Modern Empirical Likelihood Methods in Biomedicine and Health

This project focuses on the preparation and writing of a book that will reflect a growing need for rigorous systematic presentations of classical and novel empirical likelihood (EL) approaches and their applications in biomedicine and health.

Principal Investigators: Albert Vexler, PhD, and Jihnhee Yu, PhD

Funding Agency: National Library of Medicine/NIH
Period: 09/2016-09/2018

Abstract: With many examples, and data from biomedical studies, this book will explain newly advanced EL techniques applied to problems encountered in medical and epidemiological studies.

A review of the modern scientific literature reveals the EL methodology is one of key components of highly efficient and robust non- and semi-parametric statistical tools in medical and epidemiological studies. The proposed book will cover basic/traditional EL techniques as well as novel approaches to performing non- and semi-parametric inferences that have been published in the literature, but have not published in a book format, and will also present efficient methods for constructing powerful distribution-free procedures to test composite hypotheses based on data that can be subject to different problems related to, e.g., missing values and limit of detections. The book will provide relevant software code for solving real data problems.

The book material will be attractive and easily understandable to scientists who are new to the research area, including those who may not have a strong statistical background, and will also help attract statisticians interested in learning more about advanced topics, and will also be aimed at biostatisticians who want to form a clear picture of various modern EL methods to extend and improve them.