Biostatistics for Medical and Biomedical Practitioners - 1st Edition - ISBN: 9780128023877, 9780128026076

Biostatistics for Medical and Biomedical Practitioners

1st Edition

Authors: Julien Hoffman
eBook ISBN: 9780128026076
Paperback ISBN: 9780128023877
Imprint: Academic Press
Published Date: 8th September 2015
Page Count: 770
Tax/VAT will be calculated at check-out Price includes VAT (GST)
30% off
30% off
30% off
30% off
30% off
20% off
20% off
30% off
30% off
30% off
30% off
30% off
20% off
20% off
30% off
30% off
30% off
30% off
30% off
20% off
20% off
71.95
50.37
50.37
50.37
50.37
50.37
57.56
57.56
60.99
42.69
42.69
42.69
42.69
42.69
48.79
48.79
99.95
69.97
69.97
69.97
69.97
69.97
79.96
79.96
Unavailable
Price includes VAT (GST)
× DRM-Free

Easy - Download and start reading immediately. There’s no activation process to access eBooks; all eBooks are fully searchable, and enabled for copying, pasting, and printing.

Flexible - Read on multiple operating systems and devices. Easily read eBooks on smart phones, computers, or any eBook readers, including Kindle.

Open - Buy once, receive and download all available eBook formats, including PDF, EPUB, and Mobi (for Kindle).

Institutional Access

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.

Description

Biostatistics for Practitioners: An Interpretative Guide for Medicine and Biology deals with several aspects of statistics that are indispensable for researchers and students across the biomedical sciences.

The book features a step-by-step approach, focusing on standard statistical tests, as well as discussions of the most common errors.

The book is based on the author’s 40+ years of teaching statistics to medical fellows and biomedical researchers across a wide range of fields.

Key Features

  • Discusses how to use the standard statistical tests in the biomedical field, as well as how to make statistical inferences (t test, ANOVA, regression etc.)
  • Includes non-standards tests, including equivalence or non-inferiority testing, extreme value statistics, cross-over tests, and simple time series procedures such as the runs test and Cusums
  • Introduces procedures such as multiple regression, Poisson regression, meta-analysis and resampling statistics, and provides references for further studies

Readership

professionals, graduate students and trainees across the biomedical sciences.

