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Causal Inference in R

You're reading from   Causal Inference in R Decipher complex relationships with advanced R techniques for data-driven decision-making

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781837639021
Length 382 pages
Edition 1st Edition
Languages
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Author (1):
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Subhajit Das Subhajit Das
Author Profile Icon Subhajit Das
Subhajit Das
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Table of Contents (21) Chapters Close

Preface 1. Part 1:Foundations of Causal Inference
2. Chapter 1: Introducing Causal Inference FREE CHAPTER 3. Chapter 2: Unraveling Confounding and Associations 4. Chapter 3: Initiating R with a Basic Causal Inference Example 5. Part 2: Practical Applications and Core Methods
6. Chapter 4: Constructing Causality Models with Graphs 7. Chapter 5: Navigating Causal Inference through Directed Acyclic Graphs 8. Chapter 6: Employing Propensity Score Techniques 9. Chapter 7: Employing Regression Approaches for Causal Inference 10. Chapter 8: Executing A/B Testing and Controlled Experiments 11. Chapter 9: Implementing Doubly Robust Estimation 12. Part 3: Advanced Topics and Cutting-Edge Methods
13. Chapter 10: Analyzing Instrumental Variables 14. Chapter 11: Investigating Mediation Analysis 15. Chapter 12: Exploring Sensitivity Analysis 16. Chapter 13: Scrutinizing Heterogeneity in Causal Inference 17. Chapter 14: Harnessing Causal Forests and Machine Learning Methods 18. Chapter 15: Implementing Causal Discovery in R 19. Index 20. Other Books You May Enjoy

Introducing Causal Inference

In this inaugural chapter, let’s explore the topic of causal inference a bit. For some, this may be a new topic; for others, it might be somewhat familiar. However, whether you find this topic intimidating or not depends less on your existing statistical knowledge and more on your interest in the subject and your consistent effort throughout the book.

Our exploration begins with three pivotal questions: What exactly is causal inference? Why is it indispensable? How can it be effectively utilized? To clarify these concepts, we’ll use both fictitious and real-life scenarios.

Approach this chapter with unhindered curiosity and an open mind. Be prepared to encounter concepts and terminology that might initially seem abstruse. Don’t worry, though—we will be with you every step of the way, ensuring you understand everything clearly and thoroughly as we explore causal inference together.

In this chapter, we will cover the following...

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Causal Inference in R
Published in: Nov 2024
Publisher: Packt
ISBN-13: 9781837639021
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