Dear Lv,
you're right that analysing PCs of Procrustes shape coordinates one at
a time is not a good idea. There will be very few cases (if any) when
a single PC is a good summary of multivariate shape.
In association studies, it is much more appropriate to look for the
direction that maximizes covariation (with other variables) in the
full multivariate space (multivariate regression, PLS etc.). PCs know
nothing about covariates, as they just maximize total variance: they
may or may not pick up some variation in the 'right' direction (the
one where most covariation is), but are at best sub-optimal and more
often inappropriate and misleading.

A few refs, in which you'll find more refs to older but more important papers:
Adams D.C., Cardini A., Monteiro L.R., O’Higgins P., Rohlf F.J., 2011.
Morphometrics and Phylogenetics: principal components of shape from
cranial modules are neither appropriate nor effective cladistic
characters. Journal of Human Evolution , 60: 240–243.
Cardini A., 2020. Modern morphometrics and the study of population
differences: good data behind clever analyses and cool pictures?
Anatomical Record, 303: 2747–2765. DOI: 10.1002/ar.24397
Pdfs should be available in my webpage.

All the best

Andrea

On 03/05/2022, lv xiao <[email protected]> wrote:
> Dear all,
>
> I have the impression over the years that principal component scores of
> shape along each axis after PCA cannot be analysed separately as if each
> were idependent traits. However, I still come across such papers from time
> to time (Fig 3 in R. Soc. open sci. 6: 181382; Fig 4 in PLoS Genet
> 12:e1006174.).
>
> I would like to ask whether shape PC scores (like PC1 scores for all
> specimens) could be used to investigate the association between explanatory
>
> variables and shape changes along that PC?
>
> If it is not possible, why and is there any references? Thanks.
>
> Lv
>
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-- 
E-mail address: [email protected], [email protected]
WEBPAGE: https://sites.google.com/view/alcardini2/
or https://tinyurl.com/andreacardini

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