[R-sig-eco] multiple regression

[Andrew Kosydar]

Hi Nathan,

I only quickly read your email, but I believe you were asking about step-wise regression.  I would strongly suggest that instead you consider using multimodel inference (Burnham & Anderson).  If you want I can suggest for you a couple of papers to read in order to learn more about this technique.

Best of luck,

Andrew


Andrew Kosydar
University of Washington
Department of Biology
24 Kincaid Hall, Box 351800
Seattle, WA 98195
USA







On Sat, 6 Feb 2010, Nathan Lemoine wrote:

> Hi everyone,
>
> I'm trying to fit a multiple regression model and have run into some 
> questions regarding the appropriate procedure to use. I am trying to 
> compare fish assemblages (species richness, total abundance, etc.) to 
> metrics of habitat quality. I swam transects are recorded all fish 
> observed, then I measured the structural complexity and live coral 
> cover over each transect. I am interested in weighting which of these 
> two metrics has the largest influence on structuring fish 
> assemblages.
>
> My strategy was to use a multiple linear regression. Since the data 
> were in two different measurement units, I scaled the variables to a 
> mean of 0 and std. dev. of 1. This should allow me to compare the 
> sizes of the beta coefficients to determine the relative (but not 
> absolute) importance of each habitat variable on the fish assemblage, 
> correct?
>
> My model was lm(Species Richness~Complexity+Coral Cover). I had run a 
> full model and found no evidence of interactions, so I ran it without 
> the interaction present.
>
> It turns out coral cover was not significant in any regression. I 
> have been told that the test I used was incorrect and that the 
> appropriate procedure is a stepwise regression, which would, 
> undoubtedly, provide me with Complexity as a significant variable and 
> remove Coral Cover. This seems to me to be the exact same 
> interpretation as the above model. So, since I'm very new to all of 
> this, I am wondering how to tell whether one model is 'incorrect' or 
> 'inappropriate' given that they yield almost identical results? What 
> are the advantages of a stepwise regression over a standard multiple 
> regression like I have run?
>
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