LEARNING OBJECTIVES
- Explain what longitudinal/clustered data is and some of its advantages and disadvantages
- Simple approaches to analyzing longitudinal data
- Understand what a mixed model is and when it may be useful
- Example mixed model analysis
PRESENTER(S)
John Rice, PhD
Research Assistant Professor, Adult and Child Consortium for Health Outcomes Research and Delivery Science
John Rice, PhD is currently a research assistant professor in the Department of Biostatistics and Informatics and a biostatistician with the Adult and Child Consortium for Health Outcomes Research and Delivery Science (ACCORDS). He received his PhD in biostatistics in 2015 from the University of Michigan, followed by a postdoc at the University of Rochester. His methodological research is focused on missing and coarsened outcomes, longitudinal/correlated data analysis, and recurrent events. Areas of application include cancer survival, HIV screening, vaccine hesitancy, and other health outcomes.