Statistics in Medicine.
Title:
Statistics in Medicine.
Author:
Riffenburgh, Robert H.
ISBN:
9780080541747
Personal Author:
Edition:
2nd ed.
Physical Description:
1 online resource (665 pages)
Contents:
Front Cover -- Statistics in Medicine, Second Edition -- Copyright Page -- Contents -- Foreword to the Second Edition -- Foreword to the First Edition -- Acknowledgments -- Databases -- Part I: A Study Course of Fundamentals -- Chapter 1. Data, Notation, and Some Basic Terms -- 1.1. About This Book -- 1.2. Stages of Scientific Knowledge -- 1.3. Quantification and Accuracy -- 1.4. Data Types -- 1.5. Notation (or Symbols) -- 1.6. Samples, Populations, and Randomness -- Chapter 2. Distribution -- 2.1. Frequency Distributions -- 2.2. Relative Frequencies and Probabilities -- 2.3. Characteristics of a Distribution -- 2.4. What Is Typical? -- 2.5. The Spread About the Typical -- 2.6. The Shape -- 2.7. Statistical Inference -- 2.8. Distributions Commonly Used in Statistics -- 2.9. Standard Error of the Mean -- 2.10. Joint Distributions of Two Variables -- Chapter 3. Summary Statistics -- 3.1. Numerical Summaries, One Variable -- 3.2. Numerical Summaries, Two Variables -- 3.3. Pictorial Summaries, One Variable -- 3.4. Pictorial Summaries, Two Variables -- 3.5. Good Graphing Practices -- Chapter 4. Confidence Intervals and Probability -- 4.1. Overview -- 4.2. The Normal Distribution -- 4.3. Confidence Interval on an Observation from an Individual Patient -- 4.4. Concept of a Confidence Interval on a Descriptive Statistic -- 4.5. Confidence Interval on a Mean, Known Standard Deviation -- 4.6. The t Distribution -- 4.7. Confidence Interval on a Mean, Estimated Standard Deviation -- 4.8. The Chi-square Distribution -- 4.9. Confidence Interval on a Variance or Standard Deviation -- 4.10. Other Frequently Seen Confidence Intevals and Probabilities -- Chapter 5. Hypothesis Testing: Concept and Practice -- 5.1. Hypotheses in Inference -- 5.2. Error Probabilities -- 5.3. Two Policies of Testing -- 5.4. Organizing Data for Inference.
5.5. Evolving a Way to Answer Your Data Question -- Chapter 6. Statistical Testing, Risks, and Odds in Medical Decisions -- 6.1. Overview -- 6.2. Categorical Data: Basics -- 6.3. Categorical Data: Tests on 2 x 2 Tables -- 6.4. Categorical Data: Risks and Odds -- 6.5. Rank Data: Basics -- 6.6. Rank Data: The Rank-Sum Test to Compare Two Samples -- 6.7. Continuous Data: Basics of Means -- 6.8. Continuous Data: Normal ( z ) and t Tests to Compare Two Sample Means -- 6.9. Other Tests of Hypotheses -- Chapter 7. Sample Size Required for a Study -- 7.1. Overview -- 7.2. Is the Estimate of Minimum Required Sample Size Adequate? -- 7.3. Sample Size in Means Testing -- 7.4. Minimum Sample Size Estimation for a Test of Two Means -- 7.5. Other Situations in Which Minimum Sample Size Estimation Is Used -- Chapter 8. Statistical Prediction -- 8.1. What Is a "Model"? -- 8.2. Straight-Line Models -- 8.3. What Is "Regression" (and Its Relation to Correlation)? -- 8.4. Assessing and Predicting Relationships by Regression -- 8.5. Other Questions That Can Be Answered by Regression -- 8.6. Clinical Decisions and Outcomes Analysis -- Chapter 9. Epidemiology -- 9.1. The Nature of Epidemiology -- 9.2. Some Key Stages in the History of Epidemiology -- 9.3. Concept of Disease Transmission -- 9.4. Descriptive Measures -- 9.5. Types of Epidemiologic Studies -- 9.6. An Informal Approach to Public Health Problems -- 9.7. Analysis of Survival and Causal Factors -- Chapter 10. Reading Medical Articles -- 10.1. Assessing Medical Information from an Article -- 10.2. Keep in Mind How a Study Is Constructed -- 10.3. Study Types -- 10.4. Sampling Bias -- 10.5. Statistical Aspects Where Articles May Fall Short -- 10.6. Evolving Terms: Meta-analysis, Multivariable Analysis, and Others -- 10.7. Selection of Statistical Tests to Use in a Study -- Answers to Chapter Exercise, Part I.
