Survival Analysis in Python [Time to event analysis]

Published: 16 October 2021
on channel: The Researchers' Guide

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Survival analysis is a branch of statistics for analysing the expected duration of time until one or more events occur. This topic is called reliability analysis in engineering, duration analysis or duration modelling or time to event analysis in economics, and event history analysis in sociology. Survival analysis attempts to answer the following questions:

Proportion of population surviving up to a given time
Rate at which they are dying
How predictors could explain the time to event analysis

There are plenty of application scenarios, where we could utilize survival analysis. Some are described as follows:

After diagnose with cancer when a patent would die
Hospital readmission duration after a major heart surgery
When would Tesla car battery permanently die/fail
Waiting time of pedestrian after red (do-not walk) phase arrival at intersection
After seeing ads when a person would purchase the product
When an employee would leave a company (churn)

Reading resources
Blog1: https://sphweb.bumc.bu.edu/otlt/mph-m...

Blog2: https://boostedml.com/2018/11/when-sh...

Survival analysis concept videos
MarinStatsLectures-R Programming & Statistics
• Survival Analysis Part 1 | What is Censoring?

Zedstatistics
• Introduction to Survival Analysis [1/8]

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