Book contents
- Interpersonal Emotion Dynamics in Close Relationships
- Studies in Emotion and Social Interaction
- Interpersonal Emotion Dynamics in Close Relationships
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Foreword
- Introduction
- Chapter 1 Conceptual approaches to studying interpersonal emotion dynamics
- Chapter 2 A general framework for capturing interpersonal emotion dynamics
- Chapter 3 Simplifying the complexity of interpersonal emotion dynamics with regression graphics
- Chapter 4 Methodological approaches to studying interpersonal emotion dynamics
- Chapter 5 Biochemical contributions to interpersonal emotion dynamics
- Chapter 6 Physiological correlates associated with interpersonal emotion dynamics
- Chapter 7 Interpersonal emotion dynamics in families
- Chapter 8 Interpersonal emotion dynamics within young adult romantic and peer relationships
- Chapter 9 Interpersonal emotion dynamics within intimate relationships
- Chapter 10 Next steps toward understanding interpersonal emotion dynamics
- Author Index
- Subject Index
- Studies in Emotion and Social Interaction
- References
Chapter 3 - Simplifying the complexity of interpersonal emotion dynamics with regression graphics
Published online by Cambridge University Press: 14 September 2018
Book contents
- Interpersonal Emotion Dynamics in Close Relationships
- Studies in Emotion and Social Interaction
- Interpersonal Emotion Dynamics in Close Relationships
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Foreword
- Introduction
- Chapter 1 Conceptual approaches to studying interpersonal emotion dynamics
- Chapter 2 A general framework for capturing interpersonal emotion dynamics
- Chapter 3 Simplifying the complexity of interpersonal emotion dynamics with regression graphics
- Chapter 4 Methodological approaches to studying interpersonal emotion dynamics
- Chapter 5 Biochemical contributions to interpersonal emotion dynamics
- Chapter 6 Physiological correlates associated with interpersonal emotion dynamics
- Chapter 7 Interpersonal emotion dynamics in families
- Chapter 8 Interpersonal emotion dynamics within young adult romantic and peer relationships
- Chapter 9 Interpersonal emotion dynamics within intimate relationships
- Chapter 10 Next steps toward understanding interpersonal emotion dynamics
- Author Index
- Subject Index
- Studies in Emotion and Social Interaction
- References
Summary
This chapter shows how to evaluate the assumptions that underlie dynamical systems modeling often applied to dyadic outcomes, and how to communicate the results; both through graphical methods. First the chapter provides a conceptual overview of dynamical systems theory (DST) as applied to interpersonal emotion processes. This conceptual framework is then integrated into regression logic wherein the assumptions of regression are merged with the assumptions of DST. The chapter then goes through an example using second-by-second heart rate taken from a couple over a ten-minute period. Each time series are examined individually and then simultanouslysimultaneously. Special attention is given towards the role of set points, stability, coupling, and nonlinear dynamics, all of which are of particular importance within the interpersonal emotion circumstance. Syntax for all the figures are provided in R.
- Type
- Chapter
- Information
- Interpersonal Emotion Dynamics in Close Relationships , pp. 47 - 74Publisher: Cambridge University PressPrint publication year: 2018
References
Boker, S. M., & Laurenceau, J. P. (2006). Dynamical systems modeling: an application to the regulation of intimacy and disclosure in marriage. In Walls, T. A. & Schafer, J. L. (Eds.) Models for Intensive Longitudinal Data (pp. 195–218). New York, NY: Oxford University Press.CrossRefGoogle Scholar
Butler, E. A. (2011). Temporal interpersonal emotion systems the “TIES” that form relationships. Personality and Social Psychology Review, 15(4), 367–93.CrossRefGoogle ScholarPubMed
Butler, E. A., & Gross, J. J. (2009). Emotion and emotion regulation: integrating individual and social levels of analysis. Emotion Review, 1(1), 86–7.CrossRefGoogle Scholar
Butler, E. A., & Randall, A. K. (2013). Emotional coregulation in close relationships. Emotion Review, 5, 202–10.Google Scholar
Butner, J. E., Behrends, A. A., & Baucom, B. R. (2017). Mapping co-regulation in social relations through exploratory topology analysis. In Vallacher, R. R., Read, S. J., & Nowak's, A. (Eds.) Computational Social Psychology. New York, NY: Psychology Press.Google Scholar
Butner, J. E., Gagnon, K. T., Geuss, M. N., Lessard, D. A., & Story, T. N. (2014). Utilizing topology to generate and test theories of change. Psychological Methods, 20(1), 1.Google Scholar
Casdagli, M., Eubank, S., Farmer, J. D., & Gibson, J. (1991). State space reconstruction in the presence of noise. Physica D: Nonlinear Phenomena, 51(1), 52–98.CrossRefGoogle Scholar
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. Mahwah, NJ: Routledge.Google Scholar
Cook, W. L., & Kenny, D. A. (2005). The actor-partner interdependence model: a model of bidirectional effects in developmental studies. International Journal of Behavioral Development, 29, 101–9.Google Scholar
Helm, J. L., Sbarra, D., & Ferrer, E. (2012). Assessing cross-partner associations in physiological responses via coupled oscillator models. Emotion, 12(4), 748.Google Scholar
Jennings, J. R., Bberg, W. K., Hutcheson, J. S., et al. (1981). Publication guidelines for heart rate studies in man. Psychophysiology, 18, 226–31.CrossRefGoogle ScholarPubMed
Kenny, D. A., Kashy, D. A., & Cook, W. L. (2006). Dyadic Data Analysis. New York, NY: Guilford.Google Scholar
Perry, N. S., Baucom, K. J. W., Bourne, S., et al. (2017). Graphic methods for interpreting longitudinal dyadic patterns from repeated-measures actor-partner interdependence models. Journal of Family Psychology. doi: 10.1037/fam0000293Google Scholar
Preston, S. D., & Hofelich, A. J. (2012). The many faces of empathy: parsing empathic phenomena through a proximate, dynamic-systems view of representing the other in the self. Emotion Review, 4, 24–33.Google Scholar
Ramseyer, F., Kupper, Z., Caspar, F., Znoj, H., & Tschacher, W. (2014). Time-series panel analysis (TSPA): multivariate modeling of temporal associations in psychotherapy process. Journal of Consulting and Clinical Psychology, 82, 828.CrossRefGoogle ScholarPubMed
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (Volume 1). Thousand Oaks, CA: Sage.Google Scholar
Scherer, K. R. (2009) The dynamic architecture of emotion: evidence for the component process model. Cognition and Emotion 23(7), 1307–51.Google Scholar
Takens, F. (1981). Detecting strange attractors in turbulence. In Dynamical Systems and Turbulence, Warwick 1980 (pp. 366–81). Berlin Heidelberg: Springer.Google Scholar
Thelen, E., & Smith, L. B. (1996). A Dynamic Systems Approach to the Development of Cognition and Action. Cambridge, MA: MIT Press.Google Scholar
Vallacher, R. R., & Nowak, A. E. (1994). Dynamical Systems in Social Psychology. San Diego, CA: Academic Press.Google Scholar
- 3
- Cited by