>From what I can tell by reading forum posts etc., this is not a trivial issue. An answer in 2008 indicated some directions, but I'm curious whether any developments have been made since then.
In my data set I have 182 observations with a binomial response, a 2-level explanatory factor, and x and y coordinates. By visually inspecting the spatial distribution of standardized residual error and multi-directional variograms I must conclude that adding spatial correlation structure to my logistic regression model (currently implemented using glm) would be prudent. Can anyone please offer advice as to how I should go about incorporating this spatial auto-correlation to my model? Is it perhaps easier in my case, given that I have only a single 2-level factor as an explanatory variable? If so, I'm actually interested in how to do this for logistic regression (with continuous variables) too, so a method toward this end would be interesting as well. -- View this message in context: http://r.789695.n4.nabble.com/Adding-Spatial-Correlation-Strucutre-to-Logistic-Regression-Contingency-Analysis-tp4649300.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
