Understanding clinical data analysis : learning statistical principles from published clinical research
著者
書誌事項
Understanding clinical data analysis : learning statistical principles from published clinical research
Springer International Pub., c2017
大学図書館所蔵 件 / 全1件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references and index
内容説明・目次
内容説明
This textbook consists of ten chapters, and is a must-read to all medical and health professionals, who already have basic knowledge of how to analyze their clinical data, but still, wonder, after having done so, why procedures were performed the way they were. The book is also a must-read to those who tend to submerge in the flood of novel statistical methodologies, as communicated in current clinical reports, and scientific meetings.
In the past few years, the HOW-SO of current statistical tests has been made much more simple than it was in the past, thanks to the abundance of statistical software programs of an excellent quality. However, the WHY-SO may have been somewhat under-emphasized. For example, why do statistical tests constantly use unfamiliar terms, like probability distributions, hypothesis testing, randomness, normality, scientific rigor, and why are Gaussian curves so hard, and do they make non-mathematicians getting lost all the time? The book will cover the WHY-SOs.
目次
Chapter 1
Randomness
Basis of All Scientific Methods
Chapter 2
Randomized and Observational Research
Writing Protocols, Making Study Data Files
Chapter 3
Randomized Clinical Trials, Designs
Questionable Use of Placebos and Lack of Placebos, Stepped Wedge and Adaptive Designs
Chapter 4
Randomized Clinical Trials, Analysis Sets, Statistical Analysis, Reporting Issues
Principal Features of Statistical Analyses, the Cochrane Risk-of-Bias-Tool
Chapter 5
Discrete Data Analysis, Failure Time Data Analysis
Better Assessments of Biological and Pharmaceutical Agents
Chapter 6
Quantitative Data Analysis
Modeling for False Positive Findings, Using Median Absolute Deviations
Chapter 7
Subgroup Analysis
European Medicines Agency's and American Food Drug Administration's Directives
Chapter 8
Interim Analysis
Alpha Spending Function Approach
Chapter 9
Multiplicity Analysis
Gate Keeping Strategies and Closure Principles
Chapter 10
Medical Statistics, a Discipline at the Interface of Biology and Mathematics
Equating Subjective Feelings with Probabilities, and Providing Quality Criteria for Diagnostic Tests
「Nielsen BookData」 より