事件论点在R？生存函数中的统计意义

Question

I have created a Cox Regression model for Survival Analysis on a churn dataset.Now I am confused at two points:

1. When I write Surv(time,status) as the survival object and commit the cox regression, I get a very bad survival curve which does not reach the survival probability of 0.5
2. When I write Surv(time,status==0) as the survival object and commit the cox regression,I get a decent survival curve which reaches the almost 0 probability mark at the end of the time duration of the observation.

The time parameter in my dataset has a peculiar anomaly. Those with status==0 have a very high time value and those with status==1 have a very low time value.

Answer 1

The statistical significance is like this :

fit1<- Surv(time,event)
df1<-as.data.frame.character(fit1)

gives a result where all the individuals for whom status == 1 are considered censored ie their times will be designated as 2+,3+ etc. and those whose status==0 , their status will be considered dead after their respective time given in the time column, ie their times will be given as 13,10,15 etc. The moot point is those who are alive will be considered dead after their respective times and those who are alive will be considered dead after their respective times.