Statistics in Medicine, 4th Edition

Statistics in Medicine, 4th Edition
PDF
  • eBook:
    Statistics in Medicine, 4th Edition
  • Author:
    Robert H. Riffenburgh, Daniel L. Gillen
  • Edition:
    4 edition
  • Categories:
  • Data:
    August 18, 2020
  • ISBN:
    0128153288
  • ISBN-13:
    9780128153284
  • Language:
    English
  • Pages:
    822 pages
  • Format:
    PDF

Book Description
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.

Content

1. Planning studies: from design to publication
2. Planning analysis: how to reach my scientific objective
3. Probability and relative frequency
4. Distributions
6. Finding probabilities
7. Hypothesis testing: concept and practice
8. Tolerance, prediction, and confidence intervals
9. Tests on categorical data
10. Risks, odds, and receiver operating characteristic 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 and multifactor analysis of variance
17. Logistic regression for binary outcomes
18. Poisson regression for count outcomes
19. Analysis of censored time-to-event data
20. Analysis of repeated continuous measurements over time
21. Sample size estimation
22. Clinical trials and group sequential testing
23. Epidemiology
24. Meta-analyses
25. Bayesian statistics
26. Questionnaires and surveys
27. Techniques to Aid Analysis
28. Methods you might meet, but not every day

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