Table of Contents

  • About the Author
  • Preface
  • Acknowledgments
  • Part 1. Basic Aspects of Statistics
    • Chapter 1. Basic Concepts
      • Introduction
      • Basic Uses of Statistics
      • Data
      • General Approach to Study Design
      • A Brief History of Statistics
    • Chapter 2. Statistical Use and Misuse in Scientific Publications
      • Early Use of Statistics
      • Current Tests in Common Use
      • Statistical Misuse
      • Basic Guides to Statistics
    • Chapter 3. Some Practical Aspects
      • Statistics Programs
      • Variables
      • Measurement Scales
      • Displaying Data Sets
      • Accuracy of Measurement
      • Notation
      • Operators
      • Weights
      • Statistics Books
    • Chapter 4. Exploratory Descriptive Analysis
      • Basic Concepts
      • Advanced and Alternative Concepts
      • Appendix
    • Chapter 5. Basic Probability
      • Introduction
      • Types of Probability
      • Basic Principles and Definitions
      • Conditional Probability
      • Bayes' Theorem
  • Part 2. Continuous Distributions
    • Chapter 6. Normal Distribution
      • Introduction
      • Normal or Gaussian Curve
      • Populations and Samples
      • Description of the Distribution Shape
      • Determining Normality
      • Ungrouped Data
      • How Important Is Normality?
    • Chapter 7. Statistical Limits and the Central Limit Theorem
      • Central Limit Theorem
      • Tolerance Limits
      • Reporting Results
    • Chapter 8. Other Continuous Distributions
      • Continuous Uniform Distribution
      • Exponential Distribution
      • Logarithmic Distribution
      • Weibull Distribution
      • Chi-Square Distribution
      • Variance Ratio (F) Distribution
    • Chapter 9. Outliers and Extreme Values
      • Outliers
      • Extreme Values
      • Appendix
  • Part 3. Hypothesis Testing
    • Chapter 10. Hypothesis Testing
      • Hypotheses
      • Significance
    • Chapter 11. Hypothesis Testing
      • Basic Concepts
      • Advanced and Alternative Concepts
  • Part 4. Discrete and Categorical Distributions
    • Chapter 12. Permutations and Combinations
      • Permutations
      • Combinations
    • Chapter 13. Hypergeometric Distribution
      • Introduction
      • General Formula
      • Fisher's Exact Test
      • Multiple Groups
    • Chapter 14. Categorical and Cross-Classified Data
      • Basic Concepts
      • Advanced Concepts
    • Chapter 15. Categorical and Cross-Classified Data
      • Paired Samples: McNemar's Test
      • Testing Ordered Categorical Data: Kolmogorov–Smirnov Tests
      • Concordance (Agreement) between Observers
      • Intraclass Correlation
    • Chapter 16. Binomial and Multinomial Distributions
      • Basic Concepts
      • Advanced or Alternative Concepts
      • Appendix
    • Chapter 17. Proportions
      • Introduction
      • Proportions and Binomial Theorem
      • Confidence Limits
      • Sample and Population Proportions
      • Sample Size
      • Comparing Proportions
      • Pooling Samples
    • Chapter 18. The Poisson Distribution
      • Introduction
      • Relationship to the Binomial Distribution
      • Goodness of Fit to a Poisson Distribution
      • The Ratio of the Variance to the Mean of a Poisson Distribution
      • Setting Confidence Limits
      • The Square Root Transformation
      • Cumulative Poisson Probabilities
      • Differences between Means of Poisson Distributions
      • Determining the Required Sample Size
      • Appendix
    • Chapter 19. Negative Binomial Distribution
      • Introduction
      • Probability of r Successes
      • Overdispersed Distribution
      • Uses of the Negative Binomial
  • Part 5. Probability in Epidemiology and Medical Diagnosis
    • Chapter 20. Some Epidemiological Considerations
      • Basic Concepts
      • Advanced Concepts
    • Chapter 21. Probability, Bayes' Theorem, Medical Diagnostic Evaluation, and Screening
      • Bayes' Theorem Applied
      • Sensitivity and Specificity
      • Likelihood Ratios
      • Cutting Points
      • Receiver Operating Characteristic Curves
      • Some Comments on Screening Tests
  • Part 6. Comparing Means
    • Chapter 22. Comparison of Two Groups
      • Basic Concepts
      • Advanced Concepts
      • Appendix
    • Chapter 23. t-Test Variants
      • Crossover Trials
      • Equivalence and Noninferiority Testing
    • Chapter 24. Multiple Comparisons
      • Introduction
      • Bonferroni Correction and Equivalent Tests
      • Group Sequential Boundaries
      • Sequential Analysis
      • Adaptive Methods
    • Chapter 25. Analysis of Variance I. One-Way
      • Basic Concepts
      • Advanced Concepts
    • Chapter 26. Analysis of Variance II. More Complex Forms
      • Basic Concepts
      • Advanced and Alternative Concepts
      • Appendix
  • Part 7. Regression and Correlation
    • Chapter 27. Linear Regression
      • Basic Concepts
      • Advanced or Alternative Concepts
      • Appendix
    • Chapter 28. Variations Based on Linear Regression
      • Transforming the Y Variate
      • Inverse Prediction
      • Line of Best Fit Passes through Zero
      • Errors in the X Variate
      • Break Points
      • Resistant Lines
      • Appendix
    • Chapter 29. Correlation
      • Basic Concepts
      • Advanced and Alternative Concepts
      • Appendix
    • Chapter 30. Multiple Regression
      • Basic Concepts
      • Advanced Concepts and Examples
    • Chapter 31. Serial Measurements
      • Introduction
      • Serial Correlation
      • Control Charts
      • Cumulative Sum Techniques (Cusums)
      • Serial Measurements
    • Chapter 32. Dose–Response Analysis
      • General Principles
      • Quantal Dose–Response Curves
    • Chapter 33. Logistic Regression
      • Introduction
      • Single Explanatory Variable
      • Multiple Explanatory Variables
      • Appropriateness of Model
    • Chapter 34. Poisson Regression
      • Introduction
      • Suitability of Poisson Regression
      • Detecting Overdispersion
      • Correcting for Overdispersion
  • Part 8. Miscellaneous Topics
    • Chapter 35. Survival Analysis
      • Basic Concepts
      • Advanced Concepts
    • Chapter 36. Meta-analysis
      • Introduction
      • Forest Graphs
      • Funnel Plots
      • Radial Plots
      • L'Abbé Plots
      • Criticisms of Meta-analysis
    • Chapter 37. Resampling Statistics
      • Introduction
      • Bootstrap
      • Permutations
      • Jackknife
      • Monte Carlo Methods
    • Chapter 38. Study Design
      • Sampling Problems
      • Historical Controls
      • Randomization
      • Clinical Trials
      • Placebo Effect
      • Alternatives to Randomized Clinical Trials
  • Part 9. End Texts
    • Answers to Problems
    • Glossary
    • Index

Details

No. of pages:
770
Language:
English
Copyright:
© Academic Press 2015
Published:
Imprint:
Academic Press
eBook ISBN:
9780128026076
Paperback ISBN:
9780128023877

About the Author

Julien Hoffman

Dr. Julien I. E. Hoffman has 40 years of experience teaching biostatistics to fellows in various medical fields. For about 15 years, Dr. Hoffman was a member of the Biostatistics Committee of the University of California and he still does statistical reviews for all the journals published by the American Heart Association.

The author has published 214 articles in journals, 164 chapters in books, 109 abstracts, and has edited 9 books.

Affiliations and Expertise

Professor of Pediatrics, Emeritus, Senior Member of the Cardiovascular Research Institute, University of California, San Francisco, CA