Yue Liu, Xi Luo, Hongyun Liu
High participant burden in intensive longitudinal studies (ILS) often reduces data quality and quantity. Planned measurement missing designs (MMD) can alleviate this burden by lowering data collection frequency or duration while maintaining efficiency. This study proposed and evaluated the complete duration MMD (CD-MMD) and the reduced duration MMD (RD-MMD) within the dynamic structural equation modeling framework using Monte Carlo simulations. CD-MMD performed better for long-term cyclical processes, while RD-MMD was more efficient under stationary or short-cycle conditions. Both designs achieved satisfactory power and accuracy when appropriately implemented, offering flexible and practical options for ILS.