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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

Basic R programming concepts

For novices starting with R, it is imperative to initially grasp the fundamental aspects of various data types and data structures you can use. Such an understanding is critical for conducting proficient data analysis and programming.

Data types in R

Following are the commonly-used data types in R:

  • Numeric: Representing decimal or floating-point numbers, numeric is R’s default for numerical values. Assigning a value such as 4.5 or 10.2 in R automatically categorizes it as numeric.
  • Integers: These are whole numbers, devoid of fractional components. To designate a number as an integer, one appends the L suffix, as in 4L.
  • Characters: This data type is used for text or string values. Any sequence of characters, including letters, numbers, spaces, and symbols, enclosed in quotes (" ") is treated as character data.
  • Logical (Boolean): The logical data type, often referred to as Boolean, represents binary values: TRUE...
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