BookTyler VanderWeele.
Summary: "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 given throughout. Software implementation in SAS, Stata, SPSS, and R is provided. The book should be accessible to students and researchers who have completed a first-year graduate sequence in quantitative methods in one of the social- or biomedical-sciences disciplines. The book will only presuppose familiarity with linear and logistic regression, and could potentially be used as an advanced undergraduate book as well"-- Provided by publisher
Contents:
Cover; Explanation in Causal Inference; Copyright; Dedication; Contents; Preface; Part 1 Mediation Analysis; 1 Explanation and Mechanism; 1.1 Causal Inference and Explanation; 1.2 Forms of Explanation and Types of Mechanisms; 1.3 Motivations for Assessing Mediation, Interaction, and Interference; 1.4 Organization of this Book; 2 Mediation: Introduction and Regression-Based Approaches; 2.1 Classic Regression Approach to Mediation Analysis; 2.2 Counterfactual Approach to Mediation Analysis: Continuous Outcomes; 2.3 Assumptions about Confounding; 2.4 Binary and Count Outcomes. 2.5 Binary Mediators2.6 Comparison of Approaches: Product-of-Coefficient and Difference Methods; 2.7 Description of the SAS Macro; 2.8 Description of the SPSS Macro; 2.9 Description of the Stata Macro; 2.10 Hypothetical Example with Output; 2.11 Empirical Example in Genetic Epidemiology; 2.12 When to Include an Exposure
Mediator Interaction; 2.13 Proportion Mediated; 2.14 Proportion Eliminated; 2.15 Study Design and Mediation Analysis; 2.16 Counterfactual Notation for Natural Direct and Indirect Effects; 2.17 An Alternative Regression-Based Estimation Approach Using Simulations. 2.18 Code for the Simulation-Based Approach in R2.19 Discussion; 3 Sensitivity Analysis for Mediation; 3.1 Sensitivity Analysis for Unmeasured Confounding for Total Effects; 3.2 Sensitivity Analysis for Unmeasured Confounding for Controlled Direct Effects; 3.3 Sensitivity Analysis for Unmeasured Confounding for Natural Direct and Indirect Effects; 3.4 Sensitivity Analysis Using Two Trials; 3.5 Sensitivity Analysis for Direct and Indirect Effects in the Presence of Measurement Error; 3.6 Discussion; 4 Mediation Analysis with Survival Data. 4.1 Earlier Literature on Mediation Analysis with Survival Models4.2 Mediation Analysis with an Accelerated Failure Time Model; 4.3 Mediation Analysis with a Proportional Hazards Model; 4.4 Mediation with an Additive Hazard Model; 4.5 A Weighting Approach to Direct and Indirect Effects with Survival Outcomes; 4.6 Sensitivity Analysis with Survival Data; 4.7 Discussion; 5 Multiple Mediators; 5.1 Regression-Based Approaches to Multiple Mediators; 5.2 A Weighting Approach to Multiple Mediators; 5.3 Controlled Direct Effects and Exposure-Induced Confounding. 5.4 Effect Decomposition with Exposure-Induced Confounding5.5 Path-Specific Effects; 5.6 Sensitivity Analysis for Exposure-Induced Confounding; 5.7 Discussion; 6 Mediation Analysis with Time-Varying Exposures and Mediators; 6.1 Notation and Definitions; 6.2 Controlled Direct Effects with Time-Varying Exposures and Mediators; 6.3 Natural Direct and Indirect Effects and their Randomized Interventional Analogues with Time-Varying Exposures and Mediators; 6.4 Counterfactual Analysis of MacKinnon's Three-Wave Mediation Model; 6.5 Discussion; 7 Selected Topics in Mediation Analysis.