You should bootstrap on cities or any random effect group that you have in
your model.
 On Jun 15, 2012 5:23 AM, "Joe King" <joeking1809@yahoo.com> wrote:

> Dear all
>
> I am attempting to obtain a bootstrap confidence interval for the random
> effect in a simple (random intercept) model using glmer.
>
> The problem I have is that the interval I obtain consistently does not
> contain the value I am trying to get an interval for ! For example I get
> the following output when I run glmer on the full data:
>
> Generalized linear mixed model fit by the Laplace approximation
> Formula: wg~ (1 | city)
>    Data: dt
>    AIC   BIC logLik deviance
>  10115 10131  -5056    10111
> Random effects:
>  Groups   Name        Variance Std.Dev.
>  city(Intercept)       0.14155  0.37623
> Number of obs: 19318, groups: city, 218
>
> Fixed effects:
>             Estimate Std. Error z value Pr(>|z|)
> (Intercept) -2.58566    0.04045  -63.93   <2e-16 ***
>
> So I am trying to obtain the confidence interval for random effect
> variance : 0.14155.  Yet, the confidence interval I got was  0.2839343 ,
> 0.3534999. Moreover, the value in every one of the bootstrap replicates is
> greater than 0.14155. For example, the output from glmer in the last
> replicate the last bootstrap replicate was
>
> Generalized linear mixed model fit by the Laplace approximation
> Formula: wg~ (1 | city)
>    Data: sam
>    AIC   BIC logLik deviance
>  10480 10496  -5238    10476
> Random effects:
>  Groups   Name        Variance Std.Dev.
>  city(Intercept)     0.32769  0.57245
> Number of obs: 19318, groups: city, 217
>
> Fixed effects:
>              Estimate Std. Error z value Pr(>|z|)
> (Intercept) -2.58779    0.05142  -50.33   <2e-16 ***
>
> There are no missing data. This is the code I have used to obtain the
> interval:
>
> for (i in 1:k) {
>     sam <- dt[sample(nrow(dt), replace=T, size=nrow(dt)), ]
>     m1<- glmer(wg~(1|city), data=sam, family=binomial)
>     bs[i] <- VarCorr(m1)$city[1]
> }
> quantile(bs,c(0.025,0.975))
>
> Could anyone suggest why this is happening, and what I might be able to do
> about it ?
>
> Thank you
> JK
>
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