Book contents
- Dyadic Health Science
- Advances in Personal Relationships
- Dyadic Health Science
- Copyright page
- Dedication
- Contents
- Tables
- Acknowledgments
- Introduction
- Part I Origins, Influences, and Journeys in Dyadic Health Science
- Part II Theories, Frameworks, and Methods
- 2 Established Dyadic Health Theories and Frameworks
- 3 Emerging Dyadic Health Theories and Frameworks
- 4 Designing Dyadic Research
- 5 Dyadic Quantitative Methods
- 6 Dyadic Qualitative Methods and Mixed Methods
- Part III Current and Exciting Research in Dyadic Health Science
- Part IV Where Do We Need to Go in Dyadic Health Science and How Do We Get There?
- References
- Index
5 - Dyadic Quantitative Methods
from Part II - Theories, Frameworks, and Methods
Published online by Cambridge University Press: 09 January 2026
Book contents
- Dyadic Health Science
- Advances in Personal Relationships
- Dyadic Health Science
- Copyright page
- Dedication
- Contents
- Tables
- Acknowledgments
- Introduction
- Part I Origins, Influences, and Journeys in Dyadic Health Science
- Part II Theories, Frameworks, and Methods
- 2 Established Dyadic Health Theories and Frameworks
- 3 Emerging Dyadic Health Theories and Frameworks
- 4 Designing Dyadic Research
- 5 Dyadic Quantitative Methods
- 6 Dyadic Qualitative Methods and Mixed Methods
- Part III Current and Exciting Research in Dyadic Health Science
- Part IV Where Do We Need to Go in Dyadic Health Science and How Do We Get There?
- References
- Index
Summary
Chapter 5 provides an overview of numerous quantitative approaches to analyzing dyadic data, both cross-sectionally and longitudinally. We begin with a focus on models that address research questions about self and partner influence, such as the actor-partner interdependence model (APIM), and then highlight models that allow researchers to analyze variables that are dyadic in nature, such as the common fate model (CFM). We then explore models that are particularly well-suited to data that are micro-level in measurement, such as daily diary data, including grid sequence analysis. We include approaches to examining congruence and similarity within dyads, and end with important caveats about measurement invariance and structural equation modeling versus multilevel modeling approaches.
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- Dyadic Health ScienceTheories, Methods, and Future Directions, pp. 97 - 111Publisher: Cambridge University PressPrint publication year: 2025
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