# This output file is at www.richardsconsulting.co.uk/lectures

# Load in the library of survival functions
library(survival)

# Create a vector of observation times
times<-c(10, 13, 18, 19, 23, 30, 36, 38, 54, 56, 59, 75, 93, 97, 104, 107, 107, 107)
 
# Create a vector of event types -- '1' for death, '0' for censored
events<-c(1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0)
 
#Take a look at the survival data -- '+' marks censored observation
Surv(times, events)
 [1]  10   13+  18+  19   23+  30   36   38+  54+  56+  59   75   93   97  104+
[16] 107  107+ 107+
 
# Calculate the Kaplan-Meier survival estimates
kapmei<-survfit(Surv(times, events) ~ 1)
 
# Take a look at the estimates and confidence intervals
# Compare these results with the table on page 7 of the red book
summary(kapmei)
Call: survfit(formula = Surv(times, events) ~ 1)

 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   10     18       1    0.944  0.0540        0.844        1.000
   19     15       1    0.881  0.0790        0.739        1.000
   30     13       1    0.814  0.0978        0.643        1.000
   36     12       1    0.746  0.1107        0.558        0.998
   59      8       1    0.653  0.1303        0.441        0.965
   75      7       1    0.559  0.1412        0.341        0.917
   93      6       1    0.466  0.1452        0.253        0.858
   97      5       1    0.373  0.1430        0.176        0.791
  107      3       1    0.249  0.1392        0.083        0.745