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The book provides an accessible but comprehensive overview of methods for mediation and interaction. There has been considerable and rapid methodological development on mediation and moderation/interaction analysis within the causal-inference literature over the last ten years. Much of this material appears in a variety of specialized journals, and some of the papers are quite technical. There has also been considerable interest in these developments from empirical researchers in the social and biomedical sciences. However, much of the material is not currently in a format that is accessible to them. The book closes these gaps by providing an accessible, comprehensive, book-length coverage of mediation. The book begins with a comprehensive introduction to mediation analysis, including chapters on concepts for mediation, regression-based methods, sensitivity analysis, time-to-event outcomes, methods for multiple mediators, methods for time-varying mediation and longitudinal data, and relations between mediation and other concepts involving intermediates such as surrogates, principal stratification, instrumental variables, and Mendelian randomization. The second part of the book concerns interaction or "moderation," including concepts for interaction, statistical interaction, confounding and interaction, mechanistic interaction, bias analysis for interaction, interaction in genetic studies, and power and sample-size calculation for interaction. The final part of the book provides comprehensive discussion about the relationships between mediation and interaction and unites these concepts within a single framework. This final part also provides an introduction to spillover effects or social interaction, concluding with a discussion of social-network analyses.The book is written to be accessible to anyone with a basic knowledge of statistics. Comprehensive appendices provide more technical details for the interested reader. Applied empirical examples from a variety of fields are used throughout.
This book investigates the methodological advancements in mediation and interaction analysis to provide a unified, accessible framework for causal inference. Tyler J. VanderWeele, a professor at Harvard University, synthesizes complex developments from the last decade of causal-inference literature. By bridging the gap between highly technical journal papers and the practical needs of empirical researchers, the author provides a structured approach to understanding how variables influence outcomes through intermediate mechanisms and moderating factors.
What You Will Find
Experts recognize this work as a foundational text that successfully translates advanced statistical theory into practical applications for social and biomedical scientists. Readers frequently note that while the prose remains accessible to those with basic statistical knowledge, the inclusion of technical appendices ensures the text remains rigorous enough for advanced practitioners.
Page Count:
728
Publication Date:
2015-01-01
Publisher:
Oxford University Press
ISBN-10:
019932588X
ISBN-13:
9780199325887
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