Hi, I have a question regarding the nesting structure in linear mixed models of data, which is spatially and at the same time temporally correlated.
So far I have tried to get around the problem by averaging out the temporal component but I would really like to keep everything in the model. Here is the experimental set-up: We have measured insect abundance in two different islands, each having 5 sites, each site having 4 plots, in which each we have 5 collection points (traps). The sampling was repeated 5 times. Two times in 2011 and 3 times in 2012. After averaging the temporal correlation out I composed the following model for the abundance: model<-lme(abundance~continous_explanatory_variable,random=~1|island/site/plot/trap,method="REML") This works fine but I have problems making a model that allows the temporal component to stay in. How can I do this using the function lme? I know with lmer I could do this: model2<-lmer(abundance~continous_variable+(1|island/site/distance/triplet)+(1|year/round)) but I really want to use the function lme. How can I insert multiple levels of grouping in lme? Any help is very much appreciated! Best, Thomas ______________________________________ Dr Thomas Tscheulin Laboratory of Biogeography and Ecology University of the Aegean Department of Geography University Hill GR-81100 Mytilene Greece Tel.: +30 22510 36463 (or 36423) Fax: +30 22510 36423 Email: [email protected]<mailto:[email protected]> Laboratory website: http://www2.aegean.gr/lab_biogeography-ecology ISI ResearcherID: http://www.researcherid.com/rid/B-9722-2011 Google Scholar Profile: http://scholar.google.com/citations?user=hKmpu-EAAAAJ "Ï óêïðüò ôçò öýóçò äåí åßíáé ç äéáéþíéóç ôïõ áíèñþðéíïõ åßäïõò áëëÜ ç äéáóöÜëéóç ôçò âéïðïéêéëüôçôáò ôùí åéäþí" Èåüöñáóôïò (372-287 ð.×.) [[alternative HTML version deleted]]
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