Statistics Applied to Clinical Studies

1. Front Matter

   Pages i-xxxv

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2. Hypotheses, Data, Stratification

   • Ton J. Cleophas, Aeilko H. Zwinderman

   Pages 1-14

3. The Analysis of Efficacy Data

   • Ton J. Cleophas, Aeilko H. Zwinderman

   Pages 15-39

4. The Analysis of Safety Data

   • Ton J. Cleophas, Aeilko H. Zwinderman

   Pages 41-60

5. Log Likelihood Ratio Tests for Safety Data Analysis

   • Ton J. Cleophas, Aeilko H. Zwinderman

   Pages 61-68

6. Equivalence Testing

   • Ton J. Cleophas, Aeilko H. Zwinderman

   Pages 69-75

7. Statistical Power and Sample Size

   • Ton J. Cleophas, Aeilko H. Zwinderman

   Pages 77-93

8. Interim Analyses

   • Ton J. Cleophas, Aeilko H. Zwinderman

   Pages 95-101

9. Controlling the Risk of False Positive Clinical Trials

   • Ton J. Cleophas, Aeilko H. Zwinderman

   Pages 103-108

10. Multiple Statistical Inferences

    • Ton J. Cleophas, Aeilko H. Zwinderman

    Pages 109-117

11. The Interpretation of the p-Values

    • Ton J. Cleophas, Aeilko H. Zwinderman

    Pages 119-131

12. Research Data Closer to Expectation than Compatible with Random Sampling

    • Ton J. Cleophas, Aeilko H. Zwinderman

    Pages 133-138

13. Statistical Tables for Testing Data Closer to Expectation than Compatible with Random Sampling

    • Ton J. Cleophas, Aeilko H. Zwinderman

    Pages 139-147

14. Data Dispersion Issues

    • Ton J. Cleophas, Aeilko H. Zwinderman

    Pages 149-159

15. Linear Regression, Basic Approach

    • Ton J. Cleophas, Aeilko H. Zwinderman

    Pages 161-176

16. Linear Regression for Assessing Precision, Confounding, Interaction, Basic Approach

    • Ton J. Cleophas, Aeilko H. Zwinderman

    Pages 177-186

17. Curvilinear Regression

    • Ton J. Cleophas, Aeilko H. Zwinderman

    Pages 187-197

18. Logistic and Cox Regression, Markov Models, Laplace Transformations

    • Ton J. Cleophas, Aeilko H. Zwinderman

    Pages 199-218

19. Regression Modeling for Improved Precision

    • Ton J. Cleophas, Aeilko H. Zwinderman

    Pages 219-225

20. Post-hoc Analyses in Clinical Trials, A Case for Logistic Regression Analysis

    • Ton J. Cleophas, Aeilko H. Zwinderman

    Pages 227-231

Thanks to the omnipresent computer, current statistics can include data files of many thousands of values, and can perform any exploratory analysis in less than seconds. This development, however fascinating, generally does not lead to simple results. We should not forget that clinical studies are, mostly, for confirming prior hypotheses based on sound arguments, and the simplest tests provide the best power and are adequate for such studies. In the past few years the authors of this 5th edition, as teachers and research supervisors in academic and top-clinical facilities, have been able to closely observe the latest developments in the field of clinical data analysis, and they have been able to assess their performance. In this 5th edition the 47 chapters of the previous edition have been maintained and upgraded according to the current state of the art, and 20 novel chapters have been added after strict selection of the most valuable and promising novel methods. The novel methods are explained using practical examples and step-by-step analyses readily accessible for non-mathematicians. All of the novel chapters have been internationally published by the authors in peer-reviewed journal, including the American Journal of Therapeutics, the European Journal of Clinical Investigation, The International journal of Clinical Pharmacology and therapeutics, and other journals, and permission is granted by all of them to use this material in the current book. We should add that the authors are well-qualified in their fields of knowledge. Professor Zwinderman is president-elect of the International Society of Biostatistics, and Professor Cleophas is past-president of the American College of Angiology. From their expertise they should be able to make adequate selections of modern methods for clinical data analysis for the benefit of physicians, students, and investigators. The authors, although from a different discipline, one clinician and one statistician, have been working and publishing together for over 10 years, and their research of statistical methodology can be characterized as a continued effort to demonstrate that statistics is not mathematics but rather a discipline at the interface of biology and mathematics. They firmly believe that any reader can benefit from this clinical approach to statistical data analysis.

• clinical research
• clinical trials
• evidence based medicine
• pharmaceutical medicine
• statistics

From the reviews of the fifth edition:

“‘Statistics Applied to Clinical Studies, 5^th Edition’ clearly explains most anything that might be worth knowing about clinical research statistics. The content is accessible to non-staticians and also has the breadth and depth to interest professional biostaticians.” (Norman M. Goldfarb, Journal of Clinical Research Best Practices, Vol. 9 (2), February, 2013)

• , Department Medicine, Albert Schweitzer Hospital, Dordrecht, Netherlands

  Ton J. Cleophas

• , Dept. Epidemiology and Biostatistics, Academic Medical Center, Amsterdam, Netherlands

  Aeilko H. Zwinderman

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