Custom Cox PH model
You have isolated three factors that are statistically significant at the 0.05 level in the previous exercise: fin, age, and prio.
fin: if the convict received financial assistance, hazards decrease by 31%;age: for each age older than average, hazards decrease by 5%;prio: for each prior arrest more than average, hazards increase by 9%.
Let's build a custom Cox PH model using these covariates.
The CoxPHFitter class has been imported for you, and the pandas and numpy libraries are imported as pd and np, respectively. Use the console to explore the DataFrame prison and its column names as needed.
This exercise is part of the course
Survival Analysis in Python
Exercise instructions
- Instantiate a
CoxPHFitterclass calledcustom_cph. - Fit
custom_cphwith a custom regression modelfin + age + priousing theformulaparameter. - Get the model summary of
cphand print it.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Instantiate CoxPHFitter class
custom_cph = ____
# Fit custom model
____
# Print model summary
print(____)