Hi, Doesanyone use the 'betatree' function in the betareg package to do a kind
of falsediscovery rate (FDR) test for a set of many p values? I wasthinking to
compare the beta parameters of the true distribution of about 1000p values with
p values of permuted data, and test whether the two distributionswere
significantly different, with a greater mass of low p values in the truedata. I
know this is possible with betatree, I'm just not sure if it's a
'normal'method. I knowuniform-beta mixture models are commonly used to examine
FDR, and there are R packagesavailable, but my tests are non-independent so the
null distribution may not beuniform and has to be found empirically. The
mixture model approach assumes there are two groups: truepositives (beta
distribution) and true negatives (uniform distribution). I think my approach
would assume a continuous distributionof effect sizes in the true data, rather
than 2 distinct groups, with a point mass at 0 effect size for thepermuted data.
I also looked at using the 'betamix' function, but this is much less accurate
and takes longer to run. Best Richard.
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