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st: joint modeling of survival & longitudinal data (econometric version?)


From   "Feiveson, Alan H. (JSC-SK311)" <alan.h.feiveson@nasa.gov>
To   "statalist" <statalist@hsphsun2.harvard.edu>
Subject   st: joint modeling of survival & longitudinal data (econometric version?)
Date   Mon, 12 Jun 2006 14:28:56 -0500

Hi - In biometric applications, there has been a lot of recent work on
joint modeling of survival and a continuous longitudinal response, where
the latter contains random effects and/or measurement error. For
example, see the Wulfsohn-Tsiatis approach. WIth all the sophisticated
econometric instrumental variable, etc. routines in Stata, I wonder if
there is one already there that essentially does the same thing as
Wulfsohn-Tsiatis, but is hiding behind some econometric name or
terminology. 

In rudimentiary terms, my understanding of the Wulfsohn Tsiatis model is
that of two variables, say T and X , where T given X and other
covariates follows a Cox survival model, and that X is measured
longitudinally with sporadic repeated measurements for each of a number
of subjects. However we observe not X, but X + a random subject effect +
a random measurement error, where the errors have normal distributions.
The Wulfsohn-Tsiatis estimation methdology then uses an EM approach to
get maximum likehood estimates of the parameters.

Thanks

Al Feiveson


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