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st: margins command: adjusting predictions with means of a group not esimated

From   Doug Hess <>
Subject   st: margins command: adjusting predictions with means of a group not esimated
Date   Thu, 18 Aug 2011 09:54:55 -0400

It was hard to come up with a succinct title for this email, and it
may be hard to write about this problem (writing about complex
adjusted margins is like thinking through one of those variants of
chess where you play on multiple inter-related boards...challenging in
a way that is fun up until you become frustrated and want to jab forks
in your eyes), but here goes:

I have a logistic model of an outcome (0=nonevent, 1=event) on the
household level with predictors at the household level and (U.S.)
state level (set aside clustering issues for the moment). Most of the
state level predictors are continuous, but all the household-level
ones are binary. After running the model, I want to say what state A's
rate of the event is if it had the population characteristics of State
B (the state with the lowest prevelance of the outcome), first holding
state A's state-level variables as they are, and then also giving
state A the state-level variables of state B.

However, other than filling in lots and lots of -at(x=(...))- options,
I am not sure if there's a way to do this. The problem seems to be
that since I don't have the states in the model I cannot use them to
control the means assigned to a state (I guess I could add them as
indicators, but there are reasons not to have fixed effects). The
-over( )- option doesn't seem to do all of this, but perhaps I am
missing a creative way to use some of the more complex contrast
commands or operators, or other options.

Perhaps just doing completing lots of -at()- options is the only way to go?

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