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st: Stata in Marginal Structural Models survival analysis


From   Michael McCulloch <mm@pinest.org>
To   Statalist <statalist@hsphsun2.harvard.edu>
Subject   st: Stata in Marginal Structural Models survival analysis
Date   Fri, 13 Jul 2007 08:31:31 -0700

Dear readers
I have read with great interest the paper Fewell, Z., M. A. Hernan, et al. (2004). "Controlling for time-dependent confounding using marginal structural models." The Stata Journal 4(4): 402-20, in which causal inference for survival at time(T) is estimated using logistic regression.

In my case, I am hoping to find do-file examples showing how to implement the MSM-adjusted hazard ratio using dates of treatment and death. Specifically, I have hit two stumbling blocks:
(1) the _stset_ command cannot incorporate the weights generated using logistic regression Inverse Probability of Treatment Weighting.
(2) the bootstrap appears to not be correctly specified.

Variables:
treatment (y/n) = tcm
event = failed
date of treatment = datedx
date of death = datedied

My code is:
*estimate probability of treatment
predict p_tcm_ALL
gen p_notcm_ALL = 1-p_tcm_ALL if tcm==0
replace p_tcm_ALL =p_notcm_ALL if tcm==0

*create stabilized weight==P(A)/P(A|W)
logit tcm
predict p_ALL
gen p_noALL=1-p_ALL if tcm==0
replace p_ALL = p_noALL if tcm==0
gen wt_stab_ALL=p_ALL/p_tcm_ALL

* MSM Cox, stabilized weights
stset datedied [iweight=wt_stab_ALL], failure(failed) origin(datedx)

*MSM COX
bootstrap, reps(1000): stcox tcm

Thank you,




--

Michael McCulloch
Pine Street Foundation
124 Pine St., San Anselmo, CA 94960-2674
Tel: (415) 407-1357
Fax: (415) 485-1065
mcculloch@pinestreetfoundation.org
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