Chris:  It may make sense to compare relative importance of predictors
across regions.  But it makes NO SENSE to base measures of relative
importance of predictors in your models on AIC weights.  AIC weights apply
to an entire model (1 to many predictors) not to individual predictors
within a model.  This is a flawed procedure advocated by Burnham and
Anderson.  Check out the simulation study by Murray and Connor (2009.
 Ecology 90:348-355). The AIC weights approach to relative importance could
only do anything useful if all your models included a single predictor.
 There are lots of other legitimate approaches to computing relative
importance of predictors within your models (ratio of t-statistics,
standardized coefficients, hierarchical partitioning, variance
decomposition, etc.).  Use those, not AIC weights.

Brian

Brian S. Cade, PhD

U. S. Geological Survey
Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO  80526-8818

email:  cadeb@usgs.gov <brian_cade@usgs.gov>
tel:  970 226-9326



On Mon, Jun 24, 2013 at 3:11 AM, Chris Mcowen <chrismcowen@gmail.com> wrote:

> Dear list:
>
>
>
> I am investigating the drivers of variance in fisheries yield over time,
> across multiple sites (52).My aim is to isolate the drivers of yield in one
> site compared to another, in order to investigate spatial heterogeneity in
> the primary correlates.
>
>
>
> To date i have approached this by calculating the importance of each
> potential correlate (3) using an AIC framework (e.g. using model weights)
> for each site.
>
>
>
> >From this analysis I have a matrix: of  site against variable importance
>
>
>
> To my question. First, does it make sense, from a theoretical perspective,
> to make conclusions by comparing the importance of a variable in one region
> to another, for example, making statements like: In site A temperature was
> the most important variable in explaining changes in fisheries yield whilst
> in site G it was productivity?
>
>
>
> Second, I then clustered the variable  importance values and ended up with
> 3
> distinct clusters, from which i want to say -yield within cluster one is
> primarily driven by temperature, whilst for those sites in cluster 2 it is
> driven by productivity?
>
>
>
> I have got some nice results, that make sense from an ecological
> perspective
> i just wanted to check my approach?
>
>
>
> Thanks
>
>
>
>
>
>
>
>
>
>
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