Hongyun Liu and Yueqin Hu, Beijing Normal University

This talk will address key challenges and emerging solutions in the measurement and modeling of intensive longitudinal data (ILD). On the measurement side, participant burden poses a major difficulty, potentially reducing compliance. Planned missing data designs may offer relief, but how should they be structured? Measurement timing also presents complications: variables may differ in sampling density, and data may be collected at misaligned times of day. In addition, ILD studies often rely on adapted or abbreviated versions of standard scales, raising questions about how to assess their reliability. 

Modeling ILD is equally challenging. Complex data structures, such as the aforementioned non-synchronous time points, demand thoughtful modeling strategies to preserve dynamic patterns. The relationships among variables are often nonlinear and interactive, requiring flexible models capable of capturing latent interactions and diverse patterns of feedback mechanisms. Estimation presents another layer of complexity, especially in continuous-time models based on differential equations, where issues such as bias and instability remain difficult to overcome.

This presentation will propose practical strategies to address these challenges and highlight the importance of tailored modeling choices and estimation techniques. Illustrative examples and findings from our recent work will be shared to foster further discussion and innovation in ILD research.

about the speaker (primary author)

Hongyun Liu is a professor in the Faculty of Psychology at Beijing Normal University, China. She earned her Ph.D. in Measurement and Psychometrics from BNU in 2003. Dr. Liu has made substantial contributions to her field through impactful research and teaching. Her work encompasses diverse areas, including advanced data analysis methods for intensive longitudinal studies, latent class mixture modeling, and psychometric approaches for process data.

Dr. Liu has authored over 260 research articles, with recent publications appearing in leading journals such as Psychological Methods, Structural Equation Modeling, Psychometrika, and Behavior Research Methods. Her research not only advances theoretical frameworks but also offers practical solutions to real-world challenges in education and psychology.

In addition to her scholarly work, Dr. Liu actively contributes to the professional community. She serves as an Associate Editor of Psychometrika and holds leadership roles in various national and international organizations. She is the Executive Director and Vice Chairman of the Education Statistics and Measurement Society and the Chairman of the Educational Measurement and Evaluation Professional Committee.

Dr. Liu’s achievements have been recognized with numerous awards, including the First Prize for Research Achievements in Education Curriculum (2010), the Special Prize of the 13th and the 17th Beijing Outstanding Achievement Award in Philosophy and Social Sciences (2014 and 2023), the 20th Beijing Distinguished Teaching Award, and the National First-class Online Undergraduate Course Award, among others. Her dedication to advancing psychological and educational research, coupled with her leadership and teaching excellence, has solidified her reputation as a leading figure in her field in China.

about the speaker (second author)

Yueqin Hu is a professor in the Faculty of Psychology at Beijing Normal University, China. She received her Ph.D. in Quantitative Psychology from the University of Virginia in 2013. She then held academic positions at Texas State University and Beijing Normal University, where she has been actively engaged in teaching and research in psychometrics and statistical modeling.

Dr. Hu’s research focuses on developing innovative analytic methods for intensive longitudinal data and applying them in health psychology. Her work integrates approaches such as dynamical systems analysis, machine learning, and multimodal assessment to identify predictive factors and underlying mechanisms related to maintaining health behaviors, coping with stress, and the onset of emotional disorders.

She has published over 50 peer-reviewed articles. Her methodological contributions have appeared in journals such as Psychological Methods, Behavior Research Methods, and Structural Equation Modeling, while her applied research has been featured in Health Psychology and JAMA Psychiatry. Dr. Hu has led eight research projects, including both government-funded grants and industry collaborations, securing over one million USD in total funding.

She currently serves as an Associate Editor for the SSCI journal Mindfulness and sits on the editorial board of the Journal of Psychology. She is an active member of the Psychometric Society and serves on the academic committee of the Behavioral and Health Psychology Division of the Chinese Psychological Society.

Dr. Hu is dedicated to bridging the gap between statistical methodology and psychological applications, with the goal of advancing cutting-edge measurement and analytic techniques in the field of health psychology.