Hi Geertje, You should look into linear mixed-effects models. In these you can incorporate spatial correlation explicitly. The basic function to use is lme(), but you should do some reading about this type of models before jumping into it. An excellent resource is the book "Mixed Effects Models in S and S-Plus" by Jose Pinheiro and Douglas Bates.
Good Luck! Julian Geertje Van der Heijden wrote: > Hi, > > I have collected data on trees from 5 forest plots located within the > same landscape. Data within the plots are spatially autocorrelated > (calculated using Moran's I). I would like to do a ANCOVA type of > analysis combining these five plots, but the assumption that there is no > autocorrelation in the residuals is obviously violated. Does anyone have > any ideas how to incorporate these spatial effects in my analysis? I > have been reading up on autoregressive techniques, but I am not sure if > it works with more than one plot. > > All help is greatly appreciated! > > Many thanks, > Geertje van der Heijden > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. ______________________________________________ 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.
