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Statistics in Medicine, Fourth Edition, helps medical and biomedical investigators design and answer questions about analyzing and interpreting data and predicting the sample size required to achieve useful results. It makes medical statistics easy for the non-biostatistician by outlining common methods used in 90% of medical research. The text covers how to plan studies from conception to publication, what to do with data, and follows with step-by-step instructions for biostatistical methods from the simplest levels, to more sophisticated methods now used in medical articles. Examples from almost every medical specialty, and from dentistry, nursing, pharmacy and health care management are provided.
This book does not require background knowledge of statistics or mathematics beyond high school algebra and provides abundant clinical examples and exercises to reinforce concepts. It is a valuable source for biomedical researchers, healthcare providers and anyone who conducts research or quality improvement projects.
Table of Contents:
- 1. Planning Studies: From Design to Publication
- 2. Planning Analysis: Addressing Your Scientific Objective
- 3. Probability and Relative Frequency
- 4. Distributions
- 5. Descriptive Statistics
- 6. Finding Probabilities
- 7. Hypothesis Testing: Concept and Practice
- 8. Confidence Intervals
- 9. Tests on Categorical Data
- 10. Risks, Odds, and ROC Curves
- 11. Tests of Location with Continuous Outcomes
- 12. Equivalence Testing
- 13. Tests on Variability and Distributions
- 14. Measuring Association and Agreement
- 15. Linear Regression and Correlation
- 16. Multiple Linear and Curvilinear Regression
- 17. Logistic Regression for Binary Outcomes
- 18. Regression Models for Count Outcomes
- 19. Analysis of Censored Time-To-Event Data
- 20. Analysis of Repeated Continuous Measures of Time
- 21. Sample Size Estimation
- 22. Clinical Trials and Group Sequential Analyses
- 23. Epidemiology and Alternative Sampling Designs
- 24. Meta Analyses
- 25. Bayesian Statistics
- 26. Questionnaires and Surveys
- 27. Techniques to Aid Analysis
- 28. Methods You Might Meet, But Not Every Day
About the Author:
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.
Daniel L. Gillen, PhD, is Professor and Chair of Statistics at University of California, Irvine (UCI). He is Fellow of the American Statistical Association and Past President of the Western North American Region of the International Biometric Society.
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