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Statistical Reasoning in Medicine

The Intuitive P-Value Primer

  • Book
  • © 2000

Overview

Authors:
  1. Lemuel A. Moyé

    1. School of Public Health, University of Texas, Houston, USA

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Table of contents (13 chapters)

  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

    • Lemuel A. Moyé
    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

    • Lemuel A. Moyé
    Pages 173-210

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

    • Lemuel A. Moyé
    Pages 211-233

  12. Bayesian P Values

    • Lemuel A. Moyé
    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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Keywords

About this book

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.

Authors and Affiliations

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

    Lemuel A. Moyé

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