Dynamic random effects model

I am trying to estimate a model of third party intervention into civil war.  The data is panel data structure.  The unit of analysis
is civil war year.  For each civil war year my dependent variable is coded 0=no intervention and 1=intervention.  I want to use a
lagged dependent variable as an independent variable and i am including other variables such as type of war conventional=0,1 dummy
irregular 0,1 dummy,,, other dummy variables such as cold war period, and other variables such as state strength .   Some of my independent variables are time invariant or slow moving.   Because i want to include lagged dependent variable rules out a fixed effect,
therefore I was thinking of using random effects.    Any suggestion on how to model this?

I am inexperienced with these models, I will appreciate any help I can get

Thank you

jcm
On Thu, Jan 29, 2009 at 8:04 AM, Ben Bolker <bolker at ufl.edu<mailto:bolker at ufl.edu>> wrote:
Joseph Magagnoli <jcm331 <at> gmail.com<http://gmail.com/>> writes:

All R experts,
How do I fit a dynamic Random effects model with a binary dependent variable
in R
Thanks
JCM

 You haven't given us nearly enough information to go on.
If you're talking about something like a state-space model with
a binary response, I would probably say your best bet is
a Bayesian approach, prob. via JAGS/R2jags or WinBUGS/R2WinBUGS.
(A lot) more context will give a higher probability of a useful
answer.

 good luck
   Ben Bolker