Publisher
The University of Arizona.Rights
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.Abstract
Interpersonal relationships are seemingly contradictory, such that they provide an interpersonal context for experiencing and sharing life’s highs and lows while functioning to both alleviate and exacerbate emotional distress. Understanding the paradox between relationships and biopsychosocial wellbeing necessitates investigation of unfolding emotion dynamics that occur during real-time interactions. The conceptual understanding of relationships as regulatory systems is widespread, yet the modeling of temporal interpersonal emotion dynamics remains stymied largely due to the statistical expertise required to translate such conceptualizations into mathematical models. Thus, the overarching aim of my dissertation is to first introduce and then demonstrate how researchers can use analytical tools within the R package, rties, to turn established theory about emotions and social interactions into tractable models. In the first paper, I introduce the rties package, which provides user friendly tools for modeling temporal interpersonal dynamics. In this first paper, I do the following: (1) Describe two dynamic models supported by the current version of the package; (2) Demonstrate how to implement and interpret the results of these models using emotional experience time series data; and (3) Illustrate how the resulting classifications can be used as either predictors or outcomes of other variables of interest. In the second paper, I use tools provided in the rties package to model complex dynamic patterns of physiological linkage (i.e., statistical interdependence of partner’s physiology) and address two central questions: (1) Do different patterns arise depending on the measure of physiological linkage utilized? and 2) Are these patterns correlated with different biopsychosocial constructs? The work presented across the two papers should aid in making the modeling of interpersonal dynamics more accessible for social scientists; ultimately contributing to our understanding of the social-functional role that emotions play in social interactions.Type
Electronic Dissertationtext
Degree Name
Ph.D.Degree Level
doctoralDegree Program
Graduate CollegeFamily & Consumer Sciences