Document Type : Research Paper

Author

Associate Professor, Psychology Assessment and Measurement, Allameh Tabataba'i University, Tehran, Iran

Abstract

Psychopathology is often an interpersonal issue and interpersonal problems are one of the most common areas of concern expressed by clients. Regardless of the origin of the psychological disorders, most psychological traumas have important interpersonal consequences, and therefore the success of treatment largely depends on a careful analysis of interpersonal relationships in couples' psychotherapy. In this paper, the actor-partner interdependence model (APIM) approach was described and demonstrated by pooled regression for dyadic data analysis for a small sample of couples. This method can be done using conventional statistical software and manual calculations. Therefore, this method of analysis is more suitable for researchers and psychotherapists who want to learn more about their clients, but do not have the sample size available for them to use structural equation modeling or multilevel modeling. This method has several advantages over other approaches used to analyze this type of data. The main advantage is that psychotherapists and researchers can explain the effect of interdependence between members of a couple (for example, spouse, sibling or patient and client) and can examine the effect of the actor and the effect of the partner. As a result, more accurate statistical inferences can be made using this method to help researchers and therapists understand relationships in a couple relationship. The actor-partner interdependence model (APIM) approach helps to incorporate the dependence of a couple's members into the analysis and to consider the dyad as a unit of analysis instead of focusing on the individual, which is a strategic issue in clinical settings. It paves the way for client analysis, and this allows researchers and psychotherapists to improve research related to their field of work in the field of psychology and counseling.

Keywords

تیلور، کاترین، اس. (2013). روایی و رواسازی. ترجمه یونسی، جلیل (1398). انتشارات دانشگاه علامه طباطبائی.
رضائی، هما (1398). تأثیر سبک زندگی بر رضایت زناشویی زوجین. پروژه منتشرنشده.
یونسی، جلیل؛ دلاور، علی؛ اسکندری، فرزاد؛ فلسفی نژاد، محمدرضا؛ فرخی، نورعلی (1393). توانمندی رویکرد بیزی مدل IRT چندسطحی: تحلیل داده­های آزمون ریاضیات تیمز پیشرفته (2008). فصلنامه پژوهش در نظام های آموزشی، پیاپی ۲۴.
Campbell & Stanley (1963).Experimental and Quasi-Experimental Designs for Research. RAND Mcnally College Publishing Company, Chicago.
Cook, T. D., Campbell D. T. (1979). Quasi- Experimentation: Design and analysis issues for field settings. Houghton Mifflin Company. Boston.
Fitzpatrick, J., Gareau, A., Lafontaine, M. F., & Gaudreau, P. (2016). How to use the actor-partner interdependence model (APIM) to estimate different dyadic patterns in Mplus: A step-by-step tutorial. The Quantitative Methods for Psychology12(1), 74-86.
Fowers, B. J., & Olson, D. H. (1986). Predicting marital success with PREPARE: A predictive validity study. Journal of marital and family therapy12(4), 403-413.
Gonzalez, R., & Griffin, D. (2012). Dyadic data analysis. In APA handbook of research methods in psychology, Vol 3: Data analysis and research publication. (pp. 439-450). American Psychological Association.
Kane, M. T. (2006). Validation. In R. L. Brennan (ed.), Educational measurement (4th ed.) (pp. 17-64). Westport, CT: Praeger.
Kashy, D. A., & Snyder, D. K. (1995). Measurement and data analytic issues in couples research. Psychological Assessment7(3), 338.
Kenny, D. A. (1995). The effect of nonindependence on significance testing in dyadic research. Personal relationships2(1), 67-75.
Kenny, D. A., & Judd, C. M. (1996). A general procedure for the estimation of interdependence. Psychological bulletin119(1), 138.
Kenny, D. A., & Ledermann, T. (2010). Detecting, measuring, and testing dyadic patterns in the actor–partner interdependence model. Journal of family psychology24(3), 359.
Kenny, D. A., Kashy, D. A., & Cook, W. L. (2020). Dyadic data analysis. Guilford Publications.
Kiesler, D. J. (1996). Contemporary interpersonal theory and research: Personality, psychopathology, and psychotherapy. New York: Wiley.
Ledermann, T., & Kenny, D. A. (2017). Analyzing dyadic data with multilevel modeling versus structural equation modeling: A tale of two methods. Journal of Family Psychology31(4), 442.
McDonald, J. H. (2009). Handbook of biological statistics (Vol. 2, pp. 6-59). Baltimore, MD: sparky house publishing.
Messick, S. (1989). Validity. In R. L. Linn (Ed.), Educational measurement (3rd ed.) (pp. 13-103). New York: Macmillan.
Reed, R. G., Butler, E. A., & Kenny, D. A. (2013). Dyadic models for the study of health. Social and Personality Psychology Compass7(4), 228-245.
Reed, R. G., Butler, E. A., & Kenny, D. A. (2013). Dyadic models for the study of health. Social and Personality Psychology Compass7(4), 228-245.
Sadler, P., Ethier, N., & Woody, E. (2011). Interpersonal complementarity. Handbook of interpersonal psychology: Theory, research, assessment, and therapeutic interventions, 123-142.
Satterthwaite, F. E. (1946). An approximate distribution of estimates of variance components. Biometrics bulletin2(6), 110-114.
Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasiexperimental designs for generalized causal inference. Boston, MA: Houghton Mifflin.