Modern Statistical Methods for Health Research
(Din) Ding-Geng Chen
Venduto da AHA-BUCH GmbH, Einbeck, Germania
Venditore AbeBooks dal 14 agosto 2006
Nuovi - Rilegato
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Aggiungere al carrelloVenduto da AHA-BUCH GmbH, Einbeck, Germania
Venditore AbeBooks dal 14 agosto 2006
Condizione: Nuovo
Quantità: 1 disponibili
Aggiungere al carrelloDruck auf Anfrage Neuware - Printed after ordering - This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include:Health data analysis and applications to EHR dataClinical trials, FDR, and applications in health scienceBig network analytics and its applications in GWASSurvival analysis and functional data analysisGraphical modelling in genomic studiesThe book will be valuable to data scientists and statisticians who are working in biomedicine and health, other practitioners in the health sciences, and graduate students and researchers in biostatistics and health.
Codice articolo 9783030724368
This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include:
Health data analysis and applications to EHR data
Clinical trials, FDR, and applications in health science
Big network analytics and its applications in GWAS
Survival analysis and functional data analysis
Graphical modelling in genomic studies
The book will be valuable to data scientists and statisticians who are working in biomedicine and health, other practitioners in the health sciences, and graduate students and researchers in biostatistics and health.
Professor Yichuan Zhao is a professor of statistics at Georgia State University in Atlanta. He has a joint appointment as associate member of the Neuroscience Institute, and he is also an affiliated faculty member of the School of Public Health at Georgia State University. His current research interest focuses on survival analysis, empirical likelihood methods, nonparametric statistics, analysis of ROC curves, bioinformatics, Monte Carlo methods, and statistical modelling of fuzzy systems. He has published 100 research articles in statistics and biostatistics, has co-edited four books on statistics, biostatistics and data science, and has been invited to deliver more than 200 research talks nationally and internationally. Dr. Zhao has organized the Workshop Series on Biostatistics and Bioinformatics since its initiation in 2012. He also organized the 25th ICSA Applied Statistics Symposium in Atlanta as a chair of the organizing committee to great success. He is currently serving as associate editor, or on the editorial board, for several statistical journals. Dr. Zhao is a Fellow of the American Statistical Association, an elected member of the International Statistical Institute, and serves on the Board of Directors, ICSA.
Professor (Din) Ding-Geng Chen is a fellow of the American Statistical Association. He is an honorary professor at the School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, South Africa and an extraordinary professor at the Department of Statistics, University of Pretoria, South Africa. Professor Chen has written more than 200 refereed publications and co-authored/co-edited 33 books on clinical trial methodology, meta-analysis, causal inference and public health statistics. This work is partially supported by the National Research Foundation of South Africa (Grant Number 127727) and the South African National Research Foundation (NRF) and South African Medical Research Council (SAMRC) (South African DST-NRF-SAMRC SARChI Research Chair in Biostatistics, Grant Number 114613).
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