Hi Jana,

If your data are proportions, you might want to model their logit, ie
log(X/(1-X)), rather than their raw value. You can then use PGLS in the
same manner as you did. An ML value of 0 for lambda indicates that you are
actually fitting a non-phylogenetic model, but it is safer to allow for
lambda to vary in case there would be signal in the residuals of the
regression.
If your data are 0/1, then you should rather use phylogenetic logistic
regression.  This is implemented for example in the 'phyloglm' function in
the R package 'phylolm'.

Cheers,
Florian

2016-01-26 16:16 GMT+01:00 Knappová Jana <jana.knapp...@ibot.cas.cz>:

> Hi everyone,
>
> I am not very familiar with phylogenetics, but i would like to incorporate
> it somehow into my work and i appreciate any suggestions.
>
> Is it possible to use any kind of phylogenetically informed analysis in
> case of multiple regression (one response ~ multiple predictors) in case I
> assume binomial distribution of response variable? I try to explain species
> occurrence (proportional data) by a couple of species traits.
>
> I tried pgls function from "caper" R package, but I am not sure about it.
> Generally, it seems that there is not strong signal in my data, when I used
> lambda="ML" than lambda was set to zero.
>
> Thanks
>
> Jana Knappová
> Botanický ústav AV ČR, v. v. i. | Institute of Botany of the CAS
> Zámek 1, 252 43 Průhonice | Zamek 1, CZ-25243 Pruhonice
> Česká republika | Czech Republic
> jana.knapp...@ibot.cas.cz
> www.ibot.cas.cz
> www.pruhonickypark.cz
> Telefon: 271015401, 737375227 | Phone: +420-271015401, 737375227
> Fax: 271015105 | Fax: +420-271015105
> _______________________________________________
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-- 
Florian Boucher
Postdoctoral researcher, Institute of Systematic Botany, Zürich

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