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how to perform survival analysis on a corrected and structured data

Hello,

I asked a question but seems like it was not very clear. I have studied and structured the data better and it is with 3 columns first column show 2 category (Drug means drug was added and the patient was monitored ) and WT (means wild type) The second column shows the number of dead patient. The third is the hour that it happened 

df<- structure(list(Condition = structure(c(1L, 2L, 1L, 2L, 1L, 2L, 
1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 
1L, 2L), .Label = c("Drug", "WT"), class = "factor"), Number.of.Dead = c(18L, 
29L, 21L, 28L, 11L, 23L, 12L, 20L, 10L, 18L, 9L, 16L, 9L, 15L, 
8L, 14L, 7L, 13L, 6L, 12L, 3L, 12L, 2L, 10L), Time = c(1L, 1L, 
2L, 2L, 3L, 3L, 4L, 4L, 5L, 5L, 6L, 6L, 7L, 7L, 8L, 8L, 9L, 9L, 
10L, 10L, 11L, 11L, 12L, 12L)), row.names = c(NA, -24L), class = "data.frame")

Now I am doing the following but the output is a bit strange, what am I missing here?

require(survcomp)
require(survival)

km.coxph.plot(formula.s=Surv(Number.of.Dead,Time) ~ Condition, data.s=df, mark.time=TRUE,
              x.label="Time (Hours)", y.label="Overall survival", main.title="",
              leg.text=c("Drug", "WT"), leg.pos="topright", leg.bty="n", leg.inset=0,
              .col=c("forestgreen","red3"),
              xlim=c(0,40),
              o.text="",
              .lty=c(1,1), .lwd=c(1.75,1.75),
              show.n.risk=TRUE, n.risk.step=10, n.risk.cex=0.8, verbose=FALSE)
r
• 160 views • link
written by Learner Learner

Hello and welcome. Is this part of a tutorial or exam?

Your data looks like this:

   Duration.h condition1 drug.treated
1           1         18           29
2           2         21           28
3           3         11           23
4           4         12           20
5           5         10           18
6           6          9           16
7           7          9           15
8           8          8           14
9           9          7           13
10         10          6           12
11         11          3           12
12         12          2           10

Which is the 'first condition'?; which is the 'second condition'?; where is the information about death? I would appreciate it if you could help us, so that we could begin to help you.

• 0 views • link
written by Kevin Blighe Kevin Blighe

@Kevin Blighe I just updated my question and thanks a lot , it is not tutorial or home work, it is a real data

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written by Learner Learner

I will have to take another look in the morning. In R, though, most survival functions are based on survival::Surv(). For example, if we wanted to do a Cox proportional Hazards Survival model, we would do:

summary(coxph(Surv(time = Duration.h) ~ condition1, data = data))

I think that you need to really understand that the input data is correct, though.

If anybody else wants to take a look, please, feel obliged.

• 0 views • link
written by Kevin Blighe Kevin Blighe

@Kevin Blighe

I just revised my question, now it is more clear. can you please have a look and let me know your ideas?

thanks

• 0 views • link
written by Learner Learner

Hi, I think that you first need to determine if the data is suitable for survival. Please read the help pages for the functions that you are using.

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written by Kevin Blighe Kevin Blighe

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