Dear all,

I would be grateful if you could help me with the following question 
using lmer()
I want to test the effect of a categorical factor with two levels 
(called 'couleurs')
The only random factor is 'nom'.

I first start with all random effects (I only report the lines for the 
random effects):
Linear mixed model fit by maximum likelihood
Formula: lRT ~ couleurs + (1 + couleurs | nom)
Random effects:
 Groups          Name            Variance  Std.Dev. Corr  
 nom              (Intercept)     0.1376693 0.371038       
                      couleurs1       0.0030358 0.055098 *-1.000 *
 Residual                             0.5118424 0.715432       
Number of obs: 7927, groups: nom, 10


Then, I remove the random effect of 'couleurs'  with the following result:

Linear mixed model fit by maximum likelihood
Formula: lRT ~ couleurs + (1 | nom)
   Data: jb

Random effects:
 Groups       Name            Variance Std.Dev.
 nom          (Intercept)     0.11768  0.34304
 Residual                         0.51263  0.71598
Number of obs: 7927, groups: nom, 10

I then compare the two models and see that I should go with the first 
model Df=6:
 > anova (jb.lmer1, jb.lmer2)
Data: jb
Models:
jb.lmer2: lRT ~ couleurs + (1 | nom)
jb.lmer1: lRT ~ couleurs + (1 + couleurs | nom)
         Df   AIC   BIC  logLik  Chisq Chi Df Pr(>Chisq)  
jb.lmer2  4 17259 17287 -8625.4                           
jb.lmer1  6 17251 17293 -8619.4 12.078      2   0.002384 **


My questions are the following:

a/ is it really a statistical (or numerical) problem to have a -1 
correlation in the model that I should keep?

b/ is it possible to remove the correlation between Intercept and 
Couleurs, as I would do if Couleurs were not a categorical factor?


Thanks in advance,

Eric Castet




-- 

Eric Castet

Institut de Neurosciences Cognitives de la Méditerranée -- INCM CNRS

31 chemin Joseph Aiguier

13402 Marseille cedex 20 (France)

tel : (+33)(0)4-91-16-43-34

fax : (+33) (0)4-91-16-44-98

UMR 6193 du CNRS

Université Aix-Marseille II

http://www.incm.cnrs-mrs.fr/equipedyva.php

http://www.incm.cnrs-mrs.fr/pperso/ecastet.php

 


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