Dear R users: I am using hierchical modeling for a response varible (ordinal) given by patients for each doctor. My MCMC run with MCMMCglmm ( thin=20,nitt=208000,burnin=24000, family='ordinal') still can't have all the parameters pass the GEWEKE diagnosis test.
I am trying to find the reason for the slow convergence. Can the reason be 20 out of 50 doctors having 5 or less response (6 docs with 1 , 4 docs with 2, 3 docs with 3, 4 docs with 4 ,2 docs with 5 responses)? However, small sample sizes are the reason for bayesian modeling in the first place. Can the reason be there are no strong variation among the doctors to start with? Any thoughts or suggestions will be appreciated. Ping ______________________________________________ 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.
