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Statistics in medicine

Record Type:	Electronic resources : Monograph/item
Title/Author:	Statistics in medicine/ Robert H. Riffenburgh.
Author:	Riffenburgh, R. H.
Published:	Burlington, MA :Elsevier Academic Press, : c2006.,
Description:	xli, 622 p. :ill. ; : 26 cm.;
Subject:	Biometry - methods. -
Online resource:	An electronic book accessible through the World Wide Web; click for information
ISBN:	9780120887705

Statistics in medicine
Riffenburgh, R. H.

Statistics in medicine[electronic resource] /Robert H. Riffenburgh. - 2nd ed. - Burlington, MA :Elsevier Academic Press,c2006. - xli, 622 p. :ill. ;26 cm.

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

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.

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.

Electronic reproduction.
Amsterdam :
Elsevier Science & Technology,
2007.

Mode of access: World Wide Web.

ISBN: 9780120887705

Source: 102074:102091Elsevier Science & Technologyhttp://www.sciencedirect.comSubjects--Topical Terms:

292300
Biometry
--methods.Index Terms--Genre/Form:

96803
Electronic books.

LC Class. No.: RA409 / .R54 2006eb

Dewey Class. No.: 610.15195

National Library of Medicine Call No.: 2006 E-754

Statistics in medicine
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504 $a Includes bibliographical references (p. 581-584) and indexes.
505 0 $a 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.
520 $a 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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