Dear all,

I’m using the package “Survival” to perform Cox regression analysis. Until now, I’ve gotten the results successfully. But I still have a question of the results:

As is shown in the picture below, the overall P-value (0.1122) of Lymnodes_status is different from P-value of “Lymphnodes_status=positive” (0.101). what's the reason of this difference?

In my opnion, the p-value of "Lymphnodes_status=positive" is calculated by wald test while overall p-value is given by likelihood test. which one should i choose?

Moreover, for polytomous variable, such as "surgery=c("no", "no-BSO","BSO")",it seems that p-value of each level can just be given by wald test. In this case, i can only accept the overall p-value of wald test? or are there many methods to perform likelihood test for each level?

I'd appreciate it if ypou can give me any suggestion.

my code:

osfsingle<-coxph(formula = Surv(time, os==1)~Lymphnodes_status,data = ess1 ,x=T,y=T)

osfsingle

Call:

coxph(formula = Surv(time, os == 1) ~ Lymphnodes_status, data = ess1,

x = T, y = T)

```
coef exp(coef) se(coef) z p
```

Lymphnodes_statusPositive 0.3690 1.4463 0.1915 1.927 **0.054**

Likelihood ratio test=3.46 on 1 df, **p=0.06296**

n= 1172, number of events= 164

`summary(osfsingle)`

Call:

coxph(formula = Surv(time, os == 1) ~ Lymphnodes_status, data = ess1,

x = T, y = T)

n= 1172, number of events= 164

```
coef exp(coef) se(coef) z Pr(>|z|)
```

Lymphnodes_statusPositive 0.3690 1.4463 0.1915 1.927 **0.054** .

Signif. codes: 0 ‘* ’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

```
exp(coef) exp(-coef) lower .95 upper .95
```

Lymphnodes_statusPositive 1.446 0.6914 0.9937 2.105

Concordance= 0.537 (se = 0.018 )

Rsquare= 0.003 (max possible= 0.835 )

Likelihood ratio test= 3.46 on 1 df, **p=0.06**

Wald test = 3.71 on 1 df, **p=0.05**

Score (logrank) test = 3.76 on 1 df, **p=0.05**