QuantDev Brownbag - Standard Errors and Confidence Intervals for Total, Direct, and Indirect Effects in Continuous-Time Mediation Models

Google map

Standard Errors and Confidence Intervals for Total, Direct, and Indirect Effects in Continuous-Time Mediation Models

 

Abstract: 

Mediation modeling using intensive 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 (DT-VAR) approaches are commonly used to estimate indirect effects in intensive longitudinal data (ILD), 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. To address these issues, continuous-time vector autoregressive (CT-VAR) models have been proposed as an alternative. Previous work in the area (e.g., Deboeck & Preacher, 2015; Ryan & Hamaker, 2021) has shown how the total, direct, and indirect effects, for a range of time-intervals values, can be calculated using parameters estimated from CT-VAR models for causal inferential purposes. However, methods for calculating the uncertainty around the total, direct, and indirect effects in continuous-time mediation have yet to be explored. Drawing from the mediation model literature, we present and compare results from using the delta and Monte Carlo methods to calculate standard errors and confidence intervals for the total, direct, and indirect effects in continuous-time mediation for inferential purposes. Options to automate these inferential procedures and facilitate interpretations are available in the cTMed R package.