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4 - Analyzing Cross-Sectional and Longitudinal Data in Close Relationships

from Part I - Foundations for Studying Relationships

Published online by Cambridge University Press:  11 June 2018

By
Deborah A. Kashy ,
Robert A. Ackerman  and
M. Brent Donnellan
Edited by
Anita L. Vangelisti  and
Daniel Perlman
Anita L. Vangelisti
Affiliation:
University of Texas, Austin
Daniel Perlman
Affiliation:
University of North Carolina, Greensboro
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Summary

In this chapter, we first briefly review the major personality variables that have been studied in the context of close relationships, focusing primarily on romantic relationships. We review both broadband traits (the "Big Five" personality dimensions) and more narrowly defined traits (attachment orientations and regulatory focus orientations). Next, we explain why and how the personality traits of both partners involved in close relationships should shape the relational dynamics that unfold between them, and why studies that adopt dyadic approaches permit greater progress toward understanding the role of personality in relationships than studies that are individual-centered. Following this, we discuss the Actor-Partner Interdependence Model (APIM; Kenny, Kashy, & Cook, 2006), which allows researchers to determine whether and how an individual’s relational experiences and outcomes are affected not only by his/her own traits (actor effects), but also by the traits of his/her partner (partner effects) and the combination of both partners’ traits (actor-partner interaction effects). We then review some representative relationship studies that have examined partner effects and/or actor-partner interaction effects, focusing on the Big Five, attachment orientations, and regulatory focus orientations. We conclude the chapter by highlighting promising future directions in which the study of personality and relationships might head.
Type
Chapter
Information
The Cambridge Handbook of Personal Relationships , pp. 49 - 64
Publisher: Cambridge University Press
Print publication year: 2018

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