Medical Statistics from Scratch
An Introduction for Health Professionals
4. Auflage Oktober 2019
496 Seiten, Softcover
Handbuch/Nachschlagewerk
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.
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.
Preface to the 3rd Edition xxi
Preface to the 2nd Edition xxiii
Preface to the 1st Edition xxv
Introduction xxvii
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 51
5 Measures of location - Numbers R Us 62
6 Measures of spread - Numbers R Us - (again) 75
7 Incidence, prevalence, and standardisation 92
III The Confounding Problem 111
8 Confounding - like the poor, (nearly) always with us 113
IV Design and Data 125
9 Research design - Part I: Observational study designs 127
10 Research design - Part II: Getting stuck in - experimental studies 146
11 Getting the participants for your study: ways of sampling 156
V Chance Would Be a Fine Thing 165
12 The idea of probability 167
13 Risk and odds 175
VI The Informed Guess - An Introduction to Confidence Intervals 191
14 Estimating the value of a single population parameter - the idea of confidence intervals 193
15 Using confidence intervals to compare two population parameters 206
16 Confidence intervals for the ratio of two population parameters 224
VII Putting it to the Test 235
17 Testing hypotheses about the difference between two population parameters 237
18 The Chi-squared (chi²) test - what, why, and how? 261
19 Testing hypotheses about the ratio of two population parameters 276
VIII Becoