Hi there!I’m trying to fit a linear mixed model. I have three locations (Summits: MAC, MAM, FEM), for each location I have 16 plots nested within the four directions (N,S,E,W -> four plots per direction). For each plot I measured an indicator S in two time steps (2001=A and 2012=B). I would like to know if the indicator S significantly changed between 2001 and 2012.I performed this model:highsummits.model2<-lmer(S~time + time+ (1+time|plot_id)+(1+time|Direction)+(1+time|Summits), data = highsummits2).S is the response variable, time is the predictive variable, plot_id is the subject of the analysis, Direction and Summits are both two random factors. Also, I have both random intercept and slope.Does the model sounds good?Thanks to all!
                                                                                                                                
Ludovico
Frate

PhD student (University of Molise - Italy)
Environmetrics Lab
http://www.distat.unimol.it/STAT/environmetrica/organico/collaboratori/ludovico-frate-1
Department of Biosciences and Territory - DiBT
Università del Molise.
Contrada Fonte
Lappone, 
86090 -  Pesche (IS)
ITALIA.
Cel: ++39
3333767557
Fax: ++39 (0874) 404123
E-mail ludovico.frate@unimol.it
ludovicofrate@hotmail.it
 		 	   		  
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