[R-sig-ME] how to know if random factors are significant?

[Leonel Arturo Lopez Toledo]

Dear all:
I’m new to mixed models and I’m trying to understand the output from “lme” in the nlme 
package. I hope my question is not too basic for that list-mail. Really sorry if that 
is the case.
Especially I have problems to interpret the random effect output. I have only one 
random factor which is “Site”. I know the “Variance and Stdev” indicate variation by 
the random factor, but are they indicating any significance? Is there any way to 
obtain a p-value for the random effects? And in case is not significant, how can I 
remove it from the model? With “update (model,~.-)”? 

The variance in first case (see below) is very low and in the second example is more 
considerable, but should I consider in the model or do I remove it?

Thank you very much for your help in advance.

EXAMPLE 1
Linear mixed-effects model fit by maximum likelihood
 Data: NULL 
       AIC      BIC    logLik
  277.8272 287.3283 -132.9136

Random effects:
 Formula: ~1 | Sitio
         (Intercept) Residual
StdDev: 0.0005098433 9.709515

EXAMPLE 2
Generalized linear mixed model fit using Laplace 
Formula: y ~Canopy*Area + (1 | Sitio) 
   Data: tod 
 Family: binomial(logit link)
   AIC   BIC logLik deviance
 50.93 54.49 -21.46    42.93

Random effects:
 Groups Name        Variance Std.Dev.
 Sitio  (Intercept) 0.25738  0.50733 
number of obs: 18, groups: Sitio, 6


Leonel Lopez
Centro de Investigaciones en Ecosistemas-UNAM
MEXICO




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