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st: Marginal efects after ologit with jack knife weights


From   Tammy Leonard <tcl051000@utdallas.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: Marginal efects after ologit with jack knife weights
Date   Tue, 31 May 2011 06:16:27 -0500

Hello,

I am trying to estimate marginal effects for an ordered logit regression
where jackknife weights are specified via svyset.  I issue the command:
margins, dydx(*) predict(outcome(1)) vce(unconditional)

And it returns the error message ³vce(jackknife) is not supported².  Is
there a way to obtain marginal effects when the survey design specifies
jackknife weights? (I am using HINTS data.)

In a further attempt to obtain marginal effects, this time at the sample
mean (so vce(unconditional) is not necessary) I issue the command:
margins, dydx(*) predict(outcome(1)) atmeans

Which returns the result that the marginal effects are not estimable.
However, using the old mfx command (which defaults to the atmeans
calculation), marginal effects are quickly estimated. What difference in the
two algorithms is causing this discrepancy?  Are the results of mfx valid?

Thanks for any and all help!

Best,

Tammy








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