[R] Potencial bug in R.adjust ("holm" method)

[peter dalgaard]

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.
>    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
> 
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-- 
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
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