[R-sig-ME] Modelling random effects with SITE, YEAR and SPECIES

[Ben Bolker]

David R. wrote:
> Hello all,
> 
> First, sorry for the english and the basic questions. I'm using mixed
> models (lme4 package) to analyse variability in 13 SPECIES of birds
> observed during 15 YEARS across 5 SITES. All the SPECIES were
> observed in all the sites in most years.
> 
> My fixed effects are A, B, C and Year. I'm interested in the
> stochastic effect of A, B and C on the dependent variable, but also
> in a possible linear trend of the dependent variable over time.
> 
> My random effects are SPECIES, YEAR and SITE, to control for the
> effects of nonindependence.
> 
> I have a model with SITE, YEAR and SPECIES as crossed random effects
> like A + B + C + Year + (1|SITE) + (1|YEAR) + (1|SPECIES).
> 
> My questions are:
> 
> 1) Is this model correct? It is correct to model YEAR both as random
> effect and fixed effect? Is there the possibility that the variance
> accounted for by the random effect could robbing year as a fixed
> effect of explanatory power?

  Seems OK and sensible to me.
  I would guess that the linear trend and the random variation are
sufficiently different patterns that they would not conflict too badly,
but you could try the different nested models and see what happens ...

> 
> 2) It is meaningful, instead,  to model YEAR as repeated measure, if
> the experimental unit were species within sites?

  "Modeling YEAR as a random effect" and "Modeling YEAR as a repeated
measure" are, in my opinion, almost the same thing (but I'm ready to be
corrected, as always).  The only aspect of "repeated measures" that
would be different would be if you wanted to fit an autoregressive model
so that samples closer together in time were more correlated (which you
can't do with lmer at this
point).

  Ben Bolker