[R-sig-ME] Non normal random effects

[Eric Edeline]

Here are model coeffs, which are indeed very different between the two 
models for some effects:

1> m1 at fixef
         (Intercept)          log(Slope)          
log(Width)                Temp
       64.3355546922        0.0176278497       -0.0301275431       
-3.8692860013
              log(D)       log(Compint2)      
log(Predln102)                Year
        0.0021372925        0.0023000751        0.0327498020       
-0.0294303421
         Temp:log(D)  Temp:log(Compint2) Temp:log(Predln102)           
Temp:Year
       -0.0032965368       -0.0013422775       -0.0008383696        
0.0019082777
1> m2 at fixef
         (Intercept)          log(Slope)          
log(Width)                Temp
        49.601725055        -0.113952871        -0.013659799        
-2.285783668
              log(D)       log(Compint2)      
log(Predln102)                Year
         0.023140502         0.055044993        -0.252180423        
-0.023767542
         Temp:log(D)  Temp:log(Compint2) Temp:log(Predln102)           
Temp:Year
        -0.006871451        -0.011123770         0.010086872         
0.001163320

In m1 I indeed meant "Station" within "Species". Actually, the full 
model I have selected so far is much more complex and includes several 
nested random effects + variance functions in lme:

m3<-lme(log(Length) 
~log(Slope)+log(Width)+log(Fcl)+Nb.species+Temp*log(D)+Temp*log(Compint2)+Temp*log(Predln102)+Temp*Year,
data=Data, na.action=na.omit, random=list(Species=pdDiag(form=~1), 
Strategy=pdDiag(form=~1), Method=pdDiag(form=~1),
Region=pdDiag(form=~1), Station=pdDiag(form=~1)), control=list(maxIter=100),
weights=varComb(varPower(form=~D), varPower(form=~Predln102), 
varPower(form=~Compint2)))#AIC 50945.01

Maybe this is too complex, but this is the best structure in terms of 
AIC. Still, the problem of skewed residuals from having a species effect 
remains (even as a fixed effect in simple lm models), and I really can't 
figure out why...


On 11/27/2010 07:14 PM, valerio.bartolino wrote:
> Dear Eric,
> I'm impressed by the drop in the AIC due to the 'Species' variable. I
> think it could be useful comparing the coefficients estimated for the
> fixed effects between the two models. It may be the case that they are
> rather different between m1 and m2. I would pay great attention to the
> interpretation of the effect of each variable.
>
> Hope this could help
>
> Valerio
>
>
> On Fri, 2010-11-26 at 21:04 +0100, Eric Edeline wrote:
>    
>> Dear list,
>>
>> is non normality of random effects a serious issue for inference on the
>> fixed effects? I am having a non normal random effect that tremendously
>> improves model AIC.
>>
>> Thanks!
>>
>>      
>    

-- 
Eric Edeline
Assistant Professor
UPMC-Paris6
UMR 7618 BIOEMCO
Ecole Normale Supérieure
46 rue d'Ulm
75230 Paris cedex 05
France

Tel: +33 (0)1 44 32 38 84
Fax: +33 (0)1 44 32 38 85

http://www.biologie.ens.fr/bioemco/biodiversite/edeline.html