[R-sig-ME] Alternatives to lmer

[Murray Jorgensen]

Let me check that I am interpreting your data correctly. It seems that 
you have 12 sites at each of which you have a number of mated pairs. You 
have physical measurements on the male and the female of each pair and 
some environmental measurements on the sites.

The pairs are numbered within sites but some numbers are missing. Might 
they be the numbers corresponding to pairs that failed to fledge? I 
think maybe they should be there as well with nfledge = 0.

'instotal' and 'weatherpc1' are measured at the 'site' level, so the 
natural way to incorporate them in a model would be through a

     (instotal + weatherpc1|site)

term.

Surely also 'nfledge' should be at the 'pair' level ?

I think it would then be better to re-shape the data so that each row is 
a pair and, for example, 'tlength' splits into two covariates 'tlengthM' 
and 'tlengthF'.

It looks doubtful to me that a Poisson model will fit this data well, 
with or without the addition of the nfledge = 0 pairs.

I think that you should be talking more to some local statisticians 
before you attempt to fit models to this data.


Regards,  Murray

On 17/01/2011 9:15 a.m., Iker Vaquero Alba wrote:
>
>     Hello:
>
>     As I posted several days ago, I was trying to implement this model:
>
> fledgecoltailmodel1<-lmer(nfledge~sex*briventral*inslarge*weatherpc1*tlength-sex:briventral:inslarge:weatherpc1:tlength-sex:briventral:inslarge:weatherpc1-sex:briventral:inslarge:tlength-sex:briventral:weatherpc1:tlength-sex:inslarge:weatherpc1:tlength-briventral:inslarge:weatherpc1:tlength-sex:briventral:inslarge-sex:briventral:weatherpc1-sex:briventral:tlength-sex:inslarge:weatherpc1-sex:inslarge:tlength-sex:weatherpc1:tlength-briventral:inslarge:weatherpc1-briventral:inslarge:tlength-briventral:weatherpc1:tlength-inslarge:weatherpc1:tlength+(site|pair),family=poisson)
>
>     but I got the error message:
>
>     Error in asMethod(object) : matrix is not symmetric [1,2]
>
>    as no one seems to know what could be the reason for that or how to find a solution, I was thinking that maybe I could try using another function. Starting with the one which seems more similar to "lmer", I tried with "GLMM", which I read in some post it could be taken from "lme4" package. However, when I try to use it (either "glmm" or "GLMM"), R tells me such function doesn't exist.
>
>     Do you know why this could be happening? Do you know of any other functions I could use to fit my model? I was thinking as well of "MCMCglmm", but I'm not sure I can apply it to my model and I don't think I'm expert enough as to deal with its syntax or the overdispersion problems.
>
>     I am using R 2.12.0
>
>     Thank you very much for your help!
>
>
>
>     Iker Vaquero-Alba
>
>     Centre for Ecology
> and Conservation
>
>     Daphne du Maurier
> Building
>
>     University of Exeter,
> Cornwall Campus
>
>     Treliever Road
>
>     TR10 9EZ Penryn
>
>     U.K.
>
>
>
>
>
>
>
> 	[[alternative HTML version deleted]]
>
>
>
>
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models


-- 
Dr Murray Jorgensen      http://www.stats.waikato.ac.nz/Staff/maj.html
Department of Statistics, University of Waikato, Hamilton, New Zealand
Email: maj at waikato.ac.nz    majorgensen at ihug.co.nz      Fax 7 838 4155
Phone  +64 7 838 4773 wk    Home +64 7 825 0441   Mobile 021 0200 8350