Statistical Thinking in Clinical Trials
eBook - ePub

Statistical Thinking in Clinical Trials

  1. 270 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Statistical Thinking in Clinical Trials

About this book

Statistical Thinking in Clinical Trials combines a relatively small number of key statistical principles and several instructive clinical trials to gently guide the reader through the statistical thinking needed in clinical trials. Randomization is the cornerstone of clinical trials and randomization-based inference is the cornerstone of this book. Read this book to learn the elegance and simplicity of re-randomization tests as the basis for statistical inference (the analyze as you randomize principle) and see how re-randomization tests can save a trial that required an unplanned, mid-course design change.

Other principles enable the reader to quickly and confidently check calculations without relying on computer programs. The `EZ' principle says that a single sample size formula can be applied to a multitude of statistical tests. The `O minus E except after V' principle provides a simple estimator of the log odds ratio that is ideally suited for stratified analysis with a binary outcome. The same principle can be used to estimate the log hazard ratio and facilitate stratified analysis in a survival setting. Learn these and other simple techniques that will make you an invaluable clinical trial statistician.

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Yes, you can access Statistical Thinking in Clinical Trials by Michael A. Proschan in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Half-Title Page
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Contents
  7. Preface
  8. 1 Evidence and Inference
  9. 2 2 × 2 Tables
  10. 3 Introduction to Clinical Trials
  11. 4 Design of Clinical Trials
  12. 5 Randomization/Allocation
  13. 6 Randomization-Based Inference
  14. 7 Survival Analysis
  15. 8 Sample Size/Power
  16. 9 Monitoring
  17. 10 M&Ms: Multiplicity and Missing Data
  18. 11 Adaptive Methods
  19. References
  20. Index