On Thu, 3 Apr 2003, mganz wrote:
Gary,
Since -estsimp- does not support the -svyreg- command, I wonder how to
encorporate corrections for survey design within the clarify package. Since
clarify really computed standard errors and CIs using the empirical
distribution of the simulations, does it really matter? How about survey
weights if I wanted to weight the regression?
If you are estimating causal effects, then you almost surely do not need
the sample weights. The only issue is if the weights are a potential
omitted variable that is causally prior to your key causal variable and
correlated with it and the dependent variable. In that case, you can
correct for the weights by simply including the weights (or some function
of them) as an additional explanatory variable.
You can also take the observation-level simulations and combine them in
any way you see fit after estimate, and you might wish to include the
weights at that stage.
Either way, you can use clarify as is.
The advantage of incorporating sample weights in the estimation stage is
for some additional efficiency, but that is not an option presently.
Gary
: Gary King, King(a)Harvard.Edu
http://GKing.Harvard.Edu :
: Center for Basic Research Direct (617) 495-2027 :
: in the Social Sciences Assistant (617) 495-9271 :
: 34 Kirkland Street, Rm. 2 HU-MIT DC (617) 495-4734 :
: Harvard U, Cambridge, MA 02138 eFax (928) 832-7022 :
Thanks,
Michael
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