[R-sig-ME] MCMCglmm: tissue type as a random effect when not all species have been measured for all tissuess

Ben Bolker bbolker @ending from gm@il@com
Wed Jun 6 19:09:06 CEST 2018

  My guess is that it would be no problem to treat tissue as fixed and
species as random (and phylogenetically correlated) (and the
species:tissue interaction as random, so that you can model variation
within species -- **or** simply pool the multiple measurements from each
species/tissue combination, see Murtaugh "Simplicity and complexity in
ecological data analysis").
  Why not try it (maybe with a subset of your data) and see what happens?

On 2018-06-06 01:07 PM, Nathanael Walker-Hale wrote:
> Hi Ben,
> Thanks very much for your response. There are more tissues (six in all),
> I just chose those as an example of the data format. I was under the
> impression that the missing data would be a problem if attempting to
> treat tissue type as fixed, but is this not the case? I have seen in
> other threads the ways in which missing responses are imputed in
> MCMCglmm, and I could perhaps merge tissue types into two or three
> classes (say root, shoot and flower) and model them as fixed, if the
> missing data does not create problems for the analysis.
> Thanks again for your help,
> Nathanael
> On Wed, Jun 6, 2018 at 11:46 AM, Ben Bolker <bbolker using gmail.com
> <mailto:bbolker using gmail.com>> wrote:
>       In principle this kind of missing data is no problem, but it seems odd
>     to treat tissue type as random if (as I understand it) you only have two
>     types of tissue (root, leaf) ... Perhaps you have more? Even so (say you
>     had a few more), this would present both technical issues [you'd
>     probably need a moderately strongly informative prior on the
>     among-tissue variance], and it seems odd to me to treat tissues as
>     exchangeable.
>     On 2018-06-06 11:29 AM, Nathanael Walker-Hale wrote:
>     > Hi all,
>     >
>     > I am planning to use MCMCglmm to do a phylogenetic comparative
>     analysis. I
>     > have multiple metabolite measurements on multiple tissue types per
>     species
>     > (e.g. leaf, three measurements, root, three measurements, per
>     species). I
>     > am interested in analyzing how levels of metabolite are predicted
>     by the
>     > presence or absence of a gene. Ideally, I would like to model both
>     > between-species relationships (from a phylogeny) and tissue type
>     as random
>     > effects. However, not all species have measurements on all tissue
>     types.
>     >
>     > Will this be a problem for the analysis? Is it possible to run the
>     model in
>     > the presence of missing data like this? There is not a
>     particularly heavy
>     > bias to the pattern of missing tissue across the phylogeny, but
>     some tissue
>     > types have been measured much less than others (e.g. far fewer
>     species have
>     > floral measurements).
>     >
>     > Best wishes,
>     >
>     > Nathanael
>     >
>     >       [[alternative HTML version deleted]]
>     >
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