[R-sig-eco] Binomial GLMM or GAMM with random intercept and temporal correlation

[SamiC]

Dear ecology mailing list,

I am trying to model some binomial data (0/1) as a function of sex (0/1) and
DistanceToFeature (continuous km’s) with an interaction between the two.  My
data is nested and I therefore want to include a random intercept for
InidividualID and within that I want to include an AR1 correlation structure
as the data is serially/temporally auto-correlated.  I understand any
correlation structure should be nested within the random effect.

So far I have tried running the model using glmmPQL as 

glmmPQL(Y ~ DistanceToFeature * Sex + (1|InidividualID),
correlation=corAR1(form=~1|IndividualID/ContinuousBout), family=’binomial’,
data=’birds’) 

(note – ContinuousBout is an ID for where there are time gaps in the data).

However, although this runs, am I right in understanding that I should not
use PQL estimation with binomial data as it gives biased results?  Does
anyone know of a way I can model this?

I understand that this is also the case if I wish to use GAMM (as later I
will be modelling a non-linear explanatory as well)?  

Additionally I will also be running a similar set up but where the data are
not equally spaced in time (and therefore an AR1 structure would not apply).
Can anyone give a recommendation of a modelling framework for this also.

Any help would be much appreciated.

Thank you

Sam




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