Hi Terry, My "this" was your (a), i.e. the smoothed hazard rate function.
I apologize if I came across as being rude. I was only curious to see if you had any scientific/statistical rationale for not including the smoothed hazard option in your "survival" package, which is, by far, the most widely used tool for time-to-event analysis in R. Therefore, I just felt that having this, fairly useful, capability in "survival" would be nice. I have a couple of questions related to your two other points: point (b): How would you estimate the effect of a treatment on the cumulative incidence of primary outcome, adjusted for covariates, using the K&P approach (both point and interval estimation)? point (c): I don't quite understand why you find the F&G model completely biologically untenable. I view it as mathematical trickery to obtain a compact summary of the impact of a covariate on the cumulative incidence. The F&G model is especially useful in estimating covariate adjusted treatment effect, provided the proportionality assumption on the sub-distribution hazard is reasonable. The K&P approach does not provide such compactness as you have to model all the cause-specific hazards. Best, Ravi. ____________________________________________________________________ Ravi Varadhan, Ph.D. Assistant Professor, Division of Geriatric Medicine and Gerontology School of Medicine Johns Hopkins University Ph. (410) 502-2619 email: [email protected] ----- Original Message ----- From: Terry Therneau <[email protected]> Date: Friday, March 27, 2009 9:52 am Subject: RE: Competing risks Kalbfleisch & Prentice method To: [email protected], [email protected], Ravi Varadhan <[email protected]> Cc: [email protected] > Ravi's last note finished with > > I am wondering why Terry Therneau's "survival" package doesn't > > have this option. > > The short answer is that there are only so many hours in a day. > > I've recently moved the code base from an internal Mayo repository > to R-forge, > one long term goal with this is to broaden the developer base to n>2 > (me and > Thomas Lumley). > > A longer statistical answer: > > I'm not sure if the "this" of Ravi's question is a. smoothed > hazards, b. the > K&P cumulative incidence or c. the Fine & Gray model. > > b. I like the CI model and am using it more. We also have local > code. The > latest version of survival (on rforge, likely in the next default R > release) has > added simple CI curves to the survfit function. Adding code for > survfit on Cox > models is on the todo list. But -- this release also fixes up > survfit.coxph to > handle weighted Cox models and that was on my list for approx 10 > years, i.e., > don't hold your breath. I don't release something until it also has > a set of > worked out test cases to add to the 'tests' directory. > > a. smoothed hazards. For the case at hand I don't see any > particular > advantage of this. On the other hand, I often would like to display > hazard > functions instead of CI functions for Cox models; with time dependent > covariates > I don't think a survival curve makes sense. But I haven't had the > time to think > through exactly which methods should be added. > > c. Fine & Gray model, i.e., where covariates have a direct > influence on the > competing risk. I find the model completely untenable from a > biologic point of > view, so have no interest in adding it. (Due to finite time, > everything in the > survival package is code that I needed for an analysis; medical > research is what > pays my salary.) Assume that I have competing processes/risks, say > progression > of a tumor and heart disease; I expect that the tumor process pays > no attention > whatsoever to what is going on in the heart. But this is necessary > if > "type=squamous" is modeled as an absolute beta=__ increase in the CI > for cancer. > The squamous cells need to "step up the pace" of invasion if heart > failure > threatens, like jockeys in a horse race. > > Terry T. > ______________________________________________ [email protected] 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.
