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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 […]
Is blogging better than publishing?
This week I started with the intension of writing about the use of Mata for analysing the Poisson regression problem that has occupied this blog for the last month. Before preparing the Mata program, I went back to my Stata code to use it as a guide and when I did so, I noticed that […]
Poisson regression with two random effects: WinBUGS, OpenBUGS and JAGS Options
In my last posting (available here) I described Stata programs that call WinBUGS, OpenBUGS or JAGS to fit a Poisson regression model with two random effects. WinBUGS, OpenBUGS and JAGS make automatic choices about the samplers that they use and in my previous comparison I accepted the defaults offered by those programs. This week I want to look […]
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 […]
Poisson regression with two random effects: Improving performance
Last time I analysed the epilesy data taken from Thall and Vail(1990). The model involved a Poisson regression with two random effects and I showed how this can be programmed in Stata by storing the values of the random effects in Stata variables rather than in a Stata matrix. However, the resulting do file was […]
Poisson regression with two random effects
Here we go again There has been quite a long gap since my last post because over the New Year and for a large part of January I was visiting my daughter who is working in Colombia. It was my first time in South America and I was immediately struck by the beauty and the vitality […]
JAGS with Stata III
Merry Christmas This will be my last posting before Christmas and in January I will be abroad for a few weeks so I will not be posting again until February. I have several topics in mind for the new year, including more on JAGS, a discussion of the use of Stan and more on using […]
JAGS with Stata II
This week I want to take a more detailed look at the use of JAGS with Stata and in particular I want to contrast JAGS with WinBUGS by analysing the biopsy data that I described last time. This posting really needs to be read in sequence with the previous two. Before I start on the comparison, let […]
Modelling heart biopsies
Last week I introduced the JAGS program as an alternative to WinBUGS and this week I started with the intention of comparing JAGS and WinBUGS using a sample dataset. I decided to base the comparison on the biopsy example taken from the WinBUGS help files. Predictably, by the time that I had explained the model and fitted it […]
JAGS with Stata
WinBUGS and OpenBUGS are just two of a growing number of blackbox programs for performing Bayesian analysis. Others include, JAGS (http://mcmc-jags.sourceforge.net/), Stan (http://mc-stan.org/) and BiiPS(https://alea.bordeaux.inria.fr/biips/doku.php). Of these, the program that is closest in style to WinBUGS and OpenBUGS is JAGS; it has a similar structure and it uses very similar samplers. So it should be easy to modify the […]
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