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An Idiographic Approach to Estimating Models of Dyadic Interactions with Differential Equations

Published online by Cambridge University Press:  01 January 2025

Joel S. Steele ,
Emilio Ferrer  and
John R. Nesselroade
Joel S. Steele*
Affiliation:
Portland State University
Emilio Ferrer
Affiliation:
University of California Davis
John R. Nesselroade
Affiliation:
University of Virginia
*
Requests for reprints should be sent to Joel S. Steele, Psychology Department, Portland State University, 1721 SW Broadway, Portland, Oregon 97201, USA. E-mail: j.s.steele@pdx.edu
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Abstract

We present an idiographic approach to modeling dyadic interactions using differential equations. Using data representing daily affect ratings from romantic relationships, we examined several models conceptualizing different types of dyadic interactions. We fitted each model to each of the dyads and the resulting AICc values were used to classify the most likely configuration of interaction for each dyad. Additionally, the AICc from the different models were used in parameter averaging across models. Averaged parameters were used in models involving predictors of relationship dynamics, as indexed by these parameters, as well as models wherein the parameters predicted distal outcomes of the dyads such as relationship satisfaction and status. Results indicated that, within our sample, the most likely interaction style was that of independence, without evidence of emotional interrelations between the two individuals in the couple. Attachment-related avoidance and anxiety showed significant relations with model parameters, such that ideal levels of affect for males were negatively influenced by higher levels of avoidance from their partner while their own levels of anxiety had positive effects on their levels of dyadic coregulation. For females coregulation was negatively influenced by both time in the relationship and their partner’s level of avoidance. Analysis involving distal outcomes showed modest influences from the individual’s level of ideal affect.

Keywords

dyadic interactionsmodel averagingdifferential equationsdyadographic analysisidiographic

Information

Type
Original Paper
Information
Psychometrika , Volume 79 , Issue 4 , October 2014 , pp. 675 - 700
Copyright
Copyright © 2013 The Psychometric Society

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