Time lags and time interactions in mixed effects models impacted longitudinal mediation effect estimates

Objectives: Longitudinal mediation effects can be estimated with mixed effects models. Mixed effects models are versatile, as they accommodate the estimation of contemporaneous, lagged, time-independent, and time-dependent effects. However, the inclusion of time lags and time interactions in mixed effects models for longitudinal mediation analysis has received little attention. This article demonstrates how time lags and time interactions in mixed effects models affect the interpretation of longitudinal mediation effect estimates. Study Design and Setting: We used a data example from the Amsterdam Growth and Health Longitudinal Study to illustrate how the inclusion of time lags and time interactions in mixed effects models may affect the size and interpretation of longitudinal mediation effect estimates. Results: The chosen time lags between the determinant, mediator, and outcome influenced the size and interpretation of the mediation effect estimates. Furthermore, time interactions can be used to model linear or nonlinear development of the mediation effects over time. Conclusion: The inclusion of time lags and time interactions should be considered when estimating longitudinal mediation effects based on mixed effects models, as this enables the estimation of lagged and time-dependent effects.