| ![](/includes/contimages/spacer.gif) |
[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]
RE: st: RE: mim: reg command
At 05:55 AM 4/27/2007, Maarten Buis wrote:
3) Finally, Stata's excellent simulation tools can help you assess
how bad or good
Richard's Rule works compared to Rubin's Rule. The point estimates
seem fine, but the
coverage seems to be off. To get a better view of the coverage, you
would probably have
to run the simulation longer, but even with 500 simulation it seems
pretty clear that with
Richard's Rule you reject a true null hypotheses in more than 5% of
the samples, while the
coverage for Rubin's Rule is closer to the nominal 5%.
"The point estimates seem fine" might suggest that Richard's Rule may
sometimes have some redeeming social value! We often aren't
concerned with p-values and we often don't need the numbers to be
exactly right. For example, a student of mine working with a mim
dataset wanted multicollinearity diagnostics, so she just ran the
analysis pooling all the imputed data sets. Sometimes, too, it is
sufficient to know whether a diagnostic test clearly indicates that
there is or is not a potential problem. And, then there are things
like the adjust command or Scott Long's spost routines, which help
you to interpret results. It may be sufficient for their output to
be in the ballpark.
That is not to say that you should deliberately use numbers you know
are wrong when you can easily get the right ones, but if the choice
is no numbers at all versus ballpark numbers the ballpark numbers may
be worth having.
It seems, too, that you could also do separate analyses on each
imputed data set, to see how wildly the numbers fluctuate.
I'm not as good as Maarten is at figuring these things out and
getting them programmed in 15 minutes, so my Stata 10 wishlist now
includes extensive support for a mim: type command. Ideally, it
would be very similar to the svy: command, and do all the appropriate
calculations, and know when, say, a Wald test is more appropriate
than a likelihood ratio test, and so on.
Again, great post, Maarten.
-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME: (574)289-5227
EMAIL: [email protected]
WWW: http://www.nd.edu/~rwilliam
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/