Correct. If a user wishes to adjust for multiple comparisons they may do so 
post-hoc.

Dean

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________________________________
From: [email protected] <[email protected]> on behalf of Ian 
Dworkin <[email protected]>
Sent: Monday, May 25, 2026 8:23:53 AM
To: [email protected] <[email protected]>
Cc: Morphmet <[email protected]>
Subject: Re: [MORPHMET2] Should multiple comparisons with pairwise() have 
p-value adjustments?

HI Vera,

 pairwise() in geomorph/RRPP does not do any adjustments. The last I spoke to 
Mike and Dean about (when I prepped an online seminar about it during the 
pandemic... so a while ago), it was in part because it provides ALL pairwise 
comparisons. One of the things I point out to people using it, is that you need 
to a priori plan which you are going to use, and do your adjustments based upon 
that.

Cheers
Ian

On Mon, 25 May 2026 at 06:33, 
[email protected]<mailto:[email protected]> 
<[email protected]<mailto:[email protected]>> wrote:

Hi everyone,

I was recently asked if I implement any multiple comparison adjustments (like 
Holm) when using the pairwise() function in geomorph on RRPP-based 
procD.lm/procD.pgls fits involving a factor with more than two levels. I admit 
that this never crossed my mind, but I can’t see why there should not be a 
higher risk of getting false H0 rejections with increasing comparisons, as it 
would in other multiple comparison contexts.

It is easy to do an adjustment manually, but I do not think I have seen it done 
anywhere – it is not part of the pairwise implementation as far as I can see, 
and I did not spot a comment on it in the Collyer & Adams 2018 paper on RRPP. I 
was wondering if there is a reason for this, perhaps related to the residual 
randomisation procedure or building of confidence intervals?

Thanks a lot for any suggestions!

Vera

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Ian Dworkin
Department of Biology
McMaster University
Office phone 905 525 9140 ext. 21775
Lab phone 905 525 9140 ext. 20076
[email protected]<mailto:[email protected]>
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