Introduction to Statistical Mediation Analysis
Abstract
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.
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A wide sample of individuals from the general population was analyzed with strong statistical methodologies providing good results.
“A wide sample of individuals from the general population was analyzed with strong statistical methodologies (Iacobucci et al., 2007; MacKinnon, 2012; MacKinnon et al., 2012, 2013) providing good results (McDonald and Ho, 2002; Hayes, 2009; Iacobucci, 2010; Preacher, 2015).”
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- Authors
- MacKinnon, D. P.
- Affiliations
- Arizona State University (US)
- Corresponding author
- MacKinnon, David P.
- ORCID
- MacKinnon, David P.
- Venue
- Routledge eBooks
- Publisher
- Routledge
- Published
- 2012-10-02
- OpenAlex
- W1640894779
- Cited by
- 5,618
- References
- 0
- Citations by year
- 2026: 99 · 2025: 249 · 2024: 277 · 2023: 321 · 2022: 321 · 2021: 397 · 2020: 424 · 2019: 386 · 2018: 357 · 2017: 344 · 2016: 343 · 2015: 399 · 2014: 415 · 2013: 361 · 2012: 307
- FWCI
- 120.65
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Routledge eBooks (publishedVersion)
- CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Keywords
- mediation analysis, mediating effect, path analysis, multilevel mediation, longitudinal mediation, categorical variables, moderation, confidence limits
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