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- Publisher: Chapman and Hall/CRC; 1 edition (August 22, 2018)
- Language: English
- ISBN-10: 1466555033
- ISBN-13: 978-1466555037
The Empirical Likelihood Methods in Biomedicine and Health provides a compendium of nonparametric likelihood statistical techniques in the perspective of health research applications. It includes detailed descriptions of the theoretical underpinnings of recently developed empirical likelihood-based methods. The emphasis throughout is on the application of the methods To the health sciences, with worked examples using real data.
- Provides a systematic overview of novel empirical likelihood techniques.
- Presents a good balance of theory, methods, and applications.
- Features detailed worked examples to illustrate the application of the methods.
- Includes R code for implementation.
The book material is attractive and easily understandable to scientists who are new to the research area and may attract statisticians interested in learning more about advanced nonparametric topics including various modern empirical likelihood methods. The book can be used by graduate students majoring in biostatistics, or in a related field, particularly for those who are interested in nonparametric methods with direct applications in Biomedicine.
Review
"As far as I know, Empirical Likelihood Methods in Biomedicine and Health is the first book that provides a compendium of nonparametric likelihood statistical techniques in the perspective ofhealth research applications. It focuses on the application of the methods to health sciences, with worked examples usingreal data. … The book is well written. It is comprehensive and informative. The book material is attractive and easily understandable to scientists who are new to the research area and may attract statisticians interested in learning more about advanced nonparametric topics, including various modern empirical likelihood methods. The book contains interesting examples and plenty of R codes. These features make the book suitable as a self-learning text for applied statisticians. The book can also be used by graduate students majoring in biostatistics or in a related field, particularly for those who are interested in nonparametric methods with direct applications in biomedicine."
―Gengsheng Qin, Department of Mathematics and Statistics, Georgia State University, Atlanta, Georgia, in Statistics in Medicine, January 2019
About the Author
Albert Vexler obtained his Ph.D. degree in Statistics and Probability Theory from the Hebrew University of Jerusalem in 2003. Dr. Vexler was a postdoctoral research fellow in the Biometry and Mathematical Statistics Branch at the National Institutes of Health, USA. Dr. Vexler is a tenured Full Professor at the SUNY, Department of Biostatistics. Dr. Vexler has authored and co-authored various publications that contribute to both the theoretical and applied aspects of statistics.
Dr. Yu received her Ph.D. degree in Statistics from Texas A & M University in 2003. Her Ph.D. advisor was Thomas E. Wehrly, Ph.D. Currently, Dr. Yu is a tenured associate Professor at the State University of New York at Buffalo, Department of Biostatistics. Also, Dr. Yu is the director of the Population Health Observatory, School of Public Health and Health Professions at the State University of New York at Buffalo.
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