"=?UTF-8?B?5a6L5pe25q2M?=" <[EMAIL PROTECTED]> wrote in news:[EMAIL PROTECTED]:
> Dear All, > > Are there R packages that can estimate survival model with long-term > survivors? This is sometimes known as "cure" model or > "split-population" model. Thanks. The usual Cox model would certainly allow the analysis of observations with long-term survivors, but I am wondering if you want some sort of parametric model or one which compares a cohort's survival to some sort of external standard population expected survival. Therneau and Gramsch's text has a chapter on working with such expected survival estimates and the survival package can probably be considered an R atandard. If you set up a parametric Weibull model with a decreasing hazard, you get a cure, at least asymptotically. I think Harrell's Design package can conjure up accelerated time models that include the Weibull. Although the SRAB cancer methodologists assert that: "Neither SAS nor Splus can be used to fit survival models to relative survival data." (1) I would be very dubious regarding such a claim. See for instance: <http://www.mf.uni-lj.si/ibmi/biostat-center/predtiski/CMPB_Pohar_Stare_relsurv.pdf> <http://www.ncbi.nlm.nih.gov/pubmed/15848272> <http://cran.r-project.org/web/packages/relsurv/relsurv.pdf> -- David Winsemius 1) <http://srab.cancer.gov/cansurv/models.html> ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
