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
generalized mixed model + mcmcsamp
2 messages · Thomas Mang, Ben Bolker
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