Part II: A Reference Guide -- Chapter 11. Using the Reference Guide -- 11.1. How to Use This Guide -- 11.2. Basic Concepts Needed to Use This Guide -- Chapter 12. Planning Medical Studies -- 12.1. The Science Underlying Clinical Decision Making -- 12.2. The Objective of Statistics -- 12.3. Concepts in Study Design -- 12.4. Sampling Schemes -- 12.5. How to Randomize a Sample -- 12.6. How to Plan and Conduct a Study -- 12.7. Mechanisms to Improve Your Study Plan -- 12.8. How to Manage Data -- 12.9. Setting Up a Test Within a Study -- 12.10. Choosing the Right Test -- 12.11. Statistical Ethics in Medical Studies -- Chapter 13. Finding Probabilities or Error -- 13.1. Introduction -- 13.2. The Normal Distribution -- 13.3. The t Distribution -- 13.4. The Chi-square Distribution -- 13.5. The F Distribution -- 13.6. The Binomial Distribution -- 13.7. The Poisson Distribution -- Chapter 14. Confidence Intervals -- 14.1. Overview -- 14.2. Confidence Interval on a Mean, Known Standard Deviation -- 14.3. Confidence Interval on a Mean, Estimated Standard Deviation -- 14.4. Confidence Interval on a Variance or Standard Deviation -- 14.5. Confidence Interval on a Proportion -- 14.6. Confidence Interval on a Correlation Coefficient -- Chapter 15. Tests on Categorical Data -- 15.1. Categorical Data Summary -- 15.2. 2 x 2 Tables: Contingency Tests -- 15.3. r x c Tables: Contingency Tests -- 15.4. Risks and Odds in Medical Decisions -- 15.5. 2 x 2 Tables: Tests of Association -- 15.6. Tests of Proportion -- 15.7. Tests of a Small Proportion (Close to Zero) -- 15.8. Matched Pair Test (McNemar's Test) -- Chapter 16. Test on Ranked Data -- 16.1. Basics of Ranks -- 16.2. Single or Paired Small Samples: The Signed-Rank Test -- 16.3. Two Small Samples: The Rank-Sum Test -- 16.4 Three or More Independent Samples: The Kruskal-Wallis Test.
16.5. Three or More Matched Samples: The Friedman Test -- 16.6. Single Large Samples: Normal Approximation to Signed-Rank Test -- 16.7. Two Large Samples: Normal Approximation to Rank-Sum Test -- Chapter 17. Tests on Means of Continuous Data -- 17.1. Summary of Means Testing -- 17.2. Normal ( z ) and t Tests for Single or Paired Means -- 17.3. Post Hoc Confidence and Power -- 17.4. Normal ( z ) and t Tests for Two Means -- 17.5. Three or More Means: One-Way Analysis of Variance -- Chapter 18. Multifactor Tests on Means of Continuous Data -- 18.1. Concepts of Elperimental Design -- 18.2. Two-Factor Analysis of Variance -- 18.3. Repeated-Measures Analysis of Variance -- 18.4. Analysis of Covariance -- 18.5. Three- and Higher-Factor Analysis of Variance -- 18.6. More Specialized Designs and Techniques -- Chapter 19. Tests on Variances of Continuous Data -- 19.1. Basics of Tests on Variability -- 19.2. Single Samples -- 19.3. Two Samples -- 19.4. Three or More Samples -- Chapter 20. Tests on the Distribution Shape of Continuous Data -- 20.1. Objectives of Tests on Distributions -- 20.2. Test of Normality of a Distribution -- 20.3. Test of Equality of Two Distributions -- Chapter 21. Equivalence Testing -- 21.1. Concepts and Terms -- 21.2. Basics Underlying Equivalence Testing -- 21.3. Methods for Nonsuperiority Testing -- 21.4. Methods for Equivalence Testing -- Chapter 22. Sample Size Required in a Study -- 22.1. Overview -- 22.2. Relation of Sample Size Calculated to Sample Size Needed -- 22.3. Sample Size for Tests on Means -- 22.4. Sample Size for Confidence Intervals on Means -- 22.5. Sample Size for Tests on Rates (Proportions) -- 22.6. Sample Size for a Confidence Interval on a Rate (Proportion) -- 22.7. Sample Size for Significance of a Correlation Coefficient -- 22.8. Sample Size for Tests on Ranked Data.
22.9. Sample Size for Tests on Variances, Anaslysis of Variance, and Regression -- Chapter 23. Modeling and Clinical Decisions -- 23.1. Overview of Modeling -- 23.2. Straight-Line Models -- 23.3. Curved Models -- 23.4. Constants of Fit for Any Model -- 23.5. Multiple-Variable Models -- 23.6. Clinical Decision Based on Recursive Partitioning -- 23.7. Number Needed to Treat or to Benefit -- 23.8. Clinical Decision Based on Measures of Effectiveness: Outcomes Analysis -- Chapter 24. Regression and Correlation Methods -- 24.1. Regression Concepts and Assumptions -- 24.2. Correlation Concepts and Assumptions -- 24.3. Simple Regression -- 24.4. Correlation Coefficients -- 24.5. Tests and Confidence Intervals on Regression Parameters -- 24.6. Tests and Confidence Intervals on Correlation Coefficients -- 24.7. Curved Regression -- 24.8. Multiple Regression -- 24.9. Types of Regression -- 24.10. Logistic Regression -- Chapter 25. Survival and Time-Series Analysis -- 25.1. Time-Dependent Data -- 25.2. Survival Curves: Estimation -- 25.3. Survival Curves: Testing -- 25.4. Sequential Analysis -- 25.5. Time Series: Detecting Patterns -- 25.6. Time-Series Data: Testing -- Chapter 26. Methods You Might Meet, But Not Every Day -- 26.1. Overview -- 26.2. Analysis of Variance Issues -- 26.3. Regression Issues -- 26.4. Multivariate Methods -- 26.5. Nonparametric Tests -- 26.6. Imputation of Missing Data -- 26.7. Resampling Methods -- 26.8. Agreement Measures and Correlation -- 26.9. Bonferroni "Correction" -- 26.10. Logit and Probit -- 26.11. Adjusting for Outliers -- 26.12. Curve Fitting to Data -- 26.13. Tests of Normality -- Chapter Summaries -- References and Data Sources -- Tables of Probability Distributions -- I. Normal Distribution -- II. t Distribution -- III. Chi-square Distribution, Right Tail -- IV. Chi-square Distribution, Left Tail -- V. F Distribution.
VI. Binomial Distribution.
Abstract:
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.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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