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Re: st: Combining multiple imputation with propensity score matching


From   Austin Nichols <austinnichols@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Combining multiple imputation with propensity score matching
Date   Tue, 2 Mar 2010 12:10:29 -0500

Cornell, John E <cornell@uthscsa.edu> :

The issue here is that -mahapick- on SSC will not pick unique matches
by group, and will not restrict to matches within some predefined
limit on distance, right?  You could use -psmatch2- to pick unique
matches, where ties should be broken by random sort order, but why not
reweight instead of matching, run regressions in each imputed dataset
and combine manually? See also
http://www.stata-journal.com/article.html?article=st0136_1 [
http://pped.org/stata/erratum.pdf ]
http://www.stat.psu.edu/~jls/mifaq.html#howto

You may also want to compute nonparametric estimates for propensity
scores by quantile groupings on X; simulations show these can
outperform those generated by -logit- and Hirano Imbens and Ridder
supply a related proof:
http://ideas.repec.org/a/ecm/emetrp/v71y2003i4p1161-1189.html

On Tue, Mar 2, 2010 at 11:17 AM, Cornell, John E <cornell@uthscsa.edu> wrote:
>
> Dear Stata Folks:
>
> I have a large, and somewhat complicated multi-site dataset, that requires the use of multiple imputation to fill-in missing lab values that I need to generate propensity scores for three classes of drugs. I used the new multiple imputation procedure based on multivariate normal regression to fill-in the missing lab values. We created 20 imputed datasets if the flong format, and used logistic regression to compute and save the propensity scores in logit form within each imputed set. We used mahapick to select to match cases (being on one or more of the three agents) to controls (never on any of the three agents). This worked well, but there are two problems we encountered at this stage. First, the procedure selects the closest match actual distance may be very large so we needed to edit the matches to maintain a subset of cases with reasonable closeness. Second, the procedure may match the same control to more than one case, so we needed to restrict the sample to unique ma!
 tches. Finally, the number of matches varied between imputed sets.
>
> It does not appear that the mi estimate command can handle this situation. So, we are left with the prospect of writing our own code to compute and combine the model estimates. We are relatively novice Stata programmers at the moment, and we would welcome any suggestions, references, etc. that the Stata community could provide that will help us solve this problem.

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