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| From | CJ Wilson <cwil111111@hotmail.com> |
| To | <statalist@hsphsun2.harvard.edu> |
| Subject | st: propensity score analysis time-varying treatment |
| Date | Mon, 10 Sep 2012 11:57:33 -0700 |
Dear Statalist, I’m trying to determine the correct Stata code to conduct a propensity score stratification analysis in a longitudinal dataset. My variable for the treatment is time-varying, so some patients receive treatment at certain time points but not others. I haven’t been successful at finding any examples of Stata code online that are for longitudinal propensity scores. Here is my proposed approach: 1. Estimate a random-intercept logistic regression model for the propensity of treatment using xtlogit 2. Calculate the propensity score as follows: predict prop_score gen prop_score2 = exp(prop_score)/(1+exp(prop_score)) xtile ps_quintiles = prop_score2, nq(5) tabulate ps_quintiles, ge(q) 3. Determine whether there is a treatment by propensity interaction Here are a couple areas where I'm struggling: 4. I would like to determine the standardized difference in means to assess whether balance is achieved. Does anyone have any sample Stata code relating to this? 5. Does anyone have sample code to determine the average treatment effect among the untreated? Any advice would be much appreciated. Thank you!! Carrie * * 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/