help for lemr

To whom who can help me!



 I want to run an lmer with a Poisson distribution because it is abundance
 data (discrete data)named "ind_total".

 I have a nested structure which is "observations" within "localisation"
 within "site"

 The lme function would be: y~x1+x2+x3+random=1|site/localisation, data)



 Actually, with lmer function I tried :
 model_2_lmer<-lmer(ind_total~1+(1|site:localisation)+(1|site),data=donnees,m
 ethod="Laplace",family=poisson(link = "log"),na.action=na.omit)

 And a warning message appears saying:



 Error in lmerFactorList(formula, mf, fltype) :

  number of levels in grouping factor(s) 'site' is too large

 Warning messages:

 1: In site:localisation :

  l'expression num?rique a 1278 ?l?ments : seul le premier est utilis?
 (numerical expression has 1278 elements : only first is used)

 2: In site:localisation :

  l'expression num?rique a 1278 ?l?ments : seul le premier est utilis?
 (numerical expression has 1278 elements : only first is used)



 So I tried

 model_3_lmer<-lmer(ind_total~1+(1|localisation)+(1|site),data=donnees,method
 ="Laplace",family=poisson(link = "log"),na.action=na.omit)

 and it seems to work:

 Generalized linear mixed model fit using Laplace

 Formula: ind_total ~ 1 + (1 | localisation) + (1 | site)

   Data: donnees

  Family: poisson(log link)

  AIC  BIC logLik deviance

  1032 1048 -513.1     1026

 Random effects:

  Groups       Name        Variance   Std.Dev.

  site         (Intercept) 2.0538e-01 4.5319e-01

  localisation (Intercept) 5.0000e-10 2.2361e-05

 number of obs: 1278, groups: site, 40; localisation, 2



 Estimated scale (compare to  1 )  0.7704331



 Fixed effects:

            Estimate Std. Error z value Pr(>|z|)

 (Intercept)  0.15660    0.07645   2.048   0.0405 *



 Is my nested structure written right?



 Then I tried to include all my covariates and a warning message appears
 again:

 model_4lmer<-lmer(ind_total~as.factor(annee)+temp+as.factor(pluie)+foret_tot
 +superf_reelle+foret_tot*superf_reelle+as.factor(localisation)+as.factor(pic
 )+axe_1+axe_2+as.factor(traitement)+as.factor(annee)*as.factor(traitement)+(
 1|localisation)+(1|site),data=donnees,method="Laplace",family=poisson(link =
 "log"),na.action=na.omit)

 > summary(model_4lmer)

 Erreur dans asMethod(object) : matrix is not symmetric [1,2]



 I looked at my matrix and everything is ok? the only thing is I have 3 NAs
 in my response variable but I specified "na.action=na.omit"?What am I doing
 wrong!?!

 Thank you

 Claudie Desroches

 ------------

 Claudie Desroches
 ?tudiante au 2e cycle
 Chaire de recherche du Canada en ?cologie spatiale et en ?cologie du paysage
 Universit? de Sherbrooke: D?partement de Biologie
 1-819-821-8000 poste 63468
 HYPERLINK
 "mailto:claudie.desroches at usherbrooke.ca"claudie.desroches at usherbrooke.ca





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 10:48


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