Biostatistics for Medical and Biomedical Practitioners

Häftad, Engelska, 2015

AvJulien I. E. Hoffman

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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

Produktinformation

Utgivningsdatum2015-09-08
Mått191 x 235 x undefined mm
Vikt1 560 g
FormatHäftad
SpråkEngelska
Antal sidor770
FörlagElsevier Science
ISBN9780128023877

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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.

A. BASIC ASPECTS OF STATISTICS1. Basic Concepts 2. Statistical Use And Misuse3. Some Practical Aspects4. Exploratory and Descriptive Analysis5. Basic ProbabilityB. CONTINUOUS DISTRIBUTIONS6. Normal Distribution7. Statistical Inference: Confidence Limits And The Central Limit Theorem8. Other Continuous Distributions9. Outliers And Extreme ValuesC. HYPOTHESIS TESTING10. Hypothesis testing: The Null Hypothesis, Significance and Type I error11. Hypothesis Testing: Sample Size, Effect Size, Power, Type II ErrorsD. DISCRETE AND CATEGORICAL DISTRIBUTIONS12. Permutations and combinations13. Hypergeometric Distribution14. Categorical And Cross-Classified Data: Goodness Of Fit And Association15. Categorical And Cross-Classified Data: McNemar’s Test, Kolmogorov-Smirnov Tests, Concordance16. Binomial and Multinomial Distributions17. Proportions18. Poisson Distribution19. Negative Binomial DistributionE. PROBABILITY IN EPIDEMIOLOGY AND MEDICAL DIAGNOSIS20. Some Epidemiological Considerations: Odds Ratio, Relative Risk, And Attributable Risk21. Probability, Bayes Theorem, Medical Diagnostic Evaluation, and ScreeningF. COMPARING MEANS22: Comparison Of Two Groups: T Tests And Non-Parametric Tests23. t Test Variants: Cross-over Tests, Equivalence Tests24. Multiple Comparisons25. Analysis Of Variance. I. One-Way26. Analysis Of Variance. II. More Complex FormsG. REGRESSION AND CORRELATION27. Linear Regression28. Variations based on linear regression29. Correlation30. Multiple Regression31. Serial measurements: time series, control charts, cusums32. Dose-Response Analysis33. Logistic Regression34. Poisson RegressionH. MISCELLANEOUS TOPICS35. Survival Analysis36. Meta-Analysis37. Resampling Statistics38. Study Design: Sampling, Clinical TrialsAnswers to problemsGlossaryIndex