Dear list, I'm using the rms package to fit some Cox models. I run anova() on them to obtain sequential p-values, but I'm getting strange results when I run it on a subset of the data.
Following the example on the help page of anova.coxph: > library(rms) > data(ovarian) > fit <- coxph(Surv(futime, fustat) ~ resid.ds *rx + ecog.ps, data = ovarian) > anova(fit) > fit2 <- coxph(Surv(futime, fustat) ~ resid.ds +rx + ecog.ps, data=ovarian) > anova(fit2,fit) would give me the same result, as expected. But If I do > fit <- coxph(Surv(futime, fustat) ~ resid.ds *rx + ecog.ps, data = ovarian, > subset=ovarian$age>50) > anova(fit) > fit2 <- coxph(Surv(futime, fustat) ~ resid.ds +rx + ecog.ps, data=ovarian, > subset=ovarian$age>50) > anova(fit2,fit) The first p-value seems to be wrong. Would anybody please explain to me why? Cheers, Oscar PS. I'm using R 3.0.1. Oscar M. Rueda, PhD. Postdoctoral Research Fellow, Caldas Lab, Breast Cancer Functional Genomics. University of Cambridge. Cancer Research UK Cambridge Institute. Li Ka Shing Centre, Robinson Way. Cambridge CB2 0RE England ______________________________________________ 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.
