[R] autologistic modelling in R

David Katz david at davidkatzconsulting.com
Sat Dec 20 21:55:08 CET 2008

Curiosity and Google lead me to this paper which may be of interest:

Assessing the validity of autologistic regression
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Carsten F. DormannCorresponding Author Contact Information, a, E-mail The
Corresponding Author

aDepartment of Computational Landscape Ecology, UFZ Centre for Environmental
Research, Permoserstr. 15, 04318 Leipzig, Germany

Received 11 July 2006; 
revised 30 April 2007; 
accepted 7 May 2007. 
Available online 20 June 2007.


In autologistic regression models employed in the analysis of species’
spatial distributions, an additional explanatory variable, the
autocovariate, is used to correct the effect of spatial autocorrelation. The
values of the autocovariate depend on the values of the response variable in
the neighbourhood. While this approach has been widely used over the last
ten years in biogeographical analyses, it has not been assessed for its
validity and performance against artificial simulation data with known
properties. I here present such an assessment, varying the range and
strength of spatial autocorrelation in the data as well as the prevalence of
the focal species. Autologistic regression models consistently underestimate
the effect of the environmental variable in the model and give biased
estimates compared to a non-spatial logistic regression. A comparison with
other methods available for the correction of spatial autocorrelation shows
that autologistic regression is more biased and less reliable and hence
should be used only in concert with other reference methods.

charlotte.bell wrote:
> Hi,
> I have spatially autocorrelated data (with a binary response variable and
> continuous predictor variables). I believe I need to do an autologistic
> model, does anyone know a method for doing this in R?
> Many thanks
> C Bell
> ______________________________________________
> R-help at r-project.org mailing list
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> PLEASE do read the posting guide
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> and provide commented, minimal, self-contained, reproducible code.

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