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Building Statistical Models in Python

You're reading from  Building Statistical Models in Python

Product type Book
Published in Aug 2023
Publisher Packt
ISBN-13 9781804614280
Pages 420 pages
Edition 1st Edition
Languages
Concepts
Authors (3):
Huy Hoang Nguyen Huy Hoang Nguyen
Profile icon Huy Hoang Nguyen
Paul N Adams Paul N Adams
Profile icon Paul N Adams
Stuart J Miller Stuart J Miller
Profile icon Stuart J Miller
View More author details

Table of Contents (22) Chapters

Preface 1. Part 1:Introduction to Statistics
2. Chapter 1: Sampling and Generalization 3. Chapter 2: Distributions of Data 4. Chapter 3: Hypothesis Testing 5. Chapter 4: Parametric Tests 6. Chapter 5: Non-Parametric Tests 7. Part 2:Regression Models
8. Chapter 6: Simple Linear Regression 9. Chapter 7: Multiple Linear Regression 10. Part 3:Classification Models
11. Chapter 8: Discrete Models 12. Chapter 9: Discriminant Analysis 13. Part 4:Time Series Models
14. Chapter 10: Introduction to Time Series 15. Chapter 11: ARIMA Models 16. Chapter 12: Multivariate Time Series 17. Part 5:Survival Analysis
18. Chapter 13: Time-to-Event Variables – An Introduction 19. Chapter 14: Survival Models 20. Index 21. Other Books You May Enjoy

Kaplan-Meier model

The first model for survival analysis we will discuss is the Kaplan-Meier model (also called the Kaplan-Meier estimator). We will start this section with a discussion model definition and learn how it is built. Then, we will close this section with an example of how to use this model in Python using the lifelines library. Let’s get started.

Model definition

The Kaplan-Meier estimator is defined by the following formula:

 ˆ S (t) =  i:t it  n i d i _ n i 

Here, n i is the number of subjects at risk just before time t, d i is the number of death events at time t, and  ˆ S (t) (the survival function) is the probability that life is longer than t. The Π symbol used in the formula is like the symbol Σ; however, Π indicates multiplication. This means that the preceding formula will result in a multiplication...

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