Abstract
In many research settings, understanding the mediation mechanisms of longitudinal (repeated measures) variables is essential for capturing how changes unfold over time. This presentation will highlight Zhang's contributions to advancing longitudinal mediation models, with a particular focus on her work with Bayesian (non)linear random effects mediation models, which can directly estimate both intrinsically linear and nonlinear functions (e.g., linear-linear piecewise functions with unknown changepoints).
Zhang will also discuss the impact of omitting confounders on the model estimation. She will also demonstrate how her methodological research has been motivated by applied studies, sharing her experiences collaborating with interdisciplinary teams on applied research funded by the National Institutes of Health.
Details
Date, Time & Location
Wednesday, Dec. 11, 2024
1:30-2:30 P.M. CST
Carolyn Pope Edwards Hall, Room 312
This presentation is free and open to the public.
Ziwei Zhang
Ph.D. candidate, Department of Educational Psychology, University of Minnesota–Twin Cities
Ziwei Zhang is a Ph.D. candidate in the Quantitative Methods in Education (QME) program in the Department of Educational Psychology at the University of Minnesota-Twin Cities. As a quantitative methodologist, she is committed to developing innovative statistical tools for applied researchers in the social, behavioral, health, and educational sciences.
Zhang values interdisciplinary collaboration and is passionate about using her quantitative expertise to address substantive research questions. Her applied research experiences inspire her methodological work, which addresses complex, real-world data challenges.