Question: R survival analysis : surv_pvalue vs fit.coxph for log-rank-test pvalue
gravatar for ZheFrench
10 months ago by
ZheFrench300 wrote:

I have different value for test$pval and and other.pval that should return the same log-rank test p-value, no ?

surv_object <- Surv(time = as.numeric(final_group_annotated[,time]), event = final_group_annotated[,opt$endPoint] )it1 <- survfit(surv_object ~ group, data = final_group_annotated)

test=surv_pvalue(fit1, final_group_annotated)


fit.coxph <- coxph(surv_object ~ group, data = final_group_annotated)

coxph(formula = surv_object ~ group, data = final_group_annotated)

  n= 188, number of events= 30

               coef exp(coef) se(coef)      z Pr(>|z|)
groupgroup2 -0.3482    0.7060   0.3689 -0.944    0.345

            exp(coef) exp(-coef) lower .95 upper .95
groupgroup2     0.706      1.417    0.3426     1.455

Concordance= 0.538  (se = 0.049 )
Likelihood ratio test= 0.87  on 1 df,   p=0.4
Wald test            = 0.89  on 1 df,   p=0.3
Score (logrank) test = 0.9  on 1 df,   p=0.3

other.pval <- coef(summary(fit.coxph))[,5]


survival analysis R • 1.2k views
ADD COMMENTlink modified 10 months ago by Kevin Blighe65k • written 10 months ago by ZheFrench300
gravatar for Kevin Blighe
10 months ago by
Kevin Blighe65k
Kevin Blighe65k wrote:

The p-value returned by Surv() is the log-rank p-value from the score test; so, you should be comparing this to the log-rank p-value from the Cox PH model. I went over this recently in this thread: A: survfit(Surv()) P-value interpretation for 3 survival curves?


The way that you are doing it, i.e.:


This will return multiple p-values when there are multiple strata, one p-value representing a single stratum / coefficient compared to the reference stratum.

To extract the log-rank p-value for the overall model, you need to use:



ADD COMMENTlink modified 10 months ago • written 10 months ago by Kevin Blighe65k
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