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Tech Talk: Multi-Level Modeling for Investigators

Multi-Level Modeling for Investigators

Thursday Apr. 4, 2024 from 12:00-1:00pm

Virtual Teams Presentation

Multilevel Modeling is a statistical model that allows specifying and estimating relationships between variables that have been observed at different levels of a hierarchical data structure, including in longitudinal studies where an individual’s responses over time are correlated with each other.  Multilevel models recognize the existence of the hierarchical structure by allowing for residual components at each level in the hierarchy. using multilevel models, investigators could reveal substantive values in group effect, estimate group effects simultaneously with the effects of group-level predictors, and make optimal Inference to a population of groups, from which the groups are treated as a random sample. This talk will present an overview of multilevel or hierarchical data modelling and its applications in medicine, show how to work with data for multilevel data analysis, run the necessary statistical procedures and test, and how to interpret the results from multilevel data analysis.

Meet the Speaker

Zugui Zhang, PhD

Dr. Zugui Zhang is director of biostatistics at iREACH, ChristianaCare and Fellow of American Heart Association. He received an MS in statistics from Arizona State University and his PhD in biostatistics from the University of Iowa.  He joined ChristianaCare in 2007 and has been Director of Biostatistics since 2017.  He holds appointments as Affiliated Professor of Biostatistics

at the University of Delaware and Thomas Jefferson University.  He has worked extensively on large, international, multi-center, randomized clinical trials and observational studies.

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Work supported by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under grant number U54-GM104941 (PI:Hicks) and the State of Delaware.