About this Event
This short course will provide a survey of commonly used simulation models for decision making in public health research, including cohort-/population-based simulation, microsimulation, agent-based, and compartmental models.
Intermediate course:
Attendees after taking this course should be able to recognize key simulation models used for Public Health Decision making, understand the main features of their structure, learn via examples how they have been used in real applications, understand the key components for building these models (including calibration, validation, predictive accuracy, and sensitivity analysis), appreciate the several sources of uncertainty involved in the development and use of these models, and be able to interpret results from and evaluate studies involving use of simulation models.
Faculty:
Stavroula Chrysanthopoulou, PhD. Stavroula A. Chrysanthopoulou, PhD is an Assistant Professor of Biostatistics and Director of the Master’s Program in Biostatistics at Brown University School of Public Health. The focus of her research interests is in the area of microsimulation modeling (MSM). She has developed the MIcrosimulation Lung Cancer (MILC) model, a streamlined MSM of the natural history of lung cancer, and published a package for the implementation of the MILC model in the R open-source statistical software. Her research interests span the fields of complex predictive models applied in medical decision making, calibration and predictive accuracy methods, causal inference, missing data, and high performance computing techniques. Dr Chrysanthopoulou has also extensive teaching experience with various graduate-level courses in Biostatistics, including survival and longitudinal data analysis, generalized linear models, and simulation studies.