Hi, everyone,
I came across the following strange inconsistency between R and JMP (or SAS) in median survival time estimation.
I understand that CI can be different because of different ways of doing it, but I never expected that median survival point estimation could be different. Does anyone here happen to know the actual technical reason? I tried to figure it out, but had no luck.
For the following simple dataset (event =1 means death, 0 means censor),
time | event | trt |
116 | 1 | 0 |
116 | 0 | 0 |
110 | 1 | 0 |
116 | 1 | 0 |
116 | 1 | 0 |
110 | 1 | 0 |
116 | 1 | 0 |
116 | 1 | 0 |
150 | 0 | 1 |
150 | 1 | 1 |
138 | 1 | 1 |
138 | 1 | 1 |
150 | 0 | 1 |
150 | 0 | 1 |
150 | 0 | 1 |
138 | 1 | 1 |
JMP cannot provide an estimate of median survival time for trt = 1 group while R can.
JMP output: (JMP 12.1, use analyze --> reliability and survival --> survival, Y = time, grouping = trt, cencor = event, censor code = 0 )
| Group | Median Time | ... |
| 0 | 116 | ... |
| 1 | . | ... |
R output: (code: library(survival); summary(survfit(Surv(time,event)~trt, data=data))$table)
| | ... | median | ... |
| trt=0 | ... | 116 | ... |
| trt=1 | ... | 150 | ... |
Thank you all in advance!