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st: Usage of dprobit - std errors of marginal effects and use in low success samples


From   Dana Chandler <dchandler@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: Usage of dprobit - std errors of marginal effects and use in low success samples
Date   Fri, 21 Aug 2009 11:12:17 -0500

Hello statalist,

I have two questions about the usage of dprobit: the first regarding
standard errors of marginal effects, the second on using marginal
effects on phenomena that have extremely low successes.

I recently employed a dprobit model to try and estimate the marginal
effects. I noticed that when you divide the coefficients by the
standard errors, you don't get the z-score at the right. In fact, that
z-score is the same as if you had run a probit. How can one determine
the significance level of these marginal effects (dFdx)s?

When using the marginal effects, I know that the default is to
estimate the marginal effects at the mean of all the covariates...
since I have an extremely low success rate in the sample, all of these
marginal effects are something on the order of x.x to the 10^(-9) or
lower making interpretation difficult. If I have one or two variables
that are really powerful in predicting success, might it be worthwhile
to estimate the marginal effects at high values of that variable ?
Would I get higher estimates of the other Xs if I condition on the X
that is most important? Can statalisters suggest any other strategies?

Also, although I don't think it's important, in all cases I've
employed the "asis" option.

Thanks in advance for all of your help,
Dana Chandler
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