Abstract
The authors describe an approach to analyzing dyadic data that can be utilized with the smaller samples often available to researcher–practitioners working with couples in counseling. Specifically, the authors describe how to use the actor–partner interdependence model (APIM), a common dyadic data analysis tool, using a pooled regression approach that is appropriate for smaller sample sizes. An example is provided using data collected from a study of the role of expectancies in couple counseling outcomes. Additional data from the example study are provided in Appendix A for interested readers who want to practice the techniques they describe.
Notes
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or Publication of this article.
The authors received no financial support for the research, authorship, and/or Publication of this article.
Additional information
Notes on contributors
Rachel B. Tambling
Rachel B. Tambling, PhD, LMFT, is an assistant professor in the Department of Human Development and Family Studies at the University of Connecticut. Her research interests included the processes and outcomes of couple and family therapy. She is particularly interested in factors that contribute to successful engagement and treatment persistence in counseling.
Sara K. Johnson
Sara K. Johnson, MA, CFLE, is a doctoral candidate in the Department of Human Development and Family Studies at the University of Connecticut. She has substantive research interests in programs and activities that promote positive development among adolescents and emerging adults, and her methodological interests focus on the use of advanced data analysis techniques to evaluate programs and interventions.
Lee N. Johnson
Lee N. Johnson, PhD, LMFT, is associate professor in the department of Child and Family Development and MFT Program Director at the University of Georgia. His research interests include aspects of therapy processes and outcomes.