Re: st: multproc

["Roger B. Newson" <r.newson@imperial.ac.uk>]

Sorry, my remark that

the two Benjamini-Liu methods sometimes have the annoying feature that 
the corrected P-value is lower than the uncorrected P-value.

should have read

the two Benjamini-Liu methods sometimes have the annoying feature that 
the corrected critical P-value is higher than the uncorrected critical 
P-value.

In your case, the Benjamini-Liu-corrected critical P-value is lower than 
the uncorrected critical P-value. And the discovery set is reduced to an 
empty set. My remarks about the Simes procedure and q-values are still 
valid, though.

Best wishes

Roger

Roger B Newson BSc MSc DPhil
Lecturer in Medical Statistics
Respiratory Epidemiology, Occupational Medicine
and Public Health Group
National Heart and Lung Institute
Imperial College London
Royal Brompton Campus
Room 33, Emmanuel Kaye Building
1B Manresa Road
London SW3 6LR
UNITED KINGDOM
Tel: +44 (0)20 7594 7931
Email: r.newson@imperial.ac.uk
Web page: http://www.imperial.ac.uk/nhli/r.newson/
Departmental Web page: http://www.imperial.ac.uk/nhli/reomph/

Opinions expressed are those of the author, not of the institution.

On 20/03/2014 09:57, Roger B. Newson wrote:
> No, you are not doing anything incorrectly. However, as stated in Newson
> et al. (2003), the two Benjamini-Liu methods sometimes have the annoying
> feature that the corrected P-value is lower than the uncorrected P-value.
>
> I personally usually use the Simes-Benjamini-Hochberg procedure
> (-method(simes)-), rather than the Liu procedures. And, nowadays, I
> usually use -qqvalue- instead of -multproc-, because I prefer q-values
> to discovery sets. The use of q-values is probably an advance on
> discovery sets, because, given the q-values, every individual in the
> audience can input his/her own FDR and define his/her own discovery set.
> For more about -qqvalue- and frequentist q-values, see Newson (2010).
>
> I hope this helps.
>
> Best wishes
>
> Roger
>
> References
>
> Newson R and the ALSPAC Study Team. Multiple-test procedures and smile
> plots. The Stata Journal 2003; 3(2): 109-132. Download from
> http://www.stata-journal.com/article.html?article=st0035
>
> Newson RB. Frequentist q-values for multiple-test procedures. The Stata
> Journal 2010; 10(4): 568-584. Download from
> http://www.stata-journal.com/article.html?article=st0209
>
> Roger B Newson BSc MSc DPhil
> Lecturer in Medical Statistics
> Respiratory Epidemiology, Occupational Medicine
> and Public Health Group
> National Heart and Lung Institute
> Imperial College London
> Royal Brompton Campus
> Room 33, Emmanuel Kaye Building
> 1B Manresa Road
> London SW3 6LR
> UNITED KINGDOM
> Tel: +44 (0)20 7594 7931
> Email: r.newson@imperial.ac.uk
> Web page: http://www.imperial.ac.uk/nhli/r.newson/
> Departmental Web page: http://www.imperial.ac.uk/nhli/reomph/
>
> Opinions expressed are those of the author, not of the institution.
>
> On 19/03/2014 23:25, Char Adams wrote:
> > Hello,
> >
> >
> > Does anyone have experience with false discovery methods in Stata?  I
> > asked StataHelp and was told there wasn't an official command.
> >
> > I downloaded smileplot, but I don't know if I'm using multproc
> > correctly.  I've varied the choice of method within the syntax I'm
> > trying and I don't see much of difference between methods (bonferroni
> > verus simes etc....)
> >
> > I've got a dataset which provides the pvalues in a column with my
> > tests of interest, but I was expecting to see a corrected pvalue that
> > would be less stringent than what I get with bonferroni.  Instead, it
> > is about the same, depending on the method.
> >
> > I may not be using the code correctly.
> >
> >
> > Here's the code I've tried:
> > multproc ,method(liu1) puncor(.05)
> >
> > What I get:
> > Method: liu1
> > Uncorrected overall critical P-value: .05
> > Number of P-values: 391
> > Corrected overall critical P-value: .00013118
> > Number of rejected P-values: 0
> >
> > Am I doing something incorrectly?  Is there any easier way?
> >
> > Thank you for your time,
> > Charleen
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