Statistical Reasoning in Medicine

1. Front Matter

   Pages i-xxi

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2. Prologue: “Let Others Thrash it out!” A Brief History

   • Lemuel A. Moyé

   Pages 1-19

3. Patients, Patience, and P Values

   • Lemuel A. Moyé

   Pages 20-47

4. Shrine Worship

   • Lemuel A. Moyé

   Pages 48-69

5. Mistaken Identity: P Values in Epidemiology

   • Lemuel A. Moyé

   Pages 70-96

6. Loud Messengers — P Values and Effect Size

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   Pages 97-119

7. “Your Searchlight’s Not On!” Power and P Values

   • Lemuel A. Moyé

   Pages 120-138

8. “Sir, you are unethical!” One-tailed vs. Two-tailed Testing

   • Lemuel A. Moyé

   Pages 139-158

9. P Values and Multiple Endpoints I: Pernicious Abstractions?

   • Lemuel A. Moyé

   Pages 159-172

10. P values and Multiple Endpoints II: Noxious Placebos in the Population

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    Pages 173-210

11. Neurons vs. Silicon: Regression Analysis and P values

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    Pages 211-233

12. Bayesian P Values

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    Pages 234-250

13. Blind Guides for Explorers: P Values, Subgroups and Data Dredging

    • Lemuel A. Moyé

    Pages 251-266

14. Conclusions: Good Servants but Bad Masters

    • Lemuel A. Moyé

    Pages 267-273

15. Back Matter

    Pages 274-281

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Long before I had any inkling that I would write a book, I learned that apreface is the author's attempt to engage the reader in a leisurely conversation before serious joint work begins. In that spirit, I ask you to spend a moment with me now. Although an important focus of my training and daily work is in mathematics and statistics, I have found that many health care workers in general, and physicians in particular, have difficulty understanding research issues when they are presented mathe­ matically. Statistical principles in medicine are relatively straight­ forward and can be' easily absorbed without a heavy mathematical preamble. I have come to believe that the underlying research principles are not difficult; what is difficult is the mathematics in which the principles are embedded. The mathematical medium often distorts and confuses the research message for nonmathe­ maticians. I wrote this book to explain the statistical principles in health care in fairly nonmathematical terms.

• Effect size
• clinical research
• epidemiology
• medicine
• neurons
• patients
• poison
• population
• regression analysis
• research

• School of Public Health, University of Texas, Houston, USA

  Lemuel A. Moyé

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