Workshop 3: Practical Mediation Analysis
Time: 8pm-11pm, July 5, China Time / 8am-11am, July 5, US Eastern Time
Location： Virtual on Zoom (Free Registration)
In social sciences, an input variable often affects an outcome variable via a third variable, or mediator. Mediation analysis is used to answer the question of “how”/ “why” the input variable affects the outcome. This workshop will introduce the principles and methods (e.g., multivariate regression, path analysis, multilevel models, etc.) for mediation analyses. Emphasis will be on data analysis and interpretation. After the workshop, attendants should be able to propose research questions related to mediation analyses, use advanced methods such as bootstrap to test mediation effects, decide which type of model is appropriate for mediation, interpret and display empirical findings, and understand some other important issues of mediation research such as longitudinal designs for assessing mediation and missing data problems.
Laura Lu -- University of Georgia
Dr. Laura Lu is an Associate Professor in the Quantitative Methodologies (QM) program at the University of Georgia (UGA). In general, she has expertise in structural equation modeling (SEM), longitudinal data analysis, hierarchical linear modeling (HLM), and computational statistics such as Bayesian. During her professional career at UGA, her research has focused on developing innovative statistical approaches to address perennial challenges in statistical modeling such as mixture structure, reliabilities, model selection, missing data, outliers, topic modeling, and also promoting statistical models to applied research areas through collaborating, mentoring, and classroom teaching.
Qian Zhang -- Florida State University
Dr. Qian (Jackie) Zhang is an associate professor in the Department of Educational Psychology and Learning Systems at Florida State University. Her research interests focus on causal inferences, longitudinal data analysis, and effect size synthesis using multilevel models and multilevel structural equation models. She is also interested in handling sub-optimal data conditions with missing data, measurement error, and/or confounding variables in statistical analyses. She collaborates with substantive researchers in the areas of early childhood development, sports psychology, and educational research. Her work has been published in prestigious journals such as Psychological Methods, Multivariate Behavioral Research, Structural Equation Modeling, British Journal of Mathematical and Statistical Psychology, and Behavioral Research Methods.
(1) Introduction to Social Network Analysis by Prof. Haiyan Liu from UC-Merced
(2) Longitudinal Data Analysis by Prof. Hongyun Liu from Beijing Normal University
(3) Practical Mediation Analysis by Prof. Laura Lu from University of Georgia and Prof. Qian Zhang from Florida State University
(4) Deep Learning Using R by Prof. Johnny Zhang from University of Notre Dame
(5) From Latent Class Model to Latent Transition Model Using Mplus by Prof. Hawjeng Chiou from National Taiwan Normal University
(6) Bayesian Longitudinal Data Modeling by Prof. Cynthia Tong from University of Virginia
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The meeting is jointly supported by the International Society for Data Science and Analytics, the Society of Multivariate Experimental Psychology, the Fudan Institute for Advanced Study in Social Sciences, the College of Management of National Taiwan Normal University, and the Nanjing University of Posts and Telecommunications.
Selected papers will be published in the following journals: Fudan Journal of the Humanities and Social Sciences, Chinese Political Science Review, and Journal of Behavioral Data Science.
National Taiwan Normal University
University of Texas at Dallas
Beijing Normal University
Nanjing University of Posts and Telecommunications
University of Notre Dame
University of Notre Dame
Mail: P.O.Box 1471, ISDSA, Granger, IN 46530