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

Product type Paperback

Published in Nov 2024

Publisher Packt

ISBN-13 9781837639021

Length 382 pages

Edition 1st Edition

Languages

Concepts

Data Science

Author (1):

Subhajit Das

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Table of Contents (21) Chapters

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

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20. Other Books You May Enjoy

Getting started with R

In this venture, the first step is setting up the R environment. This involves installing two key components: R itself and RStudio, a popular integrated development environment (IDE) that makes using R easier and more efficient.

Setting up the R environment

R can be downloaded from the Comprehensive R Archive Network (CRAN) [1] by Windows and macOS users. The installation process is straightforward: run the downloaded file and follow the on-screen instructions, accepting the default settings that are suitable for most users. For Linux and Unix systems, you can install R packages using their package management tool. Please follow the tutorial here for supportive guidance [2].

Once R is installed, the next step is to install RStudio, which provides a user-friendly interface for working with R. Download RStudio from its official website [3, 4], selecting the free version, the RStudio Desktop Open Source license.

Navigating the RStudio interface

Figure...

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

Table of Contents (21) Chapters

Getting started with R

Setting up the R environment

Navigating the RStudio interface

Authors (1)

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

Table of Contents (21) Chapters

Getting started with R

Setting up the R environment

Navigating the RStudio interface

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Authors (1)

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