I am running the following multilevel model with a binary outcome with mcmc:

runmlwin unique_dipstick_avai2cats cons private secondaryhosp paed_mother_child centered_unique_turn19_time centered_exp_capita gov VHIOOP, level2(country2: cons) level1(id:) discrete(distribution(binomial) link(logit) denom(cons) pql2) nopause

I have 504 observations (level 1) and 29 second level units.runmlwin unique_dipstick_avai2cats cons private secondaryhosp paed_mother_child centered_unique_turn19_time centered_exp_capita gov VHIOOP, level2(country2: cons, residuals(u)) level1(id:) discrete(distribution(binomial) link(logit) denom(cons) pql2) mcmc(burnin(1000) chain(550000)) initsprevious nopause nogroup

My outcome is whether urine dipstick are available (0=no; 1=yes). I am using mcmc because the response proportion is extreme (0=42/504; 1=462/504).

I checked the diagnostics and following the Raftery-Lewis and Brooks-Drappers diagnostics I re run the model with 550,00 iterations.

Some of the odds ratio and Standard deviations are huge for 2 of the variables (OR for gov:1156.948 , and VHIOOP:13730.1), and the 95%Credible interval is smaller than the parameter for VHIOOP: 95%CI = 0.050643 - 164.6105

Burnin = 1000

Chain = 550000

Thinning = 1

Run time (seconds) = 156

Deviance (dbar) = 214.32

Deviance (thetabar) = 195.41

Effective no. of pars (pd) = 18.91

Bayesian DIC = 233.23

Disptick_available OR Std. Dev ESS P [95% Cred.Int]

gov 1156.948 24956.07 8874 0.003 2.891191 2926.618

VHIOOP 13730.1 1120034 14575 0.307 0.050643 164.6105

Can anyone explain why is this happening, and what should I do to get correct OR and 95%CI?

Thank you!

Manuel