Inferences and effect sizes for direct, indirect, and total effects in continuous-time mediation models.

ABSTRACT: Mediation modeling using longitudinal data is an exciting field that captures the interrelations in dynamic changes, such as mediated changes, over time. Even though discrete-time vector autoregressive approaches are commonly used to estimate indirect effects in longitudinal data, they have known limitations due to the dependency of inferential results on the time intervals between successive occasions and the assumption of regular spacing between measurements. Continuous-time vector autoregressive models have been proposed as an alternative to address these issues. Previous work in the area (e.g., Deboeck & Preacher, 2015; Ryan & Hamaker, 2021) has shown how the direct, indirect, and total effects, for a range of time-interval values, can be calculated using parameters estimated from cont

SUBMITTER: Pesigan IJA 

PROVIDER: S-EPMC12494154 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature