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โœฆ   LIBER   โœฆ

๐Ÿ“

Modern Issues and Methods in Biostatistics

โœ Scribed by Mark Chang (auth.)


Publisher
Springer-Verlag New York
Year
2011
Tongue
English
Leaves
322
Series
Statistics for Biology and Health
Edition
1
Category
Library

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โœฆ Synopsis


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.

โœฆ Table of Contents


Front Matter....Pages i-xiv
Multiple-Hypothesis Testing Strategy....Pages 1-30
Pharmaceutical Decision and Game Theory....Pages 31-57
Noninferiority Trial Design....Pages 59-86
Adaptive Trial Design....Pages 87-115
Missing Data Imputation and Analysis....Pages 117-143
Multivariate and Multistage Survival Data Modeling....Pages 145-174
Meta-Analysis....Pages 175-204
Data Mining and Signal Detection....Pages 205-231
Monte Carlo Simulation....Pages 233-259
Bayesian Methods and Applications....Pages 261-289
Back Matter....Pages 291-307

โœฆ Subjects


Statistics for Life Sciences, Medicine, Health Sciences; Data Mining and Knowledge Discovery; Mathematics Education; Computational Intelligence


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