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 = (____)