?? Hello all,
?? I am doing some Bonferroni correction analyses with R.adjust function. I have
a spreadsheet with 24 columns, each with 5 values. When I use the
"holm" method, it gives me adjusted figures for all the original
values except from the ones in the 4th row of each column. I mean, the value on
the 4th row for every column is exactly the same either in the original data or
in the corrected one.?? I've tried using another algorithm just to see what
happens ("bonferroni", for example) and everything is fine, I get
corrected figures for all the values, even the ones on the 4th row.
?? Does anyone know whether this is any kind of known bug of the
"holm" algorithm of P.adjust function. If so, should I worry about it?
If so, can anybody suggest any possible solution?
?? Thank you very much.
?? Iker
__________________________________________________________________
?? Dr. Iker Vaquero-Alba
?? Visiting Postdoctoral Research Associate
?? Laboratory of Evolutionary Ecology of Adaptations,?
?? School of Life Sciences, University of Lincoln,??? Riseholme Park Campus,
Lincoln
?? LN2 2LG,
?? UK.
?? https://eric.exeter.ac.uk/repository/handle/10036/3381
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Please send a reproducible example. Best, Uwe Ligges On 06.08.2015 19:20, Iker Vaquero Alba wrote:> Hello all, > I am doing some Bonferroni correction analyses with R.adjust function. I have a spreadsheet with 24 columns, each with 5 values. When I use the "holm" method, it gives me adjusted figures for all the original values except from the ones in the 4th row of each column. I mean, the value on the 4th row for every column is exactly the same either in the original data or in the corrected one. I've tried using another algorithm just to see what happens ("bonferroni", for example) and everything is fine, I get corrected figures for all the values, even the ones on the 4th row. > > Does anyone know whether this is any kind of known bug of the "holm" algorithm of P.adjust function. If so, should I worry about it? If so, can anybody suggest any possible solution? > Thank you very much. > Iker > > > __________________________________________________________________ > > Dr. Iker Vaquero-Alba > Visiting Postdoctoral Research Associate > Laboratory of Evolutionary Ecology of Adaptations, > School of Life Sciences, University of Lincoln, Riseholme Park Campus, Lincoln > LN2 2LG, > UK. > > https://eric.exeter.ac.uk/repository/handle/10036/3381 > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >
On 06 Aug 2015, at 19:20 , Iker Vaquero Alba <karraspito at yahoo.es> wrote:> Hello all, > I am doing some Bonferroni correction analyses with R.adjust function. I have a spreadsheet with 24 columns, each with 5 values. When I use the "holm" method, it gives me adjusted figures for all the original values except from the ones in the 4th row of each column. I mean, the value on the 4th row for every column is exactly the same either in the original data or in the corrected one. I've tried using another algorithm just to see what happens ("bonferroni", for example) and everything is fine, I get corrected figures for all the values, even the ones on the 4th row. > > Does anyone know whether this is any kind of known bug of the "holm" algorithm of P.adjust function. If so, should I worry about it? If so, can anybody suggest any possible solution? > Thank you very much. > Ikerp.adjust(), I presume? The Holm procedure is essentially to sort p-values in decreasing order and mutiplying by 1:n plus a little fiddling to keep the order and prevent p > 1. The logic is that if you reject the hypothesis corresponding to the smallest p after Bonferroni-correction by N, you only have N-1 simultaneous tests to consider, etc. The smallest multiplier will be 1, so it's not strange that one value appears uncorrected. It's curious that it is always in the 4th row, but it might be that the p-values in the 4 other rows are all considerably smaller. You do realize that if you run p.adjust for each column, you are not actually adjusting for the total of 120 tests, only for 5 of them, effectively ignoring the 23 other columns every time? -pd> > > __________________________________________________________________ > > Dr. Iker Vaquero-Alba > Visiting Postdoctoral Research Associate > Laboratory of Evolutionary Ecology of Adaptations, > School of Life Sciences, University of Lincoln, Riseholme Park Campus, Lincoln > LN2 2LG, > UK. > > https://eric.exeter.ac.uk/repository/handle/10036/3381 > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.-- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Office: A 4.23 Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com
?? Hello, Peter, and thank you for your clarifying reply. Actually, that was
another doubt I had. As I take my data from different files (every "bunch
of 5" values is taken from a different file), I assumed that, if I wanted
to adjust for the error due to repeated measures, it should be enough to do it
inside each file, right? I mean, the possible error due to repeated measures
shouldn't go beyond each file. Once you close one file, open and attach a
new one, the count, let's say, starts from scratch.
Am I right? And if I'm not, what is the reason why should I pool all the
p-values in a massive column and adjust them in bulk?
?? Thank you very much for your help.??
Iker?__________________________________________________________________
?? Dr. Iker Vaquero-Alba
?? Visiting Postdoctoral Research Associate
?? Laboratory of Evolutionary Ecology of Adaptations,?
?? School of Life Sciences, University of Lincoln,??? Riseholme Park Campus,
Lincoln
?? LN2 2LG,
?? UK.
?? https://eric.exeter.ac.uk/repository/handle/10036/3381
De: peter dalgaard <pdalgd at gmail.com>
CC: "r-help at r-project.org" <r-help at r-project.org>
Enviado: Viernes 7 de agosto de 2015 14:40
Asunto: Re: [R] Potencial bug in R.adjust ("holm" method)
>? ? Hello all,
>? ? I am doing some Bonferroni correction analyses with R.adjust function. I
have a spreadsheet with 24 columns, each with 5 values. When I use the
"holm" method, it gives me adjusted figures for all the original
values except from the ones in the 4th row of each column. I mean, the value on
the 4th row for every column is exactly the same either in the original data or
in the corrected one.? I've tried using another algorithm just to see what
happens ("bonferroni", for example) and everything is fine, I get
corrected figures for all the values, even the ones on the 4th row.
>
>? ? Does anyone know whether this is any kind of known bug of the
"holm" algorithm of P.adjust function. If so, should I worry about it?
If so, can anybody suggest any possible solution?
>? ? Thank you very much.
>? ? Iker
p.adjust(), I presume?
The Holm procedure is essentially to sort p-values in decreasing order and
mutiplying by 1:n plus a little fiddling to keep the order and prevent p > 1.
The logic is that if you reject the hypothesis corresponding to the smallest p
after Bonferroni-correction by N, you only have N-1 simultaneous tests to
consider, etc. The smallest multiplier will be 1, so it's not strange that
one value appears uncorrected. It's curious that it is always in the 4th
row, but it might be that the p-values in the 4 other rows are all considerably
smaller.
You do realize that if you run p.adjust for each column, you are not actually
adjusting for the total of 120 tests, only for 5 of them, effectively ignoring
the 23 other columns every time?
-pd
>
>
> __________________________________________________________________
>
>? ? Dr. Iker Vaquero-Alba
>? ? Visiting Postdoctoral Research Associate
>? ? Laboratory of Evolutionary Ecology of Adaptations,
>? ? School of Life Sciences, University of Lincoln,? ? Riseholme Park
Campus, Lincoln
>? ? LN2 2LG,
>? ? UK.
>
>? ? https://eric.exeter.ac.uk/repository/handle/10036/3381
>
>
> ??? [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
--
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Office: A 4.23
Email: pd.mes at cbs.dk? Priv: PDalgd at gmail.com
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