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Date: | Sun, 17 Jan 2010 12:57:34 -0500 |
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Per Box-Steffensmeier and Jones's recommendation for discrete-time
data (Event History Modeling), why not use a conditional logistic
regression model with stratification on duration? This approach would
be really flexible with regard to the number of observations per panel.
-Jay
Sent from my iPhone
On Jan 17, 2010, at 6:14 AM, Robert Johns <[log in to unmask]>
wrote:
> Dear all,
>
> I've got a query about the Cox hazard models used by Gartner (APSR,
> 102:1 (2008), pp. 95-106). He runs a panel experiment in which
> monthly casualty rates during a conflict are manipulated, and the
> hazard models gauge the impact of these manipulations on the
> duration of public support for military action. Gartner's panel has
> ten waves, i.e. ten opportunities to choose between leaving the
> troops in or bringing them home. In planning a similar design, I
> was wondering about the amount of flexibility available concerning
> this number of waves. I guess that, under the model's assumptions,
> duration is a continuous variable, but obviously it is necessarily
> discrete in this kind of design. So can anyone suggest a rough rule
> on how many time periods would be needed to estimate such hazard
> models accurately?
>
> Many thanks,
>
> Rob Johns.
>
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