Book contents
- The Cambridge Handbook of Research Methods in Clinical Psychology
- The Cambridge Handbook of Research Methods in Clinical Psychology
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Acknowledgments
- Part I Clinical Psychological Science
- Part II Observational Approaches
- Part III Experimental and Biological Approaches
- Part IV Developmental Psychopathology and Longitudinal Methods
- Part V Intervention Approaches
- Part VI Intensive Longitudinal Designs
- Part VII General Analytic Considerations
- 28 Reproducibility in Clinical Psychology
- 29 Meta-Analysis
- 30 Mediation, Moderation, and Conditional Process Analysis
- 31 Statistical Inference for Causal Effects in Clinical Psychology
- 32 Analyzing Nested Data
- 33 Missing Data Analyses
- 34 Machine Learning for Clinical Psychology and Clinical Neuroscience
- Index
- References
30 - Mediation, Moderation, and Conditional Process Analysis
Regression-Based Approaches for Clinical Research
from Part VII - General Analytic Considerations
Published online by Cambridge University Press: 23 March 2020
Book contents
- The Cambridge Handbook of Research Methods in Clinical Psychology
- The Cambridge Handbook of Research Methods in Clinical Psychology
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Acknowledgments
- Part I Clinical Psychological Science
- Part II Observational Approaches
- Part III Experimental and Biological Approaches
- Part IV Developmental Psychopathology and Longitudinal Methods
- Part V Intervention Approaches
- Part VI Intensive Longitudinal Designs
- Part VII General Analytic Considerations
- 28 Reproducibility in Clinical Psychology
- 29 Meta-Analysis
- 30 Mediation, Moderation, and Conditional Process Analysis
- 31 Statistical Inference for Causal Effects in Clinical Psychology
- 32 Analyzing Nested Data
- 33 Missing Data Analyses
- 34 Machine Learning for Clinical Psychology and Clinical Neuroscience
- Index
- References
Summary
Clinical psychological science is improved when it seeks to understand not only whether an effect exists but also how that effect operates and its boundary conditions. Mediation and moderation analysis are widely used in clinical psychological research to explore and test hypotheses about the mechanisms by which causal effects operate and the contingencies of those effects. Their integration as conditional process analysis allows for the examination of the contingencies of those mechanisms – for whom or in what circumstances a particular mechanism is in operation or whether it is strong as opposed to weak. This chapter reviews the fundamentals of mediation, moderation, and conditional process analysis using ordinary least squares regression, commenting along the way on good practice as well as various misunderstandings in circulation. It illustrates the application of these fundamentals and their implementation using the PROCESS macro for SPSS and SAS.
- Type
- Chapter
- Information
- Publisher: Cambridge University PressPrint publication year: 2020
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