For any given pre-specified gene or short list of genes, yes the Cox model works fine. Two important caveats:
1. Remeber the rule of thumb for a Cox model of 20 events per variable (not n=20). Many microarray studies will have very marginal sample size. 2. If you are looking at many genes then a completely different strategy is required. There is a large and growing literature; I like Newton et al, Annals of Applied Statistictis, 2007, 85-106 as an intro; but expect to read much more. Terry Therneau -------- begin included message --------- I want to test the expression of a subset of genes for correlation with patient survival. I found out that the coxph function is appropriate for doing this since it works with continuous variables such as Affy mRNA expression values. I applied the following code: cp <- coxph(Surv(t.rfs, !e.rfs) ~ ex, pData(eset.n0)) #t.rfs: time to relapse, status (0=alive,1=dead), ex: expression value (continuous) The results I get look sensible but I would appreciate any advice on the correctness and also any suggestions for any (better) alternative methods. Best wishes ______________________________________________ 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.
