如何设计面板研究以探究双变量动态关系

Designing effective longitudinal panel studies to capture bivariate dynamics requires making informed decisions about how many measurements to collect and when to collect them. This study examines how design choices, concretely sample size, number of repeated measures, and various aspects of the temporal sampling schedule, influence the recovery of bivariate dynamic parameters in panel data analyzed using a Continuous-Time Random Intercept Cross-Lagged Panel Model (CT-RI-CLPM). Through a Monte Carlo simulation, we tested a range of generating population parameters. We proposed a novel approach