Like David, I too thought that `offset' is the way to do this. I was actually in the midst of testing the differences between using `offset' and `init' when David's email came.
Here is what I could figure out so far: 1. If you want to fix only a subset of regressors, but let others be estimated, then you must use `offset'. The `init' approach will not work. 2. Even when all the regressors are fixed (I have to admit that I do not see the point of this, like David said), there seems to be a difference in using `init' and `offset'. First of all, we cannot interpret or use the standard errors, CIs, abd p-values when iter.max=0. Secondly, there is major disagreement in the predictions between `offset' and `init' with no iterations. You can run the following code to verify this: ans1 <- coxph(Surv(time, status) ~ age + ph.karno, data = lung, init = c(0.05, -0.05), iter.max = 0) ans2 <- coxph(Surv(time, status) ~ offset(0.05*age) + offset(-0.05*ph.karno), data = lung) lp1 <- predict(ans1, type="lp") lp2 <- predict(ans2, type="lp") all.equal(lp1, lp2) > all.equal(lp1, lp2) [1] "Mean relative difference: 1.463598" The results from `offset' are correct, i.e. lp2 can be readily verified to be equal to 0.05 * (age - ph.karno). I don't know how lp1 is computed. Ravi. ____________________________________________________________________ Ravi Varadhan, Ph.D. Assistant Professor, Division of Geriatric Medicine and Gerontology School of Medicine Johns Hopkins University Ph. (410) 502-2619 email: rvarad...@jhmi.edu ----- Original Message ----- From: David Winsemius <dwinsem...@comcast.net> Date: Sunday, March 13, 2011 2:29 pm Subject: Re: [R] using pre-calculated coefficients and LP in coxph()? To: Dimitris Rizopoulos <d.rizopou...@erasmusmc.nl> Cc: r-help@r-project.org, Angel Russo <angerusso1...@gmail.com> > On Mar 13, 2011, at 1:32 PM, Dimitris Rizopoulos wrote: > > >probably you want to use the 'init' argument and 'iter.max' > control-argument of coxph(). For example, for the Lung dataset, we fix > the coefficients of age and ph.karno at 0.05 and -0.05, respectively: > > > >library(survival) > > > >coxph(Surv(time, status) ~ age + ph.karno, data = lung, > > init = c(0.05, -0.05), iter.max = 0) > > > > > > >I hope it helps. > > > >Best, > >Dimitris > > > > > >On 3/13/2011 6:08 PM, Angel Russo wrote: > >>I need to force a coxph() function in R to use a pre-calculated set > of beta > >>coefficients of a gene signature consisting of xx genes and the gene > >>expression is also provided of those xx genes. > > I would have guessed (and that is all one can do without an example > and better description of what the setting and goal might be) that the > use of the offset capablity in coxph might be needed. > > -- > David. > >> > >>If I try to use "coxph()" function in R using just the gene > expression data > >>alone, the beta coefficients and coxph$linear.predictors will > change and I > >>need to use the pre-calcuated linear predictor not re-computed > using coxph() > >>function. The reason is I need to compute a quantity that uses as > it's input > >>the coxph() output but I need this output to be pre-calculated > >>beta-coefficients and linear.predictor. > >> > >>Any one can show me how to do this in R? > >> > >>Thanks a lot. > > David Winsemius, MD > West Hartford, CT > > ______________________________________________ > R-help@r-project.org mailing list > > PLEASE do read the posting guide > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ 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.
