[R-sig-ME] Query lme4

[peter dalgaard]

On Mar 20, 2010, at 11:02 PM, Ben Bolker wrote:

> Elizabeth Crone wrote:
(well, citing Doug, actually...)
>>> In most cases of longitudinal data it would be very difficult to
>>> distinguish between an autoregressive structure and a model with
>>> random effects specification (AGEACTUAL|Individual).
> 
>  Hmm.  Is this true if there are sufficient data?  That is, shouldn't
> autocorrelated variation within an individual be detectable even if
> there is a linear trend within individuals?  (Isn't this what the
> corARxx structures in nlme are for?)

Yes. I was also a bit surprised about that remark. I'm fairly sure I have seen examples where the tell-tale decline of intra-individual correlations with distance in time was quite visible in data. I don't think you can do that with a random-slope model.

> 
>> 
>> I think this is true if observations are POSTIVELY autocorrelated,
>> but the random individual effects should be separable from NEGATIVE
>> autocorrelations, right? [This posting caught my eye because I have
>> been wishing I could use something like lme4 to fit mixed models to
>> data with strong negative autocorrelations, specifically, probability
>> of flowering for plants that flower approximately in alternate
>> years.]
> 
>  You probably have to do this in WinBUGS etc. for the foreseeable
> future.  The good news is that it's reasonably easy to write down a
> structure that should produce this, i.e. something like
> 
>   X[indiv,time] ~ Binomial(p_indiv(t))
>   logit(p_indiv(t)) ~ Normal(a+b*p_indiv(t-1)+...,tau)
> 
>  where ... could include covariates, random (but persistent)
> among-individual variation, etc..  If -1<b<0 then you get population
> dynamics with negative autocorrelation.
> 
> 
> -- 
> Ben Bolker
> Associate professor, Biology Dep't, Univ. of Florida
> bolker at ufl.edu / people.biology.ufl.edu/bolker
> GPG key: people.biology.ufl.edu/bolker/benbolker-publickey.asc
> 
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

-- 
Peter Dalgaard
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com