fitting mixed effects logistic regression with weights
Dear Ben, Thank you for your prompt response. Does MCMCglmm provide the usual REML/RSPL estimates or Bayesian estimates for the fixed effects? I mean are the coefficient and SE estimates REML/RSPL or Bayesian? I want to be sure what I am getting. Mulugeta
From: r-sig-mixed-models-bounces at r-project.org [r-sig-mixed-models-bounces at r-project.org] On Behalf Of Ben Bolker [bbolker at gmail.com]
Sent: Friday, June 10, 2011 4:33 PM
To: r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] fitting mixed effects logistic regression with weights
Sent: Friday, June 10, 2011 4:33 PM
To: r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] fitting mixed effects logistic regression with weights
On 06/10/2011 04:24 PM, Gebregziabher, Mulugeta wrote:
> 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'.
As the error message suggests (obliquely!), mcmcsamp() does not yet
work for GLMMs (i.e. [g]lmer with 'family' specified). Furthermore,
quasi-likelihood fitting no longer works with the latest releases of
lme4 (because the author decided that he didn't really understand what
it was doing, hence safer to omit it).
Have you considered MCMCglmm, or parametric bootstrapping
(help("simulate-mer")) ?
See more below:
>
> 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
> __________________________________________ Mulugeta Gebregziabher,
> PhD Assistant Professor Division of Biostatistics and Epidemiology
> 135 cannon St. Suite 303 Charleston, SC 29425 Tel: 843-876-1112; Fax:
> 843-876-1126 E-mail: gebregz at musc.edu
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
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