Dear all,
I am trying to estimate a Split Population Survival Model (also called
Cure Model) with discrete time duration data in Stata 9.0. This model
relaxes the assumption that all subjects will eventually experience
the event of interest by supposing that a proportion of the population
never fail.
The -spsurv- Stata module developed by Stephen P. Jenkins estimates
this model, but it assumes that the cure probability (the probability
of a subject never failing) is common to all individuals. The code can
be found at:
http://fmwww.bc.edu/repec/bocode/s/spsur_ll.ado
http://fmwww.bc.edu/repec/bocode/s/spsurv.ado
However, I am interested in running a Split Population Survival Model
that allows for differences between individuals in this probability,
for instance, by using a logistic relationship between some
explanatory variables and the cure probability. But I have no clue
about how to do this in Stata, or how to modify the original code of
the -spsurv- module to incorporate this heterogeneity in the cure
probability.
If it helps, Forster, M. and Jones, A.M. (2001) ("The
role of tobacco taxes in starting and quitting smoking: duration
analysis of British data" Journal of the Royal Statistical Society A,
164(3), pp.517-547) have developed a Stata code to estimate this model
for continuous time data (the code can be found at
http://www.york.ac.uk/res/herc/software/Jrsscode.pdf).
Any help would be much appreciated.
Thank you in advance
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