This problem makes use of the following table.
You can create the table in R as follows:
df <- data.frame(observation = rep(c(26.5, 37.2, 57.3, 90.8, 20.2, 89.8)),
censoring = rep(c(1, 1, 1, 0, 0, 0)),
covariate = rep(c(0.1, 11, -0.3, 2.8, 1.8, 0.4)), stringsAsFactors = T)
ifelse()
and as.factor()
functions to add a new column to the
dataframe, named group
, containing factor levels "Group 1"
and "Group 2"
.fit.km
. Be sure to label the curves so that it is clear
which curve corresponds to which group. By eye, does there appear to be a
difference between the two groups’ survival curves? Answer the
question below.
group
indicator
as a covariate, store the model in the variable fit.cox
. Inspect the output of the model and answer the following question.
logrank.test
.
Verify that the log-rank test statistic equals the score statistic
for the Cox model and answer the following question.
NOTE: the outputs of
logrank.test
andsummary(fit.cox)
return rounded \(p\)-values. In order to compare the exact \(p\)-values, inspect the appropriate attributes of the objects.
Assume that:
ISLR2
library has been loaded.survival
library has been loaded.