personalized models; moderation analysis
Definition
Personalized models; moderation analysis refers to statistical methods that examine how context factors influence the dynamic relationships within an individual's psychological network over time. These approaches use fixed moderated time series models—vector autoregressive (VAR) based models in which all parameters, including lagged connections and innovation structure, can be moderated by external variables such as social interaction or stress levels. Rather than simply identifying when network structures change, moderation analysis in idiographic networks investigates why changes occur by testing whether specific contextual or intervention-related factors causally influence the connections between an individual's symptoms, emotions, or behaviors. This approach directly estimates changes in mean levels of variables within the network and offers clinically relevant insights for personalized treatment, such as identifying which interventions or life events might alter an individual's psychological system.
Sources: Bringmann et al. (2024)
Related Terms
Applications
Personalized Models; Moderation Analysis and Intensive Longitudinal Data
Personalized models using moderation analysis are applied to intensive longitudinal data collected to study how psychological variables change over time. The moderated time series approach enables researchers and clinicians to reveal not only when network changes occur but why they occur based on contextual moderators.
Sources: Bringmann et al. (2024)
Personalized Models; Moderation Analysis and Clinical Interventions
Moderation analysis in idiographic networks allows clinicians to test how specific interventions or life events causally impact the dynamic relationships between an individual's symptoms, thereby providing guidance on which factors can improve clinical outcomes.
Sources: Bringmann et al. (2024)
