On Feb 13, 2013, at 7:46 AM, Cindy Yao wrote: > Dear R-helpers: > > I am trying to fit a multivariate Cox proportional hazards model, > modelling survival outcome as a function of treatment and receptor > status. The data look like below: > > # structure of the data > str(sample.data) > List of 4 > $ survobj : Surv [1:129, 1:2] 0.8925+ 1.8836+ 2.1191+ 5.3744+ > 1.6099+ 5.2567 0.2081+ 0.2108+ 0.2683+ 0.4873+ ... > ..- attr(*, "dimnames")=List of 2 > .. ..$ : NULL > .. ..$ : chr [1:2] "time" "status" > ..- attr(*, "type")= chr "right" > $ therapy : Factor w/ 2 levels "treatment1","treatment2": 1 1 1 1 1 > 1 1 2 2 1 ... > $ ReceptorA: Factor w/ 2 levels "0","1": 1 2 2 2 1 2 2 2 2 1 ... > $ ReceptorB: Factor w/ 2 levels "0","1": 1 2 1 1 2 1 1 1 1 1 ... > > But when I tried to fit a multivariate Cox proportional model, I got > the following error. I'm not quite what that means. Any help would be > much appreciated! > > # perform multivariate Cox proportional hazards model > coxph(sample.data$survobj ~ sample.data$therapy + > sample.data$ReceptorA + sample.data$ReceptorB) > > Error in fitter(X, Y, strats, offset, init, control, weights = weights, : > NA/NaN/Inf in foreign function call (arg 6) > In addition: Warning message: > In fitter(X, Y, strats, offset, init, control, weights = weights, : > Ran out of iterations and did not converge
I cannot tell whether your method of calling coxph() could be part of the problem, or whether you just have a dataset that creates numerical difficulties. I would have constructed a dataset that did not have a Surv-object incorporated into that dataframe, sbut rather it would have been a list of five columns with 'time' and 'status' kept separate, and the call would have looked like: coxph( Surv(time, status) ~ therapy + ReceptorA + ReceptorB , data= sample.data) I know that people have had (occasional) problems in the past related merely to creating Surv-objects outside of the formula interface and your approach appears even more dangerous than that approach. Once you have a more more data arrangement, you could investigate the possibility of a pathological arrangement of data with this since it appears all of you predictors are binomial. with(sample.data, table( status, therapy, ReceptorA , ReceptorB) ) -- David. > > Best regards, > Cindy > > -- output of sessionInfo(): > > sessionInfo() > R version 2.15.2 (2012-10-26) > Platform: x86_64-unknown-linux-gnu (64-bit) > > locale: > [1] C > > attached base packages: > [1] grid splines stats graphics grDevices datasets utils > [8] methods base > > other attached packages: > [1] MASS_7.3-23 > [2] hexbin_1.26.1 > [3] cluster_1.14.3 > [4] latticeExtra_0.6-24 > [5] RColorBrewer_1.0-5 > [6] lattice_0.20-13 > [7] survival_2.37-2 > > loaded via a namespace (and not attached): > [1] tools_2.15.2 > > ______________________________________________ > 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. David Winsemius Alameda, CA, USA ______________________________________________ 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.
