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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

Is it an association or really causation?

It’s tempting to attribute causality to superficial observations, mistaking mere associations for causation. Take, for instance, the observation that social media posts made later in the day receive fewer likes and comments, suggesting reduced engagement. One might hastily conclude that the timing of these posts is the causal factor. However, without rigorous statistical testing, such claims remain speculative. In this book, we will teach you how to conduct these necessary tests, distinguishing between simple association and true causation.

In statistics, we discuss association, causation, and correlation. While correlation is often used interchangeably with association in everyday conversations, they have distinct meanings in statistical contexts. So, what is the difference between association and correlation?

In causality, association encapsulates a general linkage between two variables, without explicitly characterizing the...

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