Does it make sense for you to combine the 2 data sets and do a 2-way anova with 
treatment vs. control as one factor and experiment number as the other factor?  
Then you could test the interaction and treatment number factor to see if they 
make a difference.

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.s...@imail.org
801.408.8111


> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of syrvn
> Sent: Saturday, February 12, 2011 7:30 AM
> To: r-help@r-project.org
> Subject: [R] Test for equivalence
> 
> 
> Hi!
> 
> is there a way in R to check whether the outcome of two different
> experiments is statistically distinguishable or indistinguishable? More
> preciously, I used the wilcoxon test to determine the differences
> between
> controls and treated subjects for two different experiments. Now I
> would
> like to check whether the two lists of analytes obtained are
> statistically
> distinguishable or indistinguishable
> 
> I tried to use a equivalence test from the 'equivalence' package in R
> but it
> seems that this test is not applicable to my problem. The test in the
> 'equivalence' package just determines similarity between two conditions
> but
> I need to compare the outcome of two different experiments.
> 
> My experiments are constructed as follows:
> 
> Exp1:
> 8 control samples
> 8 treated samples
> -> determine significantly changes (List A)
> 
> Exp2:
> 8 control samples
> 8 treated samples
> -> determine significantly changes (List B)
> 
> 
> Now i would like to check whether List A and List B are distinguishable
> or
> indistinguishable.
> 
> Any advice is very much appreciated!
> 
> Best,
> beginner
> --
> View this message in context: http://r.789695.n4.nabble.com/Test-for-
> equivalence-tp3302739p3302739.html
> Sent from the R help mailing list archive at Nabble.com.
> 
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> and provide commented, minimal, self-contained, reproducible code.

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