Chixiang Chen, a Penn State College of Medicine Biostatistics PhD student, has been selected as a winner of the Best Student Paper Award presented by The American Statistical Association’s Section on Nonparametric Statistics. The award will be presented to Chen during this year’s Joint Statistical Meeting taking place July 27 through Aug. 1 in Denver.
Chen, who is co-advised by Ming Wang, MS, PhD and Rongling Wu, PhD at the College of Medicine, is one of three recipients of this year’s award. As an awardee, Chen will give a nonparametric statistics presentation, “A Novel Consistent Information Criterion for Model Selection based on Empirical Likelihood,” during the event.
In Chen’s paper, a robust and broadly applicable information criterion is proposed for model selection. This new method is free of distribution assumptions and has the potential be more flexible in handling complicated data, which is increasingly more available due to advances in data collection techniques and plays a critical role in capturing fundamental principles underlying natural, social, and engineering.“This work fills up the gap in information theoretic criteria. We hope it can provide scientific insights in robust model diagnostics and have broad applications in multiple disciplines,” said Wang, who is an assistant professor in the Division of Biostatistics and Bioinformatics, Department of Public Health Sciences at the College of Medicine.
“In both theories and applications, statistics should be served as one of the fundamental principles, instead of an intermediate tool to the science,” said Chen.
In order to be considered for this ASA award, a student’s paper must describe the following: a research problem, the significance and background of the research, the research design and/or mathematical techniques employed, the results or anticipated results, and the conclusions. In addition, entries must contain statistical theory, methodology, or application classifiable as nonparametric or semiparametric. There were 28 entries this year, and students’ work was rated based on the significance of the research problem, the quality of exposition, and the execution.
“Increasingly we see data emerging from a wide range of fields this is highly complex, and may not follow any form of distribution that traditional statistical models require to make scientific inferences,” said Wu, distinguished professor in the Division of Biostatistics and Bioinformatics. “Chen’s work overcomes this limitation by providing a path-breaking gateway to unravel the mechanistic secrets hidden in data.”
Additionally in 2018, Chen has received the Student Paper Award from the International Chinese Statistical Association at the Applied Statistics Symposium, as well as the Biopharm-Deming Student Scholar Award from ASA Biopharmaceutical Section during the 74th annual Deming Conference on Applied Statistics.
If you're having trouble accessing this content, or would like it in another format, please email the Penn State College of Medicine web department.