Mcbee, Matthew creator author. text bibliography cau 2021 monographic eng

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xi, 234 pages : illustrations ; 24 cm. "A practical, up-to-date, step-by-step and accessible introduction to causal inference in quantitative research. Featuring worked example datasets throughout, it clearly outlines the steps involve in carrying out various types of statistical causal analysis. Matthew McBee evaluates the issue of causal inference in quantitative research, while providing guidance on how to apply these analyses to data, discussing key concepts such as: directed acyclic graphs (DAGs), Rubin’s Causal Model (RCM), Propensity Score Analysis, and Regression Discontinuity Design." Introduction -- Conditioning -- Directed acyclic graphs -- Rubin's causal model and the propensity score -- Propensity score analysis -- Instrumental variable analysis -- Regression discontinuity design -- Conclusion. Matthew Mcbee. Includes bibliographical references and index. Causation Causation Statistical methods Casual inference Statistical methods Statistics HA29 .M4384 2021 519.53 M459s 9781526424730 CSPC 241009 20250902163739.0 eng