Statistics and Actuarial Science PhD candidate Yilin Chen is one of two students to claim the 2020 Huawei Prize for Best Research paper by a Mathematics Graduate Student. The $4,000 prize affirms the value of Chen’s efforts to establish a framework for analyzing nonprobability survey samples in her winning paper: Doubly Robust Interference with Nonprobability Survey Samples.
Historically, probability survey samples have served as primary data sources for official statistics as well as social and health science researchers. In the past two decades, non-probability survey samples have risen to become a convenient yet biased and unrepresentative alternative. “A sound statistical framework for valid statistical analysis with nonprobability samples is not available in the existing literature,” according to Professors Pengfei Li and Changbao Wu, Chen’s PhD supervisors and the co-authors of the paper. In the paper, Chen proposes a new statistical framework that overcomes the biased feature of nonprobability samples through using auxiliary information from probability survey samples.
“The results presented in Chen’s paper have an immediate impact on this timely topic in the big data era,” Li and Wu believe. Professor J.N.K. Rao, the world’s leading authority in survey sampling and a recipient of an honorary Doctor of Mathematics from the University of Waterloo, cited Chen’s research results twice in a recent speech and praised her contributions to the field. The paper was accepted for publication in the Journal of the American Statistical Association (JASA), one of the most prestigious premier journals in statistics.