Comparing patient soreness treatments
There is an experiment for a new soreness treatment, and you want to compare patients that received the new treatment versus the old one. You will fit a Kaplan-Meier estimator to each set of patient data and visualize their survival curves side-by-side.
The DataFrame is called recur
and contains columns
age
: the age of the patient;treat
: the treatment that the patient received (0 if new, 1 if old);duration
: the duration post treatment in hours;censor
: whether the event is censored;
The pandas
package is loaded as pd
, the KaplanMeierFitter
class is imported from lifelines
, and the pyplot
module has been import from matplotlib
as plt
.
Additionally, a KaplanMeierFitter
instance called kmf
and a subplot figure called ax
have been created for you.
This exercise is part of the course
Survival Analysis in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Mask for new treatment
new = (____)