[R-sig-eco] Comparing results of two CCAs (Eliot Miller)

[Highland Statistics Ltd]

>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Thu, 13 Mar 2014 23:50:47 -0500
> From: Eliot Miller <eliotmiller at umsl.edu>
> To: r-sig-ecology at r-project.org
> Subject: [R-sig-eco] Comparing results of two CCAs
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> 	<CAKcGSHJYCsnoN3WT8J3f0rB=GyWQk_jYFnKVb5wsTPkhKYSU8g at mail.gmail.com>
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> I have four datasets: morphological measurements for a set of species (M1),
> ecological measurements for the same set of species (E1), morphological
> measurements for a second set of species (M2), and ecological measurements
> for this second set of species (E2).
>
> I am interested in finding the linear combinations of variables between M1
> and E1, and between M2 and E2. That is, I'd like to know what combinations
> of morphological measurements are associated with what combination of
> ecological measurements--for each set of species separately. This seems
> like a good use of CCA (two separate CCAs).
>
> But here's where things get tricky for me. I'd like to see whether the same
> linear combinations from one set of species do a good job of explaining the
> variation in the second set of matrices. And I'd like to see how they
> differ, if possible...e.g. yes the canonical function from the first CCA
> does explain some of the variation in the second, but a different function
> could do a lot better.


variance partitioning using CCA is what you need.

Kind regards,

Alain Zuur





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>



-- 
Dr. Alain F. Zuur

First author of:
1. Beginner's Guide to GAMM with R (2014).
2. Beginner's Guide to GLM and GLMM with R (2013).
3. Begginner's Guide to GAM with R (2012).
4. Zero Inflated Models and GLMM with R (2012).
5. A Beginner's Guide to R (2009).
6. Mixed effects models and extensions in ecology with R (2009).
7. Analysing Ecological Data (2007).

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