The Most Comprehensive and Cutting-Edge Guide to Statistical
Applications in Biomedical Research
With the increasing use of biotechnology in medical research and
the sophisticated advances in computing, it has become essential
for practitioners in the biomedical sciences to be fully educated
on the role statistics plays in ensuring the accurate analysis of
research findings. Statistical Advances in the Biomedical Sciences
explores the growing value of statistical knowledge in the
management and comprehension of medical research and, more
specifically, provides an accessible introduction to the
contemporary methodologies used to understand complex problems in
the four major areas of modern-day biomedical science: clinical
trials, epidemiology, survival analysis, and bioinformatics.
Composed of contributions from eminent researchers in the field,
this volume discusses the application of statistical techniques to
various aspects of modern medical research and illustrates how
these methods ultimately prove to be an indispensable part of
proper data collection and analysis. A structural uniformity is
maintained across all chapters, each beginning with an introduction
that discusses general concepts and the biomedical problem under
focus and is followed by specific details on the associated
methods, algorithms, and applications. In addition, each chapter
provides a summary of the main ideas and offers a concluding
remarks section that presents novel ideas, approaches, and
challenges for future research.
Complete with detailed references and insight on the future
directions of biomedical research, Statistical Advances in the
Biomedical Sciences provides vital statistical guidance to
practitioners in the biomedical sciences while also introducing
statisticians to new, multidisciplinary frontiers of application.
This text is an excellent reference for graduate- and Ph D-level
courses in various areas of biostatistics and the medical sciences
and also serves as a valuable tool for medical researchers,
statisticians, public health professionals, and
biostatisticians.
Sobre o autor
Atanu Biswas, Ph D, is Assistant Professor in the Applied
Statistics Unit at the Indian Statistical Institute, Kolkata in
India. Dr. Biswas has authored more than eighty published articles
and also serves as Associate Editor of several journals, including
Sequential Analysis and Communications in Statistics. He is the
recipient of the M.N. Murthy Award for his research in applied
statistics. Sujay Datta, Ph D, is Associate Professor in the
Department of Mathematics and Computer Science at Northern Michigan
University and Visiting Research Scientist in the Department of
Statistics at Texas A&M University, where he is part of a
bioinformatics research program sponsored by the National
Institutes of Health. Dr. Datta’s research interests include
high-throughput data, genomics, and models based on
graphs/networks. Jason P. Fine, Ph D, is Associate Professor in the
Department of Statistics at the University of Wisconsin-Madison and
also serves as Associate Editor of several journals, including
Biometrics, Biostatistics, and the Scandinavian Journal of
Statistics. Mark R. Segal, Ph D, is Professor in the Department of
Epidemiology and Biostatistics at the University of California, San
Francisco. A Fellow of the American Statistical Association, Dr.
Segal has published extensively and currently focuses his research
in the area of bioinformatics.
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