心理科学进展2025，Vol.33Issue(9)：1558-1574,17.DOI:10.3724/SP.J.1042.2025.1558
密集追踪数据的收集方案优化和分析方法改进
Optimization of data collection plans and improvement of data analysis methods for intensive longitudinal studies
摘要
Abstract
Intensive longitudinal studies(ILS)provide a powerful tool for investigating the dynamic changes and interaction mechanisms of psychological states.However,the high measurement intensity in ILS often leads to increased participant burden,reduced compliance,and compromised data quality.Currently,there is a lack of optimized data collection designs and analytical methods that effectively account for the unique characteristics of ILS.This study extends the concept of planned missing design(PMD)to ILS and examines,within the dynamic structural equation modeling(DSEM)framework,the comparison of different PMD strategies and their selection criteria,sample size planning and optimization for studies incorporating PMD,and improved methods for handling missing data.Additionally,we will develop an application to validate the feasibility and applicability of these approaches in real-world psychological research scenarios.关键词
纵向数据分析/结构方程模型/缺失数据分析/计划缺失设计/样本量规划Key words
longitudinal data analysis/structural equation modeling/missing data analysis/planned missing design/sample size planning分类
社会科学引用本文复制引用
刘红云,窦佳宁,徐永泽..密集追踪数据的收集方案优化和分析方法改进[J].心理科学进展,2025,33(9):1558-1574,17.基金项目
国家自然科学基金(32471145)资助. （32471145）
