The Division of Social and Economics Sciences (SES) at NSF has awarded Elena Erosheva, Professor of Statistics and Social Work, and Marina Meila, Professor of Statistics, a grant to support their research on “Improving Panel Decision Making: Understanding Methods for Aggregating Reviewer Opinions”.
The goal of Erosheva and Meila’s research project is to (1) study the overall decision-making processes of peer review panels, specifically for grant funding or conference paper review, that involve numerical scoring of submission quality and (2) to develop new methodologies to model and represent uncertainty and robustness in numerical scoring of submissions and panel consensus. The project will use new methodology with real data on peer review of grant and conference paper submissions..
As for Yen-Chi Chen, Assistant Professor of Statistics, the Division of Mathematical Sciences (DMS) at NSF has awarded him for his research on “Novel Missing Data Approaches for Corrupted Longitudinal Data”.
Chen’s research project aims to (1) observe modern longitudinal databases, which can involve combined multiple datasets and varying measurements that may not be complete and clean, and (2) to develop novel statistical methods to handle incompleteness from missing data perspectives. This is used to deal with data linkage issues on clinical trial data. The methods under development will be applied to the National Alzheimer’s Coordinating Center database and Prostate Cancer Prevention Trial data in the Southwest Oncology Group (SWOG) Cancer Research Network. The methods will also be used to address data collection problems caused by the COVID-19 pandemic and other infectious diseases.