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Statistics in medicine / Robert H. Riffenburgh.

By: Contributor(s): ©2006Edition: 2nd edDescription: 1 online resource (xli, 622 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780120887705
  • 0120887703
  • 9780080541747
  • 0080541747
  • 9780444501981
  • 0444501983
Subject(s): Genre/Form: Additional physical formats: Print version:: Statistics in medicine.LOC classification:
  • RA409 .R54 2006eb
NLM classification:
  • 2006 E-754
  • WA 950
Online resources:
Contents:
Foreword to the Second Edition, W.M. (Mike) O'Fallon -- Foreword to the First Edition, Vice Adm. Richard A. Nelson -- Databases -- I.A Study Course of Fundamentals -- 1. Data, Notation, and Some Basic Terms -- 2. Distributions -- 3. Summary Statistics -- 4. Confidence Intervals and Probability -- 5. Hypothesis Testing: Concept and Practice -- 6. Statistical Testing, Risks, and Odds in Medical Decisions -- 7. Sample Size Required for a Study -- 8. Statistical Prediction -- 9. Epidemiology -- 10. Reading Medical Articles -- Answers to Chapter Exercises, Part I -- II. A Reference Guide -- 11. Using the Reference Guide -- 12. Planning Medical Studies -- 13. Finding Probabilities of Error -- 14. Confidence Intervals -- 15. Tests on Categorical Data -- 16. Tests on Ranked Data -- 17. Tests on Means of Continuous Data -- 18. Multifactor Tests on Means of Continuous Data -- 19. Tests on Variances of Continuous Data -- 20. Tests on the Distribution Shape of Continuous Data -- 21. Equivalence Testing -- 22. Sample Size Required for a Study -- 23. Modeling and Clinical Decisions -- 24. Regression and Correlation Methods -- 25. Survival and Time-Series Analysis -- 26. Methods You Might Meet, But Not Every Day -- Chapter Summaries -- References and Data Sources -- Tables of Probability Distributions -- Symbol Index -- Subject Index.
Action note:
  • digitized 2010 HathiTrust Digital Library committed to preserve
Summary: Medicine deals with treatments that work often but not always, so treatment success must be based on probability. Statistical methods lift medical research from the anecdotal to measured levels of probability. This book presents the common statistical methods used in 90% of medical research, along with the underlying basics, in two parts: a textbook section for use by students in health care training programs, e.g., medical schools or residency training, and a reference section for use by practicing clinicians in reading medical literature and performing their own research. The book does not require a significant level of mathematical knowledge and couches the methods in multiple examples drawn from clinical medicine, giving it applicable context. * Easy-to-follow format incorporates medical examples, step-by-step methods, and check yourself exercises * Two-part design features course material and a professional reference section * Chapter summaries provide a review of formulas, method algorithms, and check lists * Companion site links to statistical databases that can be downloaded and used to perform the exercises from the book and practice statistical methods New in this Edition: * New chapters on: multifactor tests on means of continuous data, equivalence testing, and advanced methods * New topics include: trial randomization, treatment ethics in medical research, imputation of missing data, and making evidence-based medical decisions * Updated database coverage and additional exercises * Expanded coverage of numbers needed to treat and to benefit, and regression analysis including stepwise regression and Cox regression Thorough discussion on required sample size.
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Medicine deals with treatments that work often but not always, so treatment success must be based on probability. Statistical methods lift medical research from the anecdotal to measured levels of probability. This book presents the common statistical methods used in 90% of medical research, along with the underlying basics, in two parts: a textbook section for use by students in health care training programs, e.g., medical schools or residency training, and a reference section for use by practicing clinicians in reading medical literature and performing their own research. The book does not require a significant level of mathematical knowledge and couches the methods in multiple examples drawn from clinical medicine, giving it applicable context. * Easy-to-follow format incorporates medical examples, step-by-step methods, and check yourself exercises * Two-part design features course material and a professional reference section * Chapter summaries provide a review of formulas, method algorithms, and check lists * Companion site links to statistical databases that can be downloaded and used to perform the exercises from the book and practice statistical methods New in this Edition: * New chapters on: multifactor tests on means of continuous data, equivalence testing, and advanced methods * New topics include: trial randomization, treatment ethics in medical research, imputation of missing data, and making evidence-based medical decisions * Updated database coverage and additional exercises * Expanded coverage of numbers needed to treat and to benefit, and regression analysis including stepwise regression and Cox regression Thorough discussion on required sample size.

Foreword to the Second Edition, W.M. (Mike) O'Fallon -- Foreword to the First Edition, Vice Adm. Richard A. Nelson -- Databases -- I.A Study Course of Fundamentals -- 1. Data, Notation, and Some Basic Terms -- 2. Distributions -- 3. Summary Statistics -- 4. Confidence Intervals and Probability -- 5. Hypothesis Testing: Concept and Practice -- 6. Statistical Testing, Risks, and Odds in Medical Decisions -- 7. Sample Size Required for a Study -- 8. Statistical Prediction -- 9. Epidemiology -- 10. Reading Medical Articles -- Answers to Chapter Exercises, Part I -- II. A Reference Guide -- 11. Using the Reference Guide -- 12. Planning Medical Studies -- 13. Finding Probabilities of Error -- 14. Confidence Intervals -- 15. Tests on Categorical Data -- 16. Tests on Ranked Data -- 17. Tests on Means of Continuous Data -- 18. Multifactor Tests on Means of Continuous Data -- 19. Tests on Variances of Continuous Data -- 20. Tests on the Distribution Shape of Continuous Data -- 21. Equivalence Testing -- 22. Sample Size Required for a Study -- 23. Modeling and Clinical Decisions -- 24. Regression and Correlation Methods -- 25. Survival and Time-Series Analysis -- 26. Methods You Might Meet, But Not Every Day -- Chapter Summaries -- References and Data Sources -- Tables of Probability Distributions -- Symbol Index -- Subject Index.

Includes bibliographical references (pages 581-584) and indexes.

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