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Course

Survival Analysis in Python

AdvancedSkill Level

4.6+

Updated 06/2024

Use survival analysis to work with time-to-event data and predict survival time.

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PythonProbability & Statistics4 hr16 videos48 Exercises3,850 XP5,130Statement of Accomplishment

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Course Description

How long does it take for flu symptoms to show after exposure? And what if you don't know when people caught the virus? Do salary and work-life balance influence the speed of employee turnover? Lots of real-life challenges require survival analysis to robustly estimate the time until an event to help us draw insights from time-to-event distributions. This course introduces you to the basic concepts of survival analysis. Through hands-on practice, you’ll learn how to compute, visualize, interpret, and compare survival curves using Kaplan-Meier, Weibull, and Cox PH models. By the end of this course, you’ll be able to model survival distributions, build pretty plots of survival curves, and even predict survival durations.

Prerequisites

Introduction to Regression with statsmodels in Python Hypothesis Testing in Python

1

Introduction to Survival Analysis

What is survival analysis?

What problems does survival analysis solve?

Choose the right data for survival analysis

Why use survival analysis?

Identify the censorship type

Preprocess censored data

First look at censored data

Your first survival curve!

Draw a survival curve

Long live democracy!

2

Survival Curve Estimation

Fitting a Kaplan-Meier estimator

How to fit a Kaplan-Meier estimator?

Heart disease patient survival

Visualizing your Kaplan-Meier model

Plotting the survival curve

Patient soreness treatment

Applying survival analysis to groups

Senators' terms in office

Comparing patient soreness treatments

The log-rank test

Appropriate data for log-rank test

Plotting and comparing survival curves

Log-rank test

3

The Weibull Model

Fitting the Weibull model

Model prison data with Weibull

Compare Weibull model parameters

Weibull model with covariates

Analyze heart patients characteristics

Explore gender-LVDD interaction

Visualization and prediction with Weibull model

How do prior arrests impact re-arrest rate?

Predict re-arrest rate

Other distributions and model selection

How good is the fit?

Choose a parametric model

4

The Cox PH Model

Fitting the Cox Proportional Hazards model

Model prison data with Cox PH

Custom Cox PH model

Interpreting the Cox PH model

Cox PH model survival time

Plot covariate effects on survival

The proportional hazards assumption

Test the PH assumption with KM curves

Test the PH assumption automatically

Predicting with the Cox PH model

Employee churn study

Predict before they leave!

Congratulations!

Survival Analysis in Python

Course
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*4.6

from 22 reviews

73%

23%

5%

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José Antonio

17 days

Fatima Tiemi

29 days

Relies on remembering the labels of the functions (which finally could be searched in the docs) more than actually treating the data or focus on the interpretation

Minori

29 days

Javed

about 1 month

Peng

about 1 month

Filip

about 2 months

Minori

Javed

Peng

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