UW Biostatistics PhD candidate Brian Williamson was one of three Nonparametrics Section student paper award winners who presented at the 2019 Joint Statistical Meetings, July 27–August 1, in Denver.
Williamson’s paper, "A unified approach to nonparametric variable importance assessment,” proposes a model-agnostic measure of variable importance. This allows estimates of importance to be compared across different machine learning algorithms. The work develops a rigorous framework for estimating and performing valid statistical inference on the true importance. While the procedure is broadly applicable, one area in which it has been employed is the study of vaccine efficacy. The proposed approach allows investigators to use state-of-the-art machine learning tools to estimate important variables for predicting when a vaccine is effective. This, in turn, may help to more quickly develop new candidate vaccines for a range of diseases.
Williamson is working with UW Biostatistics faculty members Marco Carone and Noah Simon to prepare the manuscript for submission.
JSM draws more than 6,500 participants and is the largest gathering of statisticians and data scientists held in North America. Session and workshop topics range from statistical applications to methodology and theory to the expanding boundaries of statistics, such as analytics and data science.