Actor‐Partner Interdependence Models (APIM) and Voting Behavior: Methodology and Applications

Abstract

Recently, the social sciences have witnessed a rising interest in dyadic design, as an efficient way to disentangle mechanisms of interpersonal influence. Despite the relevance of this design to political research, few efforts have been made to collect and efficiently analyze dyadic data. In this article, we suggest the ActorPartner Interdependence Model as a useful tool to test bidirectional effects in dyadic data on political attitudes and behaviors. The model explicitly assumes that members of a dyad (reciprocally identified as actor and partner) involved in political communication are interdependent and influence each other. We apply the model to estimate the effect of partner's party identification on actor's vote choice, using 1996 Indianapolis-St. Louis dyadic data. Results show that partner's party identification is significantly associated with vote choice. Moreover, we show that influence between dyad members is moderated by their intimacy and that an increased difference in socioeconomic status between dyad members tips the balance of the effect in favor of the individual with more resources. Our conclusions point to the effectiveness of APIM in modeling interdependent asymmetric relations and call for increasing efforts in collecting dyadic data and in developing proper tools for their analysis.

Interpersonal communication, voting behavior and influence in election campaigns: a directional approach

“…Finally, we account for an aspect of today's interpersonal influence literature that has rarely been taken into account: the asymmetry between members of the dyad (Mancosu and Vezzoni 2018). It has been stressed above that more knowledgeable discussants, having more interesting and persuading arguments, may increase the likelihood of influence over their political associates.…”

Dyadic measurement invariance and its importance for replicability in romantic relationship science

“…The scientific study of romantic dyads has evolved in short order from a relatively niche and straightforward topic, to a booming subfield of interdisciplinary social science that utilizes increasingly sophisticated methods and data analysis strategies. In the shift from oversimplified analyses of individuals in romantic dyadic contexts (Hill, Rubin, & Peplau, 1976; Rubin, 1970) to the more complex relationship science of romance that we know today (Finkel & Eastwick, 2008; Mancosu & Vezzoni, 2018; Muise, Christofides, & Desmarais, 2009), the importance of the development and dissemination of dyadic data analysis models (Kenny, Kashy, & Cook, 2006) cannot be overstated. By enabling researchers to appropriately account for the interdependence of observations within a dyad, analytic paradigms like the Actor‐Partner Interdependence Model (APIM; Cook & Kenny, 2005), the Common Fate Model (CFM; Ledermann & Kenny, 2012), the Mutual Influence Model (MIM; Kenny, 1996; Woody & Sadler, 2005), the Truth and Bias Model (TBM; West & Kenny, 2011), and dyadic response surface analyses (Schönbrodt, Humberg, & Nestler, 2018) have become mainstays of basic relationship science.…”

Contextual effects, awareness, and voting behaviour: Does knowing about local politics increase contextual influence?

“…Nevertheless, citizens do not interact with discussants they pick randomly from the territory. People share a certain number of ‘social spaces’ with their relevant others (Baybeck and McClurg, 2005; Huckfeldt and Sprague, 1995; Mancosu and Vezzoni, 2017a), namely, formal or informal groups in which they can socially interact – churches, workplaces, neighbourhoods, public places, and so on. The theory of geographical context influence argues (usually implicitly) that social spaces are partly affected by the prevalence of political preferences in the context surrounding them (Baybeck and McClurg, 2005; Huckfeldt and Sprague, 1987).…”