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@ufl.edu> wrote:

>  Joseph Magagnoli <jcm331 <at> 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
>
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