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| From | Maarten Buis <maartenlbuis@gmail.com> |
| To | statalist@hsphsun2.harvard.edu |
| Subject | Re: st: multiple imputation and propensity score |
| Date | Wed, 24 Aug 2011 17:31:51 +0200 |
On Wed, Aug 24, 2011 at 5:03 PM, Stefano Di Bartolomeo wrote: > As you supposed, after calculating the PS I do some 1:1 matching and then I run several models of Cox regression for various outcomes, stratified on matched pairs. I am very curious to learn if all this would be feasible carrying forward all the imputed data sets. For sure, it is beyond my skills. I vaguely surmise that perhaps it could be possible if I used logistic regression instead of Cox regression, but I am not sure and in any case I must use survival analysis. Moreover, how could I draw a graphic of the density distribution of PS in the two groups before and after matching without having a unique PS? Propensity score matching and multiple imputation are two techniques that are both complicated, difficult to get right and easy to get wrong and have their own set of non-trivial possibly conflicting(*) assumptions. I would just focus on doing one of them right rather than trying to stack techniques this way. Hope this helps, Maarten (*) I don't know if that is the case, but it would not surprise me. -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/