Statistical Approaches to Causal Analysis

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 application 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

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