Hello dear list members.

First I want to wish you all Happy New Year! I Hope 2013 brings us many
opportunities to learn and to do our best in our careers and personal life.
 After that,  I must apologize for the late response.

I am very greatful  for your useful cues.

Sr. López, you're right about the uncountable variables, the formula
accepted it and all worked well with the countable ones. Thank you a lot
for the help. I'll keep trying to solve the problem on the correlated
predictors.

Sr. Rowlingson, thank you for the example of spatial autocorrelation, and
yes it is an important issue to worry about. The environmental variables
 were colected at stations far from each other, trying to avoid it. Also we
are not using the colected values, but new ones estimated from the real
ones. Does it help to avoid the data spatial autocorrelation too??


Thank you a lot.

Cheers!!


Suzana








2013/1/2 Barry Rowlingson <b.rowlingson@lancaster.ac.uk>

> On Sun, Dec 30, 2012 at 1:55 PM, Suzana Stutz <suzana.stutz@gmail.com>
> wrote:
> > Dear list members.
> >
> > I've been trying to apply GLM for spatial analysis of  a marine animal's
> > distribution (as the dependant variable) related to many environmental
> > variables (as the independant ones). But some of them are correlated, for
> > example, the depth increases as the distance to coast increases, and  I
> > must test both. Does it disagree with the assumption of independence of
> the
> > data? If yes, how can I fix it in order to keep the two variables in the
> > model?
>
>  Correlation in your explanatory variables is a classical problem of
> variable selection, and there are methods for that. The bigger problem
> with doing a GLM with spatial data is that the data points are going
> to have spatial autocorrelation...
>
>  Two measurements of 10 fish per square meter at depth 50m taken two
> metres apart are less likely to be independent than two measurements
> of 10 fish per square meter at depth 50m taken twenty kilometres
> apart. In the first case, the second measurement doesn't much extra
> information - you already knew that this location had 10 fish/m^2 -
> but in the second case the second measurement is much more useful.
> There were 10 fish/m^2 even though the locations were far apart! It
> might be due to the 50m depth!
>
> You can do a GLM for starters, but its important to check the
> independence assumption of the GLM otherwise you could be getting
> significant effects when none are really there.
>
> Barry
>



-- 
*Suzana Stutz Reis*
Mestranda do Programa de Pós Graduação em Ciências Biológicas -
Comportamento e Biologia Animal
Universidade Federal de Juiz de Fora, MG, Brasil.

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