Author	Moyรฉ, Lemuel A. author
Title	Statistical Reasoning in Medicine [electronic resource] : The Intuitive P-Value Primer / by Lemuel A. Moyรฉ
Imprint	New York, NY : Springer New York : Imprint: Springer, 2000
Connect to	http://dx.doi.org/10.1007/978-1-4757-3292-4
Descript	XXI, 281 p. 3 illus. online resource

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 matheยญ matically. Statistical principles in medicine are relatively straightยญ 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 nonmatheยญ maticians. I wrote this book to explain the statistical principles in health care in fairly nonmathematical terms

Prologue: โLet Others Thrash it out!โ A Brief History -- 1: Patients, Patience, and P Values -- 2: Shrine Worship -- 3: Mistaken Identity: P Values in Epidemiology -- 4: Loud Messengers โ P Values and Effect Size -- 5: โYour Searchlightโs Not On!โ Power and P Values -- 6: โSir, you are unethical!โ One-tailed vs. Two-tailed Testing -- 7: P Values and Multiple Endpoints I: Pernicious Abstractions? -- 8: P values and Multiple Endpoints II: Noxious Placebos in the Population -- 9: Neurons vs. Silicon: Regression Analysis and P values -- 10: Bayesian P Values -- 11: Blind Guides for Explorers: P Values, Subgroups and Data Dredging -- Conclusions: Good Servants but Bad Masters

1. Medicine
2. General practice (Medicine)
3. Statistics
4. Medicine & Public Health
5. General Practice / Family Medicine
6. Statistics for Life Sciences
7. Medicine
8. Health Sciences