[R] Hoe to get RESIDUAL VARIANCE in logistic regression using lmer

tomal tomal at live.it
Thu Apr 30 12:10:16 CEST 2009


Hello everybody, 
using the lmer function, I have fitted the following logistic mixed
regression model on an experimental data set containing one fixed factor
(Cond) and three random variables (Sito, Area, Trans): 


> model<-lmer(Caul~Cond+(1|Sito)+(1|Area)+(1|Trans), data=dataset,
> family=binomial) 

this is the output: 

> summary(model) 
Generalized linear mixed model fit by the Laplace approximation 
Formula: Caul ~ Cond + (1 | Sito) + (1 | Area) + (1 | Trans) 
   Data: dataset 
   AIC   BIC logLik deviance 
 548.7 573.7 -268.3    536.7 
Random effects: 
 Groups Name        Variance  Std.Dev. 
 Trans  (Intercept) 3.2313398 1.797593 
 Area   (Intercept) 0.0000000 0.000000 
 Sito   (Intercept) 0.0047151 0.068667 
Number of obs: 480, groups: Trans, 48; Area, 12; Sito, 2 

As you can see the residual variance is missing. Can anybody tell me why?
Does anybody know how can I get it? 

Thank you for your attention, I wish somebody can help me. 

Have a nice day, best regards, 
  
Tommaso Alestra 
-- 
View this message in context: http://www.nabble.com/Hoe-to-get-RESIDUAL-VARIANCE-in-logistic-regression-using-lmer-tp23313330p23313330.html
Sent from the R help mailing list archive at Nabble.com.




More information about the R-help mailing list