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, <elgo...@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/(factor1*
> 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.adj
> = "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
>
> 1. http://produkte.web.de/go/DSL_Doppel_Flatrate/2
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