On Thu, Feb 26, 2009 at 10:58 AM, Tanja Srebotnjak
<tanjas at u.washington.edu> wrote:
I'm resending this message because I did not include a subject line in my first posting.
Also, it is generally more effective to send questions about lmer/glmer to the R-SIG-Mixed-Models list, which I am cc:ing on this reply.
Hello,
I'm trying to fit a generalized linear mixed model to estimate diabetes prevalence at US county level. To do this I'm using the glmer() function in package lme4. I can fit relatively simple models (i.e. few covariates) but when expanding the number of covariates I usually encounter the following error message.
gm8 <- glmer(DIAB05F~AGE+as.factor(SEX)+poolt+poolx+poverty+fastfood+(1|as.factor(diab$fips)), family = binomial(link="logit"), data = diab, doFit=TRUE)
Error in validObject(.Object) : ? invalid class "mer" object: Slot Zt must by dims['q'] ?by dims['n']*dims['s'] Getting that error message from this model is peculiar. I couldn't actually say what might be happening without trying the fit myself. I would suggest setting doFit = FALSE but I think that this error would be encountered even with doFit = FALSE. Again, it would be hard to say exactly what is happening here.
In the above, the response is person-level diabetes status as a function of AGE=age, SEX=sex, poolt=average county diabetes prevalence for previous years, poolx=pooled county diabetes prevalence for counties with similar age, sex, race, and income structure, poverty=county poverty rate, fastfood=number of fastfood places per 100,000 people in the county, and a county random effect.
If I leave out fastfood, the model gets at least fitted - although it doesn't converge (yet):
The version of lmer currently under development tries to address that problem. The optimization of the parameter estimates is performed in a slightly different way that will, I hope, provide smoother convergence. If your data are not restricted and you would be willing to send me a copy of the diab data frame I could check what happens on that version (or you could install the development version yourself but that is a non-trivial undertaking). If you can send the data the best way to send it is to create an R data file as save(diab, file = "diab.rda") and send the file diab.rda
Warning message: In mer_finalize(ans) : false convergence (8)
Frequently that is a sign of an overspecified model.
I would be grateful for any advice on what the problem could be and how to resolve it.
Thanks,
Tanja
Tanja Srebotnjak, PhD, MSc, Dipl. Stat. Postgraduate Fellow Institute for Health Metrics and Evaluation University of Washington 2301 5th Ave, Suite 600 Seattle, WA 98121 Email: tanjas at u.washington.edu<mailto:tanjas at u.washington.edu> Tel: +1-206-897-2866 www.healthmetricsandevaluation.org<http://www.healthmetricsandevaluation.org> From: Tanja Srebotnjak Sent: Thursday, February 26, 2009 12:17 AM To: 'r-help at r-project.org' Subject: Hello, I'm trying to fit a generalized linear mixed model to estimate diabetes prevalence at US county level. To do this I'm using the glmer() function in package lme4. I can fit relatively simple models (i.e. few covariates) but when expanding the number of covariates I usually encounter the following error message. gm8 <- glmer(DIAB05F~AGE+as.factor(SEX)+poolt+poolx+poverty+fastfood+(1|as.factor(diab$fips)), family = binomial(link="logit"), data = diab, doFit=TRUE) Error in validObject(.Object) : ?invalid class "mer" object: Slot Zt must by dims['q'] ?by dims['n']*dims['s'] In the above, the response is person-level diabetes status as a function of AGE=age, SEX=sex, poolt=average county diabetes prevalence for previous years, poolx=pooled county diabetes prevalence for counties with similar age, sex, race, and income structure, poverty=county poverty rate, fastfood=number of fastfood places per 100,000 people in the county, and a county random effect. If I leave out fastfood, the model gets at least fitted - although it doesn't converge (yet): Warning message: In mer_finalize(ans) : false convergence (8) I would be grateful for any advice on what the problem could be and how to resolve it. Thanks, Tanja ? ? ? ?[[alternative HTML version deleted]]
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