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New to this edition
Taking readers through the common statistical methods seen in published research and guidelines, the text focuses on how to interpret and analyse statistics for clinical practice. Using extracts from real studies, the author illustrates how data can be employed correctly and incorrectly in medical research helping readers to evaluate the statistics they encounter and appropriately implement findings in clinical practice. End of chapter exercises, case studies and multiple choice questions help readers to apply their learning and develop their own interpretative skills. This thoroughly revised edition includes new chapters on meta-analysis, missing data, and survival analysis.
Readership: Medical students at undergraduate and postgraduate level, doctors, medical researchers, and healthcare professionals as well as all those concerned with medical data |
1: Introduction
2: The Design of Experiments
3: Sampling and observational studies
4: Summarizing data
5: Presenting data
6: Probability
7: The Normal distribution
8: Estimation
9: Significance tests
10: Comparing the means of small samples
11: Regression and correlation
12: Methods based on rank order
13: The analysis of cross-tabulations
14: Choosing the statistical method
15: Multifactorial methods
16: Time to event data
17: Meta-analysis
18: Determination of sample size
19: Missing data
20: Clinical measurement
21: Mortality statistics and population structure
22: The Bayesian approach
23: Appendix A Suggested answers to exercises
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