On Fri, Mar 11, 2011 at 8:25 AM, Brian McLoone <brianbmcloone at
gmail.com> wrote:> This is a follow-up to a query that was posted regarding some problems that
> emerge when running anova analyses for cox models, posted by Mathias
Gondan:
>
> Matthias Gondan wrote:
>
>>* Dear List,*>**>* I have tried a stratified Cox Regression, it is
working fine, except for*>* the "Anova"-Tests:*>**>* Here the
commands (should work out of the box):*>**>* library(survival)*>* d =
colon[colon$etype==2, ]*>* m = coxph(Surv(time, status) ~ strata(sex) + rx,
data=d)*>* summary(m)*>* # Printout ok*>* anova(m,
test='Chisq')*>**>* This is the output of the anova
command:*>**>* ? *>>* Analysis of Deviance Table*>>* ?Cox
model: response is Surv(time, status)*>>* Terms added sequentially (first
to last)*>>**>>* ? ? ? ? ? ? ?Df Deviance Resid. Df Resid. Dev
P(>|Chi|)*>>* NULL ? ? ? ? ? ? ? ? ? ? ? ? ? 929 ? ? 5233.5 ? ? ? ?
?*>>* strata(sex) ? 0 ? ? ? ? ? ? ? ?929 ? ? ? ? ? ? ? ? ? ? *>>* rx
? ? ? ? ? ?2 ? ? ? ? ? ? ? ?927 ? ? 5221.2 ? ? ? ? ?*>>* Warning
message:*>>* In is.na(coef(fit)) :*>>* ? is.na() auf nicht-(Liste
oder Vektor) des Typs 'NULL' angewendet*>>* ? ? *>**>* It
should be possible to do Chi-Square-Tests in a stratified analysis, *>*
right?*
>
>
> We have run into the same problem. ?In particular, we are running
stratified
> coxph models, but we are not able to generate a Chisq probability for both
> models.
>
>> drop1(Model,test='Chisq')
> Single term deletions
>
> Model:
> Surv(adjusted_days_60, Death_60_10) ~ strata(chol_60)
> ? ? ? ? ? ? ? ?Df ? ?AIC ? ?LRT Pr(Chi)
> <none> ? ? ? ? ? ? 7437.6
> strata(chol_60) ?0 8513.2 1075.6
>
> As you can see, why is the probability of the Chisq - i.e., Pr(Chi) -
> missing?
Because you can't do that. The strata() term corresponds to an
infinite-dimensional parameter, a new baseline hazard, so it isn't
like a straightforward likelihood ratio test. It certainly doesn't
have a chisquared distribution with a fixed number of degrees of
freedom -- I don't know if anyone has even worked out the sampling
distribution of this deviance difference.
-thomas
--
Thomas Lumley
Professor of Biostatistics
University of Auckland