On Jan 28, 2014, at 10:32 AM, Oscar Rueda wrote:
> 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.
Wrong ... in what way?
> Would anybody please explain to me why?
Perhaps because anova is a generic function and you were expecting anova.cph to
be used but the coxph function is not from pkg:rms but rather from pkg:survival.
methods(anova) # with both rms and survival loaded
> methods(anova)
[1] anova.coxmelist* anova.coxph* anova.coxphlist* anova.glm
[5] anova.glmlist anova.glmmPQL* anova.lm anova.loess*
[9] anova.loglm* anova.mlm anova.negbin* anova.nls*
[13] anova.polr* anova.rms* anova.rq anova.rqlist
[17] anova.survreg* anova.survreglist*
>
> 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
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David Winsemius
Alameda, CA, USA