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.
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