Dear R users, I think that the question I posted yesterday was not specific enough. Apologies for this.
The question should have been: why does MCMClogit stop working if I a) set a normal prior for the intercept and b) remove all variables except for the intercept as explanatory? Example code: simulatedCase <- rbinom(100,1,0.5) simDf <- data.frame(CASE = simulatedCase) posterior_m0 <<- MCMClogit(CASE ~ 1, data = simDf, b0 = 0, B0 = 1) It should easily be possible to fit this model with the intercept part around -0.2 or so, and, in fact, when I use flat priors with posterior_m0 <<- MCMClogit(CASE ~ 1, data = simDf) this works -- and -0.2 is easily allowed by a N(0,1) prior on the intercept, so why doesn't this work any more? It this a bug, or am I simply overlooking the most obvious error? Best wishes, Alexander Düdo -- View this message in context: http://www.nabble.com/MCMClogit%3A-normal-intercept-priors-don%27t-work-tp25789993p25789993.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
