[R] coxph question

[Mayeul KAUFFMANN]

Chris,
I understood the following: you want to try every single covariate in a
cox model with only one covariate, then take the best ones according to
p-value.

Assume your columns  look like:
stop status event x1 x2 x3 etc
You want to add column 3 (x1), then 4, etc.

I suggest a for() loop:

z<-NULL;for(i in 3:ncol(data))
{coxtmp <- coxph(Surv(stop,status)~ data[,i]) #you can modify the formula
for
                                                       #adding covariates
in any case, for instance
beta<-coxtmp$coefficients[1]
se<-sqrt(diag(coxtmp$var))[1]
z<- rbind(z,c(i,beta,se,pvalue=signif(1 - pchisq((beta/ se)^2, 1), 4)))
print (i)}

#then select the covariates according to the p values:
z[z$pvalue<.01,"i"]

Hope it helps.

Mayeul KAUFFMANN
Univ. Pierre Mendes France
Grenoble - France


----- Original Message ----- 
Thanks Mayeul,

I actually would like to test each variable individually and use those
have low p-value to build a classifier (not in cox model). Therefore, I
need to write a function to subset those low p-value variables, instead of
putting them as covariates. Any ideas?

Chris

-----Original Message-----

> I have many variables to test using cox model (coxph), and I am only
interested in those variables with p value less than 0.01. Is there a
quick way to do this automatically instead of looking at the output of
each variable?
> Chris