On 04/27/2017 09:53 AM, sesh...@mskcc.org wrote:
Thank you Drs. Therneau and Murdoch. "Why not use coxph.fit?" -- My use case scenario is that I needed the Cox model coefficients for resampled data. I was trying to reduce the computational overhead of coxph.fit (since it will repeated a large number of times) by stripping all the parts that I don't need such as sorting of the data prior to coxfit6.c call and Martingale residual and concordance computations after the parameters are estimated.
That is an interesting use case which I had not thought about. The first question is just how much slower coxph.fit is than the stripped down version (I'd guess about 1/2 but that is just a guess), and whether that makes a real difference to your code. If it is spending 10% of its time in the coxph calculation a change to 5% isn't that much, but 90% is something else. The next is what is the main impediment (I'd guess concordance, but again just a guess.) Perhaps I could add concordance= and/or resid= flags to the fitting routine.
Under the R v3.4.0 model one cannot create any modified form of coxph.fit and expect it to work. Worse yet is the following where I copy "coxph.fit" to my workspace as "mycoxph.fit" (works initially because the environment is namespace:survival and fails when environment changed to R_GlobalEnv)
If you were under linux another solution would be to grab the source from github, add your routine to the R/ directory, then R CMD build followed by R CMD INSTALL. Macintosh is essentially as easy, though you need to install Xcode for the compilers. The compile toolchain for windows is outside my ken.
Let's keep talking. Terry T. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
