This volume introduces the statistical, methodological, and conceptual aspects of mediation analysis. Applications from health, social, and developmental psychology, sociology, communication, exercise science, and epidemiology are emphasized throughout. Single-mediator, multilevel, and longitudinal models are reviewed. The author's goal is to help the reader apply mediation analysis to their own data and understand its limitations.
Each chapter features an overview, numerous worked examples, a summary, and exercises (with answers to the odd numbered questions). The accompanying CD contains outputs described in the book from SAS, SPSS, LISREL, EQS, MPLUS, and CALIS, and a program to simulate the model. The notation used is consistent with existing literature on mediation in psychology.
The book opens with a review of the types of research questions the mediation model addresses. Part II describes the estimation of mediation effects including assumptions, statistical tests, and the construction of confidence limits. Advanced models including mediation in path analysis, longitudinal models, multilevel data, categorical variables, and mediation in the context of moderation are then described. The book closes with a discussion of the limits of mediation analysis, additional approaches to identifying mediating variables, and future directions.
Introduction to Statistical Mediation Analysis is intended for researchers and advanced students in health, social, clinical, and developmental psychology as well as communication, public health, nursing, epidemiology, and sociology. Some exposure to a graduate level research methods or statistics course is assumed. The overview of mediation analysis and the guidelines for conducting a mediation analysis will be appreciated by all readers.
Table of Contents
Preface. Introduction. Applications of the Mediation Model. Single Mediator Model. Single Mediator Model Details. Multiple Mediator Model. Path Analysis Mediation Models. Latent Variable Mediation Models. Longitudinal Mediation Models. Multilevel Mediation Models. Mediation and Moderation. Mediation in Categorical Data Analysis. Computer Intensive Methods for Mediation Models. Causal Inference for Mediation Models. Additional Approaches to Identifying Mediating Variables. Conclusions and Future Directions. Appendices: Answers to Odd-Numbered Exercises. Notation.
"Dave MacKinnon's book will be a welcome addition to the field. The topic of statistical mediation is important for researchers who want to examine models more complex than simple prediction." -Lisa L. Harlow, PhD, University of Rhode Island
"Overall, I found these chapters to be uniformly excellent. The text was well written, nicely organized, and technically rigorous while remaining broadly accessible." -Patrick Curran, PhD, University of North Carolina, Chapel Hill
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