Investigating moderation effects at the within-person level using intensive longitudinal data: A two-level dynamic structural equation modelling approach in Mplus

Recent technological advances have provided new opportunities for the collection of intensive longitudinal data. Using methods such as dynamic structural equation modelling, these data can provide new insights into moment-to-moment dynamics of psychological and behavioural processes. In intensive longitudinal data (t > 20), researchers often have theories that imply that factors that change from moment to moment within individuals act as moderators. For instance, a person’s level of sleep deprivation may affect how much an external stressor affects mood. Here, we describe how researchers can implement, test and interpret dynamically changing within-person moderation effects using two-level dynamic structural equation modelling as implemented in the structural equation modelling software Mplus. We illustrate the analysis of within-person moderation effects using an empirical example investigating whether changes in spending time online using social media affect the moment-to-moment effect of loneliness on depressive symptoms. We provide annotated Mplus code, enabling researchers to better isolate, estimate and interpret the complexities of within-person interaction effects.