Re: st: selection in continuous time survival framework without instruments

["Heather Gold" <heg2001@med.cornell.edu>]

Alex Cowell asked:
1.  Does anyone know of a way of using an individual fixed-effects (in
economics lingo) that would help handle this bias in a continuous time
framework?
2.  Any other ideas on controlling for this kind of unobserved heterogeneity
bias?  Again, remember there are no obvious identifying instruments.  And
note that I think this is subtly different from modeling 'frailty' (could be
wrong on that though).
-----------------
This is something I've been interested in, too. Take a look at Hamilton & 
Hamilton (1997) "Estimating surgical volume - outcome relationships 
applying survival models: accounting for frailty and hospital fixed 
effects" Health Economics v. 6:383-395, which is based on the work of 
Heckman and Singer (1984) "A method for minimizing the impact of 
distributional assumptions in econometric models for duration data" 
Econometrica v. 62:271-320.

I could never get this programmed into Stata. (Hamilton and Hamilton's work 
was done in .tsp) Frailty is, I believe, identical to unobserved 
heterogeneity, and there are some frailty survival models canned in Stata 
that might work for you, if you want to work in a discrete-time framework 
(which it sounds like you don't).

Good luck - wish I could be more helpful,
Heather Gold

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