Data-analytische methoden voor het vastleggen van onderlinge afhankelijkheid en synchronisatie in triades

Family functioning influences health and well-being and has therefore become an important research topic. Although many researchers have recognized the importance of studying the family as an integrated whole, existing data-analytical methods show shortcomings when dealing with realistic data designs. The current dissertation aims to develop data-analytical methods to study the functioning of family systems consisting of three members, including a mother, a father and a child. We focus on two features of family functioning: synchronization, which concerns how family members' states or behavior align across time, and interdependence, which focuses on how an outcome measured for all three family members separately is associated with a predictor that is also assessed for all family members. This dissertation includes four projects on synchronization and interdependence. Regarding synchronization, we developed a genuine triadic synchronization measure together with a significance test to detect the existence of triadic synchronization. For interdependence, three objectives were pursued. First, we developed a triadic interdependence modeling framework, which allows researchers to accommodate longitudinal or multi-item design, as these are commonly used in practice. Second, within the longitudinal interdependence model, strategies were proposed and evaluated for identifying which interdependence pattern characterizes a specific family system. Third, different analytical approaches for fitting the multi-item extension of the interdependence model were evaluated, in conditions where measurement invariance only partially holds across family members. For each of these four projects, model formulas, R codes and practical guidance were provided to facilitate the application of these methods in empirical research. Overall, this dissertation improved the alignment between theoretical constructs and empirical analysis in family research and other related fields.