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From | Stas Kolenikov <skolenik@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: multiple imputation and propensity score |
Date | Wed, 24 Aug 2011 09:13:34 -0500 |
Can you follow through your analysis in the multiple imputation framework? The propensity score will probably go into some regression or matching exercise; can you perform these with -mim-? That would be the approach most closely consistent with MI framework. On Wed, Aug 24, 2011 at 5:28 AM, Stefano Di Bartolomeo <stefano.dibartolomeo@uniud.it> wrote: > Dear Statalist members > > I am doing a study that compares survival after 2 types of cardiological treatments angioplasty or by-pass. To limit confounding I use a propensity score, calculated as usual by a logistic model. A few covariates had missing values, which I imputed with ICE (5 imputations), separately for each group of treatment. Then I joined again the records in 1 file with 'append' and so have a file with N*6 observations. Then I calculate the propensity score : > mim: logistic angioplasty_vs._bypass + other_covariates > Finally I obtain the propensity score with > mim: predict pscore > As expected, I have 6 sets of propensity scores, one for each set of imputed data (_mj = 1-5) plus the one (_mj = 0) resulting from the combination of imputed estimators according to Rubin's rules. Unfortunately, the propensity score of the set _mj = 0 (which is the one I would think correct to use for further analyses) makes no sense, being virtually the same in patients treated with angioplasty or by-pass. The propensity scores of the imputed sets _mj 1-5 instead are ok and distributed as expected in the two treatment groups. I could easily pick up one of this well-working propensity scores for further use, but I know it is not correct. Has anybody ever encountered such a problem? Is it normal that the application of Rubin's rules results in a virtually useless propensity score? If so, how can one properly calculate propensity scores with multiply imputed data-sets? -- Stas Kolenikov, also found at http://stas.kolenikov.name Small print: I use this email account for mailing lists only. * * 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/