Statistical approaches to causal analysis / Matthew McBee.
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 causa...
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| Main Author: | |
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| Format: | Ebook |
| Language: | English |
| Published: |
London ; Thousand Oaks, California :
SAGE Publications Ltd,
[2021]
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| Series: | Sage qualitative research kit ;
v. 10 |
| Subjects: | |
| Online Access: | SAGE |
| Summary: | 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. |
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| Physical Description: | 1 online resource (xxix, 234 pages) : illustrations. |
| Bibliography: | Includes bibliographical references (pages 217-228) and index. |