Statistical Approaches to Causal Analysis
Book information
Description
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 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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