Researchers have developed DTVEM-RE, a novel extension to the Differential Time-Varying Effect Model (DTVEM) that allows for person-specific lag coefficients in intensive longitudinal data. This new model addresses the limitation of the original DTVEM, which assumed a uniform lag structure across all individuals. DTVEM-RE offers two versions for analysis: a discrete-time hierarchical Bayesian VAR in Stan and a continuous-time per-person Ornstein-Uhlenbeck model in ctsem. Simulations and application to an EMA dataset demonstrate DTVEM-RE's ability to accurately capture individual differences in lag effects and improve predictive accuracy. AI
IMPACT Enables more personalized analysis of time-series data, potentially improving clinical research and behavioral science insights.
RANK_REASON The cluster contains a research paper detailing a new statistical model extension.
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