Poisson regression with two random effects: MCMC by data augmentation Part II
Most of my postings are based on bits of code that were produced for other reasons; perhaps for my teaching or for my research or sometimes they are left over from when I was writing the book on Bayesian Analysis with Stata. So typically I spend a couple of hours each week on the blog; […]
Poisson regression with two random effects: MCMC by data augmentation
When I restarted this blog after the Christmas break I resolved to concentrate more on straightforward applications of Bayesian analysis with Stata; I believe that is what most Stata users are interested in. A couple of months in and I am going to ignore my good intensions and discuss a topic that I considered too […]
Poisson regression with two random effects: Better Mata code
Last time I presented a basic Mata program for fitting a Poisson model with two random effects to some epilepsy data. The program was faster that its Stata equivalent but slower than WinBUGS and the mixing was quite poor. This week I will try to improve the performance of the Mata program. It would make sense […]
Poisson regression with two random effects: Mata
In recent postings I have analysed the epilepsy trial of Thall and Vail using Stata, WinBUGS, OpenBUGS and JAGS and after a brief diversion last week I now want to move on to analysing the data using Mata. Previously we saw that an analysis in Stata takes about 6 minutes, while the BUGS-like programs take […]
Poisson regression with two random effects: WinBUGS, OpenBUGS or JAGS
Over the last two weeks I have been looking at the analysis of the epilespy trial data taken from Thall and Vail (1990). So far I have concentrated on a Bayesian analysis of those data using Stata alone, but this model involves Poisson regression with two random effects, so it is quite complex and it takes a […]
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