Faculty
Social Science
Supervisor Name
Dr. Samantha Joel
Keywords
Actor-partner interdependence model, couples, dyadic data
Description
In relationship science, researchers focus on studying interpersonal effects among dyads or romantic couples, as well as common relationship outcomes like quality, satisfaction, and commitment. To do so, a statistical analysis known as the actor-partner interdependence model is used to examine dyadic effects, such as how an individual’s variable may affect the other member of the dyad. Within this model, there are actor and partner effects. An actor effect can be defined as the effect of partner 1’s independent variable on their own dependent variable. A partner effect can be defined as the effect of partner 1’s independent variable on partner 2’s dependent variable. As partner effects are assumed to be highly important within dyads, this recent research poses a potentially large problem for all relationship scientists. My research seeks to further assess whether partner effects are significant contributors to dyadic data analysis or whether relationship researchers may be overemphasizing their importance.
Acknowledgements
A special thank you to Dr. Samantha Joel and Dr. James Kim for allowing me to be part of this project. I am appreciative of all the help and learning experiences I have received from them both.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 License.
Document Type
Poster
Included in
Partner Effects May Be Weaker Than We Thought. What Does That Mean for Relationship Science?
In relationship science, researchers focus on studying interpersonal effects among dyads or romantic couples, as well as common relationship outcomes like quality, satisfaction, and commitment. To do so, a statistical analysis known as the actor-partner interdependence model is used to examine dyadic effects, such as how an individual’s variable may affect the other member of the dyad. Within this model, there are actor and partner effects. An actor effect can be defined as the effect of partner 1’s independent variable on their own dependent variable. A partner effect can be defined as the effect of partner 1’s independent variable on partner 2’s dependent variable. As partner effects are assumed to be highly important within dyads, this recent research poses a potentially large problem for all relationship scientists. My research seeks to further assess whether partner effects are significant contributors to dyadic data analysis or whether relationship researchers may be overemphasizing their importance.