Dear all, I am experiencing problems using the glmmPQL function in the MASS package (Venables & Ripley 2002) to model binomial data with spatial autocorrelation.
My question - is the presence of birds affected by various hydrological parameters? Presence/absence data were collected from 83 sites and coupled against hydrological data from the same site. The bird survey sampling effort varied at each site so I want to include this as a random effect (fAVGNTS). I have also conducted a join count test which suggests that there is some spatial autocorrelation. Consequently I have used the following code: library(MASS) attach(Birds) Birds$x <- Birds$LONGITUDE Birds$y <- Birds$LATITUDE M <- glmmPQL(PRESENCE~ HYDROVAR1 + HYDROVAR2, random= ~ 1|fAVGNTS, correlation = corExp(form = ~ x + y), family = binomial(link = "logit"), data = Birds) The model seems to run fine. However, when I compare the results of this model and the residual spread against the same model but without the correlation function, there is absolutely no difference at all. I am somewhat confused by this as both Dormann et al. 2007 and Bivand et al. 2008 have suggested the use of the glmmPQL function to model binomial data with spatial autocorrelation and random effects. Therefore I am wondering if anyone knows why this has occurred and secondly I am wondering if the correlation function does indeed work outside of gls? Many thanks in advance for your help. Best regards -- View this message in context: http://r.789695.n4.nabble.com/GLMMPQL-spatial-autocorrelation-tp4631689.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.