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Medical Statistics from Scratch. An Introduction for Health Professionals. 3rd Edition

  • ID: 2785664
  • Book
  • 408 Pages
  • John Wiley and Sons Ltd
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Correctly understanding and using medical statistics is a key skill for all medical students and health professionals.

In an informal and friendly style, Medical Statistics from Scratch provides a practical foundation for everyone whose first interest is probably not medical statistics. Keeping the level of mathematics to a minimum, it clearly illustrates statistical concepts and practice with numerous real world examples and cases drawn from current medical literature.

This fully revised and updated third edition includes new material on: 

  • missing data, random allocation and concealment of data
  • intra–class correlation coefficient
  • effect modification and interaction
  • diagnostic testing and the ROC curve
  • standardisation

Medical Statistics from Scratch is an ideal learning partner for all medical students and health professionals needing an accessible introduction, or a friendly refresher, to the fundamentals of medical statistics.

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Preface to the 3rd Edition xv

Preface to the 2nd Edition xvii

Preface to the 1st Edition xix

Introduction xxi

I Some Fundamental Stuff 1

1 First things first the nature of data 3

II Descriptive Statistics 15

2 Describing data with tables 17

3 Every picture tells a story describing data with charts 31

4 Describing data from its shape 49

5 Numbers R us 59

6 Measures of spread 72

III The Confounding Problem 87

7 Confounding like the poor, (nearly) always with us 89

IV Design and Data 97

8 Research design Part I: Observational study designs 99

9 Research design Part II: Getting stuck in experimental studies 118

10 Getting the participants for your study: ways of sampling 127

V Chance Would be a Fine Thing 135

11 The idea of probability 137

12 Risk and odds 145

VI The Informed Guess An Introduction to Confidence Intervals 161

13 Estimating the value of a single population parameter the idea of confidence intervals 163

14 Using confidence intervals to compare two population parameters 175

15 Confidence intervals for the ratio of two population parameters 191

VII Putting it to the Test 201

16 Testing hypotheses about the difference between two population parameters 203

17 The chi–squared (2) test what, why, and how? 226

18 Testing hypotheses about the ratio of two population parameters 239

VIII Becoming Acquainted 245

19 Measuring the association between two variables 247

20 Measuring agreement 260

IX Getting into a Relationship 267

21 Straight line models: linear regression 269

22 Curvy models: Logistic regression 294

X Three More Chapters 309

23 Measuring survival 311

24 Systematic review and meta–analysis 325

25 Diagnostic testing 336

Appendix: Table of random numbers 342

References 343

Solutions to Exercises 353

Index 381

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David Bowers
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