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st: Inverse probability of treatment weights

From   David Torres <[email protected]>
To   [email protected]
Subject   st: Inverse probability of treatment weights
Date   Sun, 24 Oct 2010 17:25:34 -0400

I've read Fewell et al. ( on the construction of inverse probability of treatment weights, but wonder whether i have things correct.

It looks like I have to create stabilized and censoring weights on my longitudinal data, but I'm not sure what predictors should be in the logistic model. Any tips?

My outcome for the stabilized weights is whether a respondent was interviewed (0=no 1=yes). For the censoring weight, the outcome is of course whether the respondent was not followed up (1=censored 0=not censored). My data are in long format. Do these sound like the right outcomes?


David Diego Torres, MA(Sociology)
PhD Candidate in Sociology

2044 Population Studies Center
University of Michigan Institute for Social Research
Ann Arbor MI  48106-1248
Tel 734.763.4098
Fax 734.763.1428
torresd at umich dot edu

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