You can definitely do it using the covariance but its waaay easier to
just simulate. Simulate 1000 times from each dataset, combine the
simulations and then take the SE as normal.
Brandon
On Wed, Apr 27, 2011 at 1:43 PM, James Conran <jkconran(a)mit.edu> wrote:
Hi all,
Can anyone tell me how to calculate appropriate multiple imputation standard errors for
the marginal effect of an independent variable that is part of an interaction term?
That is, the basic model is:
Y = beta1*x1 + beta2*x2 + beta3*x1*x2.
The standard errors for each of the three coefficients can be calculated with the usual
MI adjustment but to calculate the standard error of the marginal effect you need to deal
somehow with the covariance term between x1 and x2.
Does anyone know whether the covariances can be adjusted in a similar way to what happens
with the standard errors or do we have to calculate the standard error of the marginal
effect for each dataset/regression and then perform the SE adjustment?
Cheers,
James
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