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st: IPW with OLOGIT


From   "Michael Furukawa" <Michael.Furukawa@asu.edu>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: IPW with OLOGIT
Date   Sat, 5 Apr 2008 21:38:05 -0700

I am trying to adjust for selection on observables using propensity
scores as inverse probability weights (ipw), following Wooldridge ("IPW
Estimation for General Missing Data Problems").  My dataset has a
complex survey design with survey weights (svywt), and I want to adjust
for selection bias of an ordered treatment (t1,t2,t3) on a count
outcome.  Can someone help me with the Stata code to compute the IPW
using the predicted probabilities as propensity scores?  I want to
compute IPW by multiplying the survey weight*(1/propensity score),
following Zanutto et al. (2005).

ologit t_cat $var
predict p1 p2 p3

/*Here's where I need help*/
ipw=svywt*[1/p1 ...]

glm depvar $var t2 t3 [pweight=ipw], fam(bin) link(logit) irls robust


Thanks in advance,
Mike


Michael F. Furukawa, PhD
Assistant Professor
Health Management and Policy
W. P. Carey School of Business
Arizona State University
(480) 965-2363

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