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

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: R: Kaplan Meier graph in longitudinal data |

Date |
Tue, 12 May 2009 09:05:09 -0400 |

Paul Deepa Aggarwal wrote:

Dear Carlo, Thanks for the quick response. I tried the following command. stcox age, cluster(id) But what to do after that. I looked at the reference book but I am lost. Many thanks, Deepa On Tue, May 12, 2009 at 3:36 AM, Carlo Lazzaro <carlo.lazzaro@tiscalinet.it> wrote:Dear Deepa, provided that the proportional risk assumption holds, a possible solution would be to switch to the semiparamentric Cox regression model, with the option -cluster(patient)- (please, see -help stcox-). In this way, you would correctly assume that patients are independent, whereas receuurences within the same patient aren't. This topic (like many others) is covered in Cleves MA, Gould WG, Gutierrez R. An Introduction To Survival Analysis Using Stata. Revised edition. College Station: StataPress, 2006: 148-152. Another possible (but trickier option) would be considering a Markov model (please, see Sonnenberg FA, Beck JR. Markov models in medical decision making: a practical guide. Medical Decision Making 1993;13:322-339. HTH and Kind Regards, Carlo -----Messaggio originale----- Da: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Deepa Aggarwal Inviato: lunedì 11 maggio 2009 19.52 A: statalist@hsphsun2.harvard.edu Oggetto: st: Kaplan Meier graph in longitudinal data Hi All, I have the following longitudinal data : id d_entry d_censor status age x2 1 20jan2008 22jan 2008 0 62 0 1 22jan 2008 24jan 2008 0 62 0 1 24jan 2008 26jan 2008 0 62 1 1 26jan 2008 28jan 2008 1 62 0 2 13jan 2008 18jan 2008 0 70 0 2 18jan 2008 20jan 2008 0 70 1 2 20jan 2008 24jan 2008 0 70 0 2 24jan 2008 26jan 2008 1 70 1 Here id is patient id number, d_entry is the date of entry, d_censor is the date of censoring, status is the censoring variable, age is fixed for each id, x2 changes with time for each id. First I stset the above mentioned data by using the following command: stset d_censor, id(id) failure (status==1) origin (time d_entry) Now I want to get a Kaplan meier graph . I know if there is one event per id, then sts graph can be used. But in recurrent event models, what command should be used? Thanks for your consideration. Deepa -- Deepa * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * 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

* * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**R: st: R: Kaplan Meier graph in longitudinal data***From:*"Carlo Lazzaro" <carlo.lazzaro@tiscalinet.it>

**References**:**st: Kaplan Meier graph in longitudinal data***From:*Deepa Aggarwal <da.aggarwal@gmail.com>

**st: R: Kaplan Meier graph in longitudinal data***From:*"Carlo Lazzaro" <carlo.lazzaro@tiscalinet.it>

**Re: st: R: Kaplan Meier graph in longitudinal data***From:*Deepa Aggarwal <da.aggarwal@gmail.com>

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