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Biostatistics for Medical and Biomedical Practitioners
1st Edition - September 3, 2015
Author: Julien I. E. Hoffman
Paperback ISBN:9780128023877
9 7 8 - 0 - 1 2 - 8 0 2 3 8 7 - 7
eBook ISBN:9780128026076
9 7 8 - 0 - 1 2 - 8 0 2 6 0 7 - 6
Biostatistics for Practitioners: An Interpretative Guide for Medicine and Biology deals with several aspects of statistics that are indispensable for researchers and students… Read more
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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.
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
professionals, graduate students and trainees across the biomedical sciences.
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
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
No. of pages: 770
Language: English
Published: September 3, 2015
Imprint: Academic Press
Paperback ISBN: 9780128023877
eBook ISBN: 9780128026076
JH
Julien I. E. Hoffman
Julien I E Hoffman, M.D., F.R.C.P (London) was born and educated in Salisbury (now Harare) in Southern Rhodesia (now Zimbabwe). He received a Bsc (Hons) in 1945 from the University of the Witwatersrand in South Africa, and his M.B., B.Ch. degree there in 1949. After working in the Departments of Medicine in Johannesburg General Hospital and in the Central Middlesex Hospital in London, he worked for the Medical Research Council at the Royal Postgraduate School in Hammersmith, London. Then he spent two years training in Pediatric Cardiogy at Boston Children’s Hospital, followed by 15 months as a Fellow at the Cardiovascular Research Institute (CVRI) at the University of California in San Francisco (UCSF).
In 1962 he joined the faculty of the Albert Einstein College of Medicine in New York, and moved in 1966 to UCSF as Associate Professor of Pediatrics and member of the CVRI. He spent 50% of his time in the care of children with heart disease and 50% of his time doing research into the pathophysiology of the coronary circulation.
His interest in Statistics began while taking his Science degree. In England, he took a short course run by Bradford Hill. On returning to Johannesburg he was assigned to statistical analyses for other members of the Department of Medicine. Learning was by trial and error, helped by Dr J Kerrich, head of the University’s Statistics Department. Hoffman began teaching statistics to Medical students in 1964, and in San Francisco conducted an approved course for Fellows and Residents for over 30 years. He was a member of the Biostatistics group for approving and coordinating statistics at UCSF. For many years he was a statistical consultant for the journal Circulation Research, and was intermittently statistical consultant to several other medical journals.
Affiliations and expertise
Professor of Pediatrics, Emeritus, Senior Member of the Cardiovascular Research Institute, University of California, San Francisco, CA