Statistical Approaches to Causal Analysis

✍ Scribed by Matthew McBee

Publisher: SAGE Publications
Year: 2022
Tongue: English
Leaves: 265
Series: The SAGE Quantitative Research Kit
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

A practical, up-to-date, step-by-step guidance on causal analysis for advancing students, this volume of the SAGE Quantitative Research kit features worked example datasets throughout to clearly demonstrate the appication of these powerful techniques, giving students the know-how and the confidence to succeed in their quantitative research journey.

Matthew McBee evaluates the issue of causal inference in quantitative research, while providing guidance on how to apply these analyses to your data, discussing key concepts such as:

· Directed acyclic graphs (DAGs)

· Rubin’s Causal Model (RCM)

· Propensity Score Analysis

· Regression Discontinuity Design

✦ Table of Contents

STATISTICAL APPROACHES TO CAUSAL ANALYSIS - FRONT COVER
STATISTICAL APPROACHES TO CAUSAL ANALYSIS
COPYRIGHT
CONTENTS
LIST OF FIGURES AND TABLES
ABOUT THE AUTHOR
ACKNOWLEDGEMENTS
PREFACE
CHAPTER 1 - INTRODUCTION
CHAPTER 2 - CONDITIONING
CHAPTER 3 - DIRECTED ACYCLIC GRAPHS
CHAPTER 4 - RUBIN’S CAUSAL MODEL AND THE PROPENSITY SCORE
CHAPTER 5 - PROPENSITY SCORE ANALYSIS
CHAPTER 6 - INSTRUMENTAL VARIABLE ANALYSIS
CHAPTER 7 - REGRESSION DISCONTINUITY DESIGN
CHAPTER 8 - CONCLUSION
GLOSSARY
REFERENCES
INDEX

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