Presenters: Emily Liu, College of Physical and Mathematical Sciences, Statistics
Authors: Emily Liu, Ben Anderson
Faculty Advisor: Brinley Zabriskie, College of Physical and Mathematical Sciences, Statistics
Institution: Brigham Young University
Clinical trials play a major role in the advancement of effective medical treatments to better address the ever-growing number of health challenges we face today. Adverse health effects, such as death or other serious medical conditions, may arise from these medical interventions, and understanding the extent of their effects is key to this advancement. By combining results from multiple clinical trials, through a statistical meta-regression, we can better identify factors that may be primary causes of these adverse effects. However, adverse events often occur seldomly, making it difficult to draw meaningful conclusions from the clinical trials. In this presentation, we discuss some of these statistical methods and compare their performances at identifying factors that relate to an adverse event.