autologistic modelling in R
David Katz <david <at> davidkatzconsulting.com> writes:
Curiosity and Google lead me to this paper which may be of interest: Assessing the validity of autologistic regression Carsten F. Dormann Abstract
...
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.
Good point and reference. My understanding is that the term "autologistic" is used both of a GLMM with a spatially structured random effect, and of a GLM with the product of the response and a matrix of spatial weights included on the right hand side as an "autocovariate". I believe that the article finds that the use of such an "autocovariate" can lead to the problems described, for example when the "autocovariate" is strongly correlated with the other right hand side variables. A properly specified GLMM should not suffer from the same problems. Roger Bivand
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