报告时间：2024年9月11日（周三）10:00-11:00

报告地点：中国人民大学明德主楼1016

报告嘉宾：Lijuan Wang

报告主题：Dynamic Structural Equation Modeling with intensive longitudinal data

报告摘要

Dynamic Structural Equation Modeling with intensive longitudinal dataIn this talk, I will discuss several issues related to intraindividual variability modeling. The talk will begin by distinguishing two related concepts: intraindividual change and intraindividual variability. I will then examine various indicators of intraindividual variability, assessing their statistical and psychometric properties. After that, I will introduce and evaluate multiple approaches for modeling intraindividual variability, including a one-step dynamic structural equation modeling approach and several two-step approaches. Simulation results will be presented to compare the performance of the approaches. The talk will conclude with a discussion on the implications of these findings and potential directions for future research.

作者简介

Dr. Lijuan Wang earned her PhD in Quantitative Psychology from the University of Virginia, following her Bachelor's and Master's degrees in Statistics at Renmin University of China. Currently, she is a Professor of Quantitative Psychology at the University of Notre Dame. Her research focuses on methodological issues such as intensive longitudinal data analysis, mediation and moderation analysis, and study designs. She applies these quantitative methods to developmental, clinical, family, and health disparities research. Her work has been published in top-tier journals of quantitative psychology such as Psychological Methods, Structural Equation Modeling, Multivariate Behavioral Research, and Behavior Research Methods, as well as leading non-methodological journals of psychology such as Child Development and Developmental Psychology.  Her research has been funded by the National Institutes of Health, the Institute of Education Sciences, and the John Templeton Foundation. Dr. Wang has been an elected member of the Society of Multivariate  Experimental Psychology since 2016 and served as an associate editor for Psychological Methods from 2016 to 2023.