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From |
"E. Paul Wileyto" <epw@mail.med.upenn.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Split Population Survival (Cure) Model with discrete timedata |

Date |
Thu, 20 Dec 2007 12:07:38 -0500 |

When you say discrete time, do you mean that you have (long) time intervals with a beginning and end, and the event happens some time in between? If so, we can write something simple for that using ml.

Paul

Javier Sesé wrote:

Thanks Paul for your suggestions.--

I couldn't have access to this article, although my guess is that these routines are for continuous time data (I searched for them from the Stata help).

In my case, I have discrete time data.

Any suggestions to solve it with this kind of data?

Thank you in advance

At 13:12 19/12/2007, you wrote:

Look in The Stata Journal (2007), Vol. 7, Number 3, pp. 351-375 for an article on cure models by Paul Lambert.

You can retrieve Lambert's set of routines by searching for -strsmix- from Stata Help. It's a very flexible set of parametric cure models.

EPW

Javier SesÃ© wrote:

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 * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/-- E. Paul Wileyto, Ph.D. Assistant Professor of Biostatistics Tobacco Use Research Center School of Medicine, U. of Pennsylvania 3535 Market Street, Suite 4100 Philadelphia, PA 19104-3309 215-746-7147 Fax: 215-746-7140 epw@mail.med.upenn.edu http://mail.med.upenn.edu/~epw/ * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/* * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

E. Paul Wileyto, Ph.D.

Assistant Professor of Biostatistics

Tobacco Use Research Center

School of Medicine, U. of Pennsylvania

3535 Market Street, Suite 4100

Philadelphia, PA 19104-3309

215-746-7147

Fax: 215-746-7140

epw@mail.med.upenn.edu

http://mail.med.upenn.edu/~epw/

*

* For searches and help try:

* http://www.stata.com/support/faqs/res/findit.html

* http://www.stata.com/support/statalist/faq

* http://www.ats.ucla.edu/stat/stata/

**References**:**st: Split Population Survival (Cure) Model with discrete time data***From:*Javier Sesé <javisese@unizar.es>

**Re: st: Split Population Survival (Cure) Model with discrete timedata***From:*"E. Paul Wileyto" <epw@mail.med.upenn.edu>

**Re: st: Split Population Survival (Cure) Model with discrete time data***From:*Javier Sesé <javisese@unizar.es>

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