Type.lvl1.P<-pairwise.t.test(Type.lvl1$dataSubjects,Type.lvl1$factor4,p.ad
     j
       = "none")
       i do this for every comparison im interested in and apply any method for
       multiple comparison correction afterwards on the entire set of p values
       obtained. is this valid (in statistical terms)? if not, could anyone
     refer
       to a better procedure i should use instead?
       Thanks in advance.
       Lisa
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References

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   2. http://web.de/
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   7. http://www.r-project.org/posting-guide.html
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