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# Statistics in Medicine. Edition No. 3

• ID: 2089002
• August 2012
• 738 Pages
• Elsevier Science and Technology
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Statistics in Medicine, Third Edition makes medical statistics easy to understand by students, practicing physicians, and researchers. The book begins with databases from clinical medicine and uses such data to give multiple worked-out illustrations of every method. The text opens with how to plan studies from conception to publication and what to do with your data, and follows with step-by-step instructions for biostatistical methods from the simplest levels (averages, bar charts) progressively to the more sophisticated methods now being seen in medical articles (multiple regression, noninferiority testing). Examples are given from almost every medical specialty and from dentistry, nursing, pharmacy, and health care management. A preliminary guide is given to tailor sections of the text to various lengths of biostatistical courses.

- User-friendly format includes medical examples, step-by-step methods, and check-yourself exercises appealing to readers with little or no statistical background, across medical and biomedical disciplines
- Facilitates stand-alone methods rather than a required sequence of reading and references to prior text
- Covers trial randomization, treatment

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1. Planning Studies: From Design to Publication

2. Planning Analysis: What Do I Do with my Data?

3. Probability and Relative Frequency Distributions

4. Distributions

5. Descriptive Statistics

6. Finding Probabilities of Error

7. Confidence Intervals

8. Hypothesis Testing: Concept and Practice

9. Tests on Categorical Data

10. Risks, Odds, and ROC Curves

11. Tests on Ranked Data

12. Tests on Means of Continuous Data

13. Multi-Factor ANOVA and ANCOVA

14. Tests on Variability and Distributions

15. Managing Results of Analysis

16. Equivalence Testing

17. Bayesian Statistics

18. Sample Size Estimation and Meta-Analysis

19. Modeling Concepts and Methods

20. Clinical Decisions Based on Models

21. Regression and Correlation

22. Multiple and Curvilinear Regression

23. Survival, Logistic Regression, and Cox Regression

24. Sequential Analysis and Time Series

25. Epidemiology

26. Measuring Association and Agreement

27. Questionnaires and Surveys

28. Methods You Might Meet, But Not Every Day

References and Data Sources

Tables of Probability Distributions

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Riffenburgh, Robert H.
Robert H. Riffenburgh, PhD, advises on experimental design, statistical analysis, and scientific integrity of the approximately 400 concurrent studies at the Naval Medical Center San Diego. A fellow of the American Statistical Association and Royal Statistical Society, he is former Professor and Head, Statistics Department, University of Connecticut, and has been faculty at Virginia Tech., University of Hawaii, University of Maryland, University of California San Diego, San Diego State University, and University of Leiden (The Netherlands). He has been president of his own consulting firm and performed and directed operations research for the U.S. government and for NATO. He has consulted on biostatistics throughout his career, has received numerous awards, and has published more than 140 professional articles.

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