[R-sig-ME] Calcul of confidence intervals of estimate coefficient by a logistic regression with random effect

[Laetitia ETIENNE]

Hello,

I would like to know how can i calculate confidence intervals of coefficients estimate with a logistic regression with random effect (i use the lme4 package for my glmm) ?

Example:

> y<-cbind(total-morts,morts)
			
> library(lme4)			
> modF<-glmer(y~sppNB+Fmyc+(1|Bloc),family=binomial(link="logit"))			
> drop1(modF,test="Chisq")			
Single term deletions			
Model:			
y ~ sppNB + Fmyc + (1 | Bloc)			
       Df    AIC     LRT  Pr(Chi)   			
<none>    66.680                    			
sppNB   4 73.721 15.0409 0.004617 **			
Fmyc    1 68.943  4.2636 0.038937 * 			
			
			
> summary(modF)			
Generalized linear mixed model fit by the Laplace approximation 			
Formula: y ~ sppNB + Fmyc + (1 | Bloc) 			
   AIC   BIC logLik deviance			
 66.68 71.64 -26.34    52.68			
Random effects:			
 Groups Name        Variance Std.Dev.			
 Bloc   (Intercept) 0.31936  0.56512 			
Number of obs: 15, groups: Bloc, 3			
			
Fixed effects:			
            Estimate Std. Error z value Pr(>|z|)   			
(Intercept) -4.11405    1.85861  -2.213  0.02686 * 			
sppNBjuncea  1.89728    1.11708   1.698  0.08943 . 			
sppNBMucuna  2.65001    1.87301   1.415  0.15712   			
sppNBspecta  2.72581    1.01592   2.683  0.00729 **			
sppNBVigna   1.90306    1.17422   1.621  0.10508   			
Fmyc         0.04048    0.01990   2.034  0.04192 * 	

I would like to know the confidence interval of the estimate coefficent of "Fmyc".		



thanks,

Laetitia Etienne