Prof. Paul,  Prof. Frank.

Thank you very much for helping me out. The Design package did the
trick.

Here is how the anova table looks like without using the Design package:

> anova(Fit1)
Analysis of Deviance Table
Cox model: response is Surv(Time, cancer)
Terms added sequentially (first to last)

            Df Deviance Resid. Df Resid. Dev
NULL                              16783     5341.8
relativ        1        0.0     16782    14995.0
hormone    3    939.4     16779    14055.6
.
.
.


As you see, no p-values reported

Here is how it looks with after implementing Design:

> anova(Fit1)
                 Wald Statistics          Response: Surv(Time, cancer) 
 Factor     Chi-Square d.f. P
 relativ         6.08       1   0.0137
 hormone     8.68       3   0.0339
.
.
.


Regards,
Kare


On Fri, 2008-04-18 at 11:03 -0500, Frank E Harrell Jr wrote:

> Paul Johnson wrote:
> > On Fri, Apr 18, 2008 at 3:06 AM, Kåre Edvardsen <ked@nilu.no> wrote:
> >> Hi all.
> >>
> >>  If I run the simple regression when x is a categorical variable ( x <-
> >>  factor(x) ):
> >>
> >>  > MyFit <-coxph( Surv(start, stop, event) ~ x )
> >>
> >>  How can I get the overall p-value on x other than for each dummy
> >>  variable?
> >>
> >>  > anova(MyFit)
> >>
> >>  does NOT provide that information as previously suggested on the list.
> >>
> > 
> > It "should" work...  Here's a self contained example showing that
> > anova does give the desired significance test for an lm model.
> > 
> >> y <- rnorm(100)
> >> x <- gl(5,20)
> >> mod <- lm(y~x)
> >> anova(mod)
> > Analysis of Variance Table
> > 
> > Response: y
> >           Df  Sum Sq Mean Sq F value Pr(>F)
> > x          4   6.575   1.644  1.5125 0.2047
> > Residuals 95 103.237   1.087
> > 
> > If you provide a similar self contained example leading up to a coxph,
> > I would be glad to investigate your question.  You don't give enough
> > information for me to tell which version of coxph you are running, and
> > from what  package.
> > 
> > Suppose I "guess" that you are using the coxph from the package
> > "survival". If so, it appears to me there is a bug in that package at
> > the moment.  The methods anova.coxph and drop1.coxph did exist at one
> > time, until very recently.  There is a thread in r-help (which I found
> > by typing "RSiteSearch("anova.coxph")" ) discussing recent troubles
> > with anova.coxph.
> > 
> > http://finzi.psych.upenn.edu/R/Rhelp02a/archive/118481.html
> > 
> > As you see from the discussion in that thread, there used to be an
> > anova method for coxph, and in the version of survival I have now,
> > there is no such method.  The version I have is  2.34-1, Date:
> >  2008-03-31.
> > 
> > Here's what I see after I run "example(coxph)" in order to create some
> > coxph objects, on which I can test the diagnostics:
> > 
> >> drop1(test2)
> > Error in terms.default(terms1) : no terms component
> >> anova(test2)
> > Error in UseMethod("anova") : no applicable method for "anova"
> > 
> > In that survival package, I do find anova.survreg, but not
> > anova.coxph. If you are using the survival package, I'd suggest you
> > contact Thomas Lumley directly, since he maintains it.
> > 
> > I think if you had reported the exact error you saw, it would have
> > been easier for me to diagnose the trouble.
> > 
> > HTH
> > pj
> > 
> 
> In the meantime you can do
> 
> library(Design)
> f <- cph( . . . )
> anova(f)      # multiple d.f. Wald statistics including tests of 
> nonlinearity
> 
> cph uses coxph but anova.Design is separate from the survival package.
> 
> Frank
> 

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