Medical Statistics / Edition 2by Aviva Petrie, Caroline Sabin
Pub. Date: 01/28/2005
Medical Statistics at a Glance provides a concise and accessible introduction and revision aid for undergraduate medical students and anyone wanting a straightforward introduction to this complex subject. Following the familiar, easy-to-use at a Glance format, each topic is presented as a double-page spread with key facts accompanied by clear, informative tables, formulae and graphs.
This new edition of Medical Statistics at a Glance:
- Contains a second colour throughout to enhance the visual appeal, making the subject even easier to understand
- Features worked examples on each topic, with emphasis on computer analysis of data rather than hand calculations
- Includes new topics on Rates and Poisson regression, Generalised linear models, Explanatory variables in statistical models and Regression models for clustered data.
- Has an accompanying website http://www.medstatsaag.com/containing supplementary material including multiple choice questions (MCQs) with annotated answers for self-assessment
Medical Statistics at a Glance will appeal to all medical students, junior doctors and researchers in biomedical and pharmaceutical disciplines.
Reviews of the last edition
"All medical professionals will come across statistics in their daily work and so a proper understanding of these concepts is invaluable. This is brought to you in this easily comprehensible succinct textbook.
.I unreservedly recommend this book to all medical students, especially those that dislike reading reams of text. This is one book that will not sit on your shelf collecting dust once you have graduated and will also function as a reference book."
4th Year Medical Student. Barts and the London Chronicle, Spring 2003,
vol.5, issue 1
Table of Contents
1. Types of data.
2. Data entry.
3. Error checking and outliers.
4. Displaying data graphically.
5. Describing data (1) - the ‘average’.
6. Describing data (2) - the ‘spread’.
7. Theoretical distributions (1) - the Normal distribution.
8. Theoretical distributions (2) - other distributions.
Sampling and estimation.
10. Sampling and sampling distributions.
11. Confidence Intervals.
12. Study design I.
13. Study design II.
14. Clinical trials.
15. Cohort studies.
16. Case-control studies.
17. Hypothesis testing.
18. Errors in hypothesis testing.
Basic techniques for analysing dataNumerical data.
19. A single group.
20. Two related groups.
21. Two unrelated groups.
22. More than two groupsCategorical data.
23. A single proportion.
24. Two proportions.
25. More than two categoriesRegression and correlation.
27. The theory of linear regression.
28. Performing a linear regression analysis.
29. Multiple linear regression analysis.
30. Binary outcomes and logistic regression31. Rates and Poisson regression.
32. Generalized linear models.
33. Explanatory variables in statistical models.
34. Issues in statistical modelling .
35. Checking assumptions.
36. Sample size calculations.
37. Presenting results.
38. Diagnostic tools.
39. Assessing agreement.
40. Evidence-based medicine.
41. Methods for clustered data.
42. Regression methods clustered data.
43. Systematic reviews and meta-analysis.
44. Survival analysis.
45. Bayesian methods.
A. Statistical tables.
B. Altman’s nomogram for sample size calculations.
C. Typical computer output.
D. Glossary of terms.
and post it to your social network
Most Helpful Customer Reviews
See all customer reviews >