RE: st: Creating time-dependent covariates to replicate the tvc option for stcrreg

["Travis Coan" <tcoan@law.harvard.edu>]

Thanks so much for the reply Bobby -- this is all becoming much clearer.


I have one quick follow-up question. When using the -tvc()- option you
cannot produce the CIF using stcurve. Would you recommend producing the
CIF in this situation -- i.e., when you've violated the proportionality
assumption -- using the predict and the basecif option? Or am I missing
something here?

Thanks again for your response!
Travis 



-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Roberto G.
Gutierrez, StataCorp
Sent: Monday, April 05, 2010 1:36 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Creating time-dependent covariates to replicate the tvc
option for stcrreg

Travis Coan <tcoan@law.harvard.edu> asks:

> I am trying to use interaction terms that I created manually to
replicate
> the results provided by the tvc option after Stata's stcrreg command.
> Needless to say, I am not having much success.

> I have tried to use the suggestions provided in Stata's "tvc note"
help file
> (help tvc_note) for stcox. For example, with the Hypoxia Study data
used in
> the Stata manual (Example 1, pg. 200):

> stset dftime, failure(failtype == 1) id(stnum) 
> stsplit, at(failures)
> gen ifptime = ifp*_t
> stcrreg ifp tumsize pelnode ifptime, compete(failtype == 2)

> These results are different from those produced by Stata's tvc option:

> stcrreg ifp tumsize pelnode, compete(failtype == 2) tvc(ifp)

> If anyone has any advice on this issue (or could point me to resources
on
> the issue), I would greatly appreciate it. Thanks so much for your
> consideration.

Unlike with -stcox-, using the -tvc()- option with -stcrreg- is not
equivalent
to splitting observations and generating the time interactions manually.
That
is because in competing-risks regression subjects remain in risk-pool
calculations past the time when they fail, if they fail due to competing
reasons.  When this happens, it raises the question of what to do with
the
values of the covariates for that subject past their failure time.

Suppose the event of interest is lung cancer, a heart attack is a
competing
event, and we are measuring (among other things) BMI for each subject.
If we
use the -tvc(bmi)- option to -stcrreg-, then Stata can extrapolate
values of
-bmi- past the time of the heart attack because it has a mathematical
expression for doing so.  When you split observations, however, Stata
has no
recourse but to keep -bmi- fixed at its most recent observed value, that
is,
its value when the subject had their heart attack.  You will get
different
results.

Because -tvc()- extrapolates covariates past failure, you might be
skeptical
toward the results because this is unlikely to reflect any real-data
situation.  However, if you instead interpret what you get out of
-tvc()- as
time-varying _coefficients_, what you get out of -tvc()- is a test of
the
proportional subhazards assumption; see pp. 214-215 of [ST] stcrreg for
more
details.

--Bobby
rgutierrez@stata.com
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