Hi, I have fitted a generalized linear mixed effects model using lmer (library lme4), and the family = quasibinomial. I have tried to obtain a MCMC sample, but on calling mcmcsamp(model1, 1000) I get the following error which I don't understand at all: Error in .local(object, n, verbose, ...) : Update not yet written traceback() delivers: 4: .Call(mer_MCMCsamp, ans, object) 3: .local(object, n, verbose, ...) 2: mcmcsamp(model1, n = 1000, verbose = FALSE) 1: mcmcsamp(model1, n = 1000, verbose = FALSE) which again doesn't particularly help me. R is 2.8.1 under Windows, lme4 clean installed just today. Before the model is fitted I just read in data, and transform some variables. No other library is loaded. Any ideas ? thanks, Thomas
Thomas Mang <Thomas.Mang <at> fiwi.at> writes:> > Hi, > > I have fitted a generalized linear mixed effects model using lmer > (library lme4), and the family = quasibinomial. I have tried to obtain a > MCMC sample, but on calling mcmcsamp(model1, 1000) I get the following > error which I don't understand at all: > > Error in .local(object, n, verbose, ...) : Update not yet written > > traceback() delivers: > 4: .Call(mer_MCMCsamp, ans, object) > 3: .local(object, n, verbose, ...) > 2: mcmcsamp(model1, n = 1000, verbose = FALSE) > 1: mcmcsamp(model1, n = 1000, verbose = FALSE) > > which again doesn't particularly help me. > > R is 2.8.1 under Windows, lme4 clean installed just today. > Before the model is fitted I just read in data, and transform some > variables. No other library is loaded. > > Any ideas ? >Bad news: mcmcsamp is not working at present even for LMMs, has never worked (so far) for GLMMs, and the author (Doug Bates) says he's not sure there's a coherent way to deal with quasi- models in the mcmcsamp framework (since it doesn't correspond to any well-defined distribution). You may want to browse the archives of the r-sig-mixed-models list, and/or request more information there. Ben Bolker
Hi Thomas/Ben, This model ca be MCMCed using MCMCglmm by specifying "multinomial2" (i.e. binomial) in the family argument. MCMCglmm by default, fits a residual in the linear model to soak up extra-binomial variation, which is similar in motivation to quasi models. Cheers, Jarrod Hi, I have fitted a generalized linear mixed effects model using lmer (library lme4), and the family = quasibinomial. I have tried to obtain a MCMC sample, but on calling mcmcsamp(model1, 1000) I get the following error which I don't understand at all: Error in .local(object, n, verbose, ...) : Update not yet written traceback() delivers: 4: .Call(mer_MCMCsamp, ans, object) 3: .local(object, n, verbose, ...) 2: mcmcsamp(model1, n = 1000, verbose = FALSE) 1: mcmcsamp(model1, n = 1000, verbose = FALSE) which again doesn't particularly help me. R is 2.8.1 under Windows, lme4 clean installed just today. Before the model is fitted I just read in data, and transform some variables. No other library is loaded. Any ideas ? thanks, Thomas -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.