fitting mixed effects logistic regression with weights

Dear all,

I have been trying to fit a logistic regression model with random
intercept for survey sampled data using the lmer in the lme4 package.
I also want to get HPD intervals. I tried family=binomial as well as
family=quasibinomial. I am encountering the following errors. "Eror
in .local(object, n, verbose, ...) : Update not yet written" and
"Error in HPD interval(mcmcsamp(fit, 1000)) :   error in evaluating
the argument 'object' in selecting a method for function
'HPDinterval'.

Does anyone know how to go around this problem? Thanks.

library(lme4)

Loading required package: Matrix Loading required package: lattice 
Attaching package: 'Matrix' The following object(s) are masked from
'package:base': det Attaching package: 'lme4' The following object(s)
are masked from 'package:stats': AIC

attach(cohort)

f  <- a1cge8 ~  (1|id)   +  time  +  nhb  + hispanic  + other  +
male  + mstat  +svcpct   +urban   +  comor1   +comor2  + comor3


est        <- round(slot(summary(fit), "coefs")[,1], digits=2) t
<- slot(summary(fit), "coefs")[,3] df      <- c(1, 1, 3, 3, 3, 1,
1, 1, 1, 3, 3, 3) p.value    <- ifelse(t<0, round(pt(t, df=df),
digits=3), round(1-pt(t, df), digits=3) ) se         <-
round(slot(summary(fit), "coefs")[,2], digits=4) ci         <-
HPDinterval(mcmcsamp(fit, 1000))

Error in .local(object, n, verbose, ...) : Update not yet written 
Error in HPDinterval(mcmcsamp(fit, 1000)) : error in evaluating the
argument 'object' in selecting a method for function 'HPDinterval'

lower <- round(ci$fixef[,1], digits=2)

Error: object 'ci' not found

upper <- round(ci$fixef[,2], digits=2)

Error: object 'ci' not found