Yöntem Karşılaştırma

	Experiences in Close Relationships Scale	Actor-Partner Interdependence Model
Alan	Sosyal psikoloji	Sosyal psikoloji
Aile	Latent structure	Regression model
Köken yılı	1998	2006
Köken	Kelly Brennan, Catherine Clark & Phillip Shaver	David A. Kenny and colleagues
Tür	Self-report two-dimensional scale	Regression model for dyadic interdependence
Seminal kaynak	Brennan, K. A., Clark, C. L., & Shaver, P. R. (1998). Self-report measurement of adult romantic attachment: An integrative overview. In J. A. Simpson & W. S. Rholes (Eds.), Attachment Theory and Close Relationships (pp. 46-76). Guilford Press. ISBN: 9781572302365	Kenny, D. A., Kashy, D. A., & Cook, W. L. (2006). Dyadic Data Analysis. Guilford Press. ISBN: 9781572309869
Diğer adlar	ECR, Adult Attachment Scale, Brennan-Clark-Shaver Attachment Scale	APIM, Dyadic Actor-Partner Model, Interdependence Regression Model
İlişkili	3	3
Özet	The Experiences in Close Relationships (ECR) scale, developed by Brennan, Clark, and Shaver in 1998, is the most widely used self-report measure of adult romantic attachment. The authors factor-analyzed essentially all existing English-language attachment measures and found that they reduced to two orthogonal dimensions: attachment anxiety, the fear of rejection and abandonment and a craving for closeness and reassurance, and attachment avoidance, discomfort with intimacy and dependence and a preference for self-reliance. The resulting 36-item scale, with 18 items per dimension rated on a Likert scale, locates each respondent in a two-dimensional attachment space whose regions correspond to the familiar secure, preoccupied, dismissing, and fearful styles. Highly reliable and extensively validated, the ECR (and its revision, the ECR-R) became the standard instrument for studying how attachment shapes relationship functioning, emotion regulation, and support-seeking across close relationships.	The Actor-Partner Interdependence Model (APIM), formalized by Kenny, Kashy, and Cook, is the standard framework for analyzing dyadic data in which two people's outcomes depend on both their own and their partner's characteristics. For each member of a dyad, the model estimates an actor effect -- the influence of a person's own predictor on their own outcome -- and a partner effect -- the influence of the partner's predictor on the person's outcome -- while explicitly modeling the statistical non-independence of the two members' scores. For example, a person's relationship satisfaction may depend on their own attachment anxiety (actor effect) and on their partner's attachment anxiety (partner effect). By simultaneously estimating these effects and accounting for the correlation between partners, the APIM avoids the bias of treating dyad members as independent and reveals how individuals in relationships shape each other, making it indispensable for research on couples, families, and other interacting pairs.