On Thu, Feb 26, 2009 at 10:58 AM, Tanja Srebotnjak <tan...@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: tan...@u.washington.edu<mailto:tan...@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@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]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
