2. Auflage - Mai 2003
44,90 Euro
2003. 512 Seiten, Softcover
ISBN-10: 0-86542-871-9
ISBN-13: 978-0-86542-871-3 - John Wiley & Sons

Preis inkl. Mehrwertsteuer zzgl. Versandkosten.







Kurzbeschreibung
Essential Medical Statistics is a classic amongst medical statisticians. An introductory textbook, it presents statistics with a clarity and logic that demystifies the subject, while providing a comprehensive coverage of advanced as well as basic methods.

The second edition of Essential Medical Statistics has been comprehensively revised and updated to include modern statistical methods and modern approaches to statistical analysis, while retaining the approachable and non-mathematical style of the first edition. The book now includes full coverage of the most commonly used regression models, multiple linear regression, logistic regression, Poisson regression and Cox regression, as well as a chapter on general issues in regression modelling. In addition, new chapters introduce more advanced topics such as meta-analysis, likelihood, bootstrapping and robust standard errors, and analysis of clustered data.

Aimed at students of medical statistics, medical researchers, public health practitioners and practising clinicians using statistics in their daily work, the book is designed as both a teaching and a reference text. The format of the book is clear with highlighted formulae and worked examples, so that all concepts are presented in a simple, practical and easy-to-understand way. The second edition enhances the emphasis on choice of appropriate methods with new chapters on strategies for analysis and measures of association and impact.

Essential Medical Statistics is supported by a web site at www.blackwellpublishing.com/essentialmedstats. This useful online resource provides statistical datasets to download, as well as sample chapters and future updates.

Reviews of the first edition

'This book is a well-written and easily readable introduction to statistical methods.'
Journal of the Royal Statistical Society

'The breadth of coverage of the book is excellent ... a rather different approach to teaching medical statistics.'
Statistics in Medicine

'The most readable book that I have yet discovered in the topic'
Community Health Studies

'This book is clearly presented and easy to understand, with realistic medical examples, and written by an experienced medical statistician... It has much to recommend it.'
British Medical Journal

Of related interest

Medical Statistics at a Glance
A. Petrie & C. Sabin
2000, 144 pages, 64 illustrations
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Statistical Methods in Medical Research
P. Armitage, G. Berry & J N S Matthews
Fourth edition 2001, 832 pages, 100 illustrations
0 632 05257 0

Interpretation and Uses of Medical Statistics
L. Daly & G. Bourke
Fifth edition 2000, 583 pages, 73 illustrations
0 632 04763 1

Aus dem Inhalt
Part A. Basics.

1. Using this book.

2. Defining the data.

3. Displaying the data.

Part B. Analysis of numerical outcomes.

4. Means, Standard Deviations and Standard Errors.

5. The Normal Distribution.

6. Confidence Interval for a Mean.

7. Comparison of two means: confidence intervals, hypothesis tests and P-values.

8. Using P-values and confidence intervals to interpret the results of statistical analyses.

9. Comparison of means from several groups: analysis of variance.

10. Linear Regression and Correlation.

11. Multiple Regression.

12. Goodness of fit and regression diagnostics.

13. Transformations.

Part C. Analysis of binary outcomes.

14. Probability, risks and odds (of disease).

15. Proportions and the binomial distribution.

16. Comparing two proportions.

17. Chi-squared tests for 2 × 2 and larger contingency tables.

18. Controlling for confounding: stratification.

19. Logistic regression: comparing two or more exposure groups.

20. Logisitic regression: controlling for confounding and other extensions.

21. Matched studies.

Part D. Longitudinal studies: Analysis of rates and survival times.

22. Longitudinal studies, rates and the Poisson distribution.

23. Comparing rates.

24. Poisson regression.

25. Standardisation.

26. Survival analysis: displaying and comparing survival patterns.

27. Regression analysis of survival data.

Part E. Statistical modelling.

28. Likelihood.

29. Regression modelling.

30. Relaxing model assumptions.

31. Analysis of clustered data.

32. Systematic reviews and meta-analysis.

33. Bayesian statistics.

Part F. Study design, analysis and interpretation.

34. Linking analysis to study design: summary of methods.

35. Calculation of Required Sample Size.

36. Measurement error: assessment and implications.

37. Measures of association and impact.

38. Strategies for analysis.

APPENDIX: Statistical Tables.

Bibliography