How to implement credible 95% interval for median odds ratio using JAGS?

As described in Merlo et al (J Epidem Comm Health 2006), the 95% credible interval for MOR is calculated using MCMC. MOR is defined as $\exp(\sqrt{2\sigma^2}\times 0.675)$, where $\sigma$ is the level-2 variance of the random intercept $u$ from a null model of a hierarchical logistic regression.

Does anyone have an idea of how to write a program for an Markov chain Monte Carlo to calculate the standard error of the median odds ratio (MOR) using rjags?
My dependent variable is outcome(alive/dead) and the clustering (level2)variable is Hospital. There are 140 hospitals and would like to see variations in outcome between hospitals. Other risk factors will be included later as independent level1 variables.

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A lot more information is necessary such as: the regression model (e.g. how many variables and observations you have), the prior distributions, a link to the paper you mention ... Otherwise the answer is the Reference Manual. –  user10525 Jul 13 '12 at 16:08
Start with johnmyleswhite.com/notebook/2010/08/20/… and let us know about any problem you face. 1. Also see rpubs.com/jeromyanglim/rjags_normal_distribution –  Stat-R Jul 13 '12 at 16:24
Hi Omar, I just approved your anonymous edit - note that you have full edit privileges over your own questions so, if you log in, you do not need to wait for approval when editing your question. –  Macro Jul 14 '12 at 13:07
What do you want to do with the standard error ? Can't you be satisfied with a confidence/credibility interval ? –  Stéphane Laurent Jul 14 '12 at 13:26
yes it's for the credibility interval,I thought mcmc provide standard error only, either would do for me . It just that I have no experience in programming MCMC. the paper mentioned that mLwin does it but I don't have the software, that's why I thought of rJags. This is for interpreting result with odds ratio at the level 2 rather using ICC which is not reliable for logistic regression as it is with linear multilevel. Thanks. –  Omar Jul 15 '12 at 11:15
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