Manisha,
It might be helpful if you could be more specific about what you mean by
correlated event times e.g. one could image that the time to event for
hospitalization for a heart attack and the time to event for death might
be correlated because they both depend on the the status of
atherosclerotic heart disease.
A parametric approach would be to specify the hazards for the two events
and include a common covariate (e.g. serum cholesterol time course,
chol(t)) in the hazard e.g.
h(hosp)=basehosp*exp(Bcholhosp*chol(t))
h(death)=basedeath*exp(Bcholdeath*chol(t))
The common covariate, chol(t), would introduce some degree of
correlation between the event times.
Nick
Manisha Lamba wrote:
Dear NMusers,
If anyone in the user group aware of approaches on developing
semi-parametric or parametric models for (joint modeling of) two
time-to-event endpoints, which are highly correlated?
Any suggestions/references/codes(NONMEM, R etc.) would be very much
appreciated!
Many thanks!
Manisha
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
[email protected] tel:+64(9)923-6730 fax:+64(9)373-7090
mobile: +33 64 271-6369 (Apr 6-Jul 20 2009)
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
