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© 2011

Modern Issues and Methods in Biostatistics

  • Displays broad coverage and can be used as a textbook or as a reference text

  • Details novel ingredients or developments in methodology, computation algorithms, and applications

  • Includes an introduction to the concepts, discussions of methodology, and examples of applications for a diverse range of topics including Multivariate and Multistage Survival Data Modeling, Meta-analysis, Data Mining and Signal Detection, and Bayesian Methods and Applications

Book

Part of the Statistics for Biology and Health book series (SBH)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Mark Chang
    Pages 1-30
  3. Mark Chang
    Pages 59-86
  4. Mark Chang
    Pages 87-115
  5. Mark Chang
    Pages 117-143
  6. Mark Chang
    Pages 175-204
  7. Mark Chang
    Pages 205-231
  8. Mark Chang
    Pages 233-259
  9. Mark Chang
    Pages 261-289
  10. Back Matter
    Pages 291-307

About this book

Introduction

Classic biostatistics, a branch of statistical science, has as its main focus the applications of statistics in public health, the life sciences, and the pharmaceutical industry. Modern biostatistics, beyond just a simple application of statistics, is a confluence of statistics and knowledge of multiple intertwined fields. The application demands, the advancements in computer technology, and the rapid growth of life science data (e.g., genomics data) have promoted the formation of modern biostatistics. There are at least three characteristics of modern biostatistics: (1) in-depth engagement in the application fields that require penetration of knowledge across several fields, (2) high-level complexity of data because they are longitudinal, incomplete, or latent because they are heterogeneous due to a mixture of data or experiment types, because of high-dimensionality, which may make meaningful reduction impossible, or because of extremely small or large size; and (3) dynamics, the speed of development in methodology and analyses, has to match the fast growth of data with a constantly changing face.

This book is written for researchers, biostatisticians/statisticians, and scientists who are interested in quantitative analyses. The goal is to introduce modern methods in biostatistics and help researchers and students quickly grasp key concepts and methods. Many methods can solve the same problem and many problems can be solved by the same method, which becomes apparent when those topics are discussed in this single volume.

Keywords

Biostatistics

Authors and affiliations

  1. 1.BiometricsAMAG Pharmaceuticals, Inc.LexingtonUSA

About the authors

Mark Chang Ph.D. is the executive director, Biostatistics and Data Management, AMAG Pharmaceuticals, with over 15 years of experience as a statistician in the field of clinical trials. He is a co-founder of the International Society for Biopharmaceutical Statistics, an executive member of ASA Biopharmaceutical Section, and a member of Expert Panel for the Networks of Centres of Excellence, Canada. He is a co-chair of Biotechnology Industry Organization Adaptive Design Working Group.

Bibliographic information

Industry Sectors
Pharma
Health & Hospitals
Biotechnology
Finance, Business & Banking
Consumer Packaged Goods

Reviews

From the book reviews:

“There are 10 chapters, each one covering a major topic in biostatistics in about 30 pages. Each chapter is reasonably self-contained, so a reader does not necessarily need to read all prior chapters to understand a given one. … this is a useful book for upper-level graduate students and Ph.D. statisticians.” (Charles Heckler, Technometrics, Vol. 55 (1), February, 2013)

“This is a first class book. It discusses a wide range of deep issues in statistics, and although focused on topics arising in biostatistics, pharmaceuticals, and clinical trials it would make stimulating and thought-provoking reading for any statistician. … There are exercises at the end of each chapter, and I am certainly tempted to use the book as the basis for a short course for beginning postgraduate students … since it would open their eyes to some challenging and indeed fascinating aspects of modern statistics.” (David J. Hand, International Statistical Review, Vol. 80 (1), 2012)