Thom Baguley wrote:
> christophe tourenq wrote:
> >
> > I am a biologist (definitely not a statistician) in France with very
> > limited access to statistical resources and I wonder if someone can give
> > me some advice. I have been conducting weekly bird counts in wetland
> > areas for a period of 1 year. The intention is to compare numbers of
> > birds (of each species) among different wetland types. I was intending
> > on using a generalized linear model framework where counts are treated
> > as a Poisson random variable. The problem is this:
> >
> > Of course I have now been fully advised that these counts are not
> > independent... and someone suggested to me to consider this as a
> > repeated measure. However, it seems to me that independence is really
> > also a function of time. Clearly counts taken over a short time
> > interval are related... but counts taken during different seasons over
> > the year probably are not. Someone else suggested to me that there
> > might be a way to use a bootstrapping approach to resample the data and
> > eliminate some of the independence problem. Anyway, I would appreciate
> > any ideas that anyone might have.
>
> The counts are non-independent if you have repeated counts of the same wetland
> area (not type) over time. There are models for repeated measures Poisson GLMs
> (e.g., multilevel approaches). A normal repeated measures model (possibly with
> a transformation) might fit the data reasonably well and is definitely worth
> considering. If different areas are sampled (randomly or in a stratified) over
> time then a standard Poisson model should be OK.
>
> Thom
Thom has given some good advice. As noted, though, a little more about your
problem might be helpful. Tell more about your sampling plan. As Thom says, did
you sample exactly the same areas over time or did you choose different areas each
time? How many samples at each time point? Or did you take one measurement at a
number of time points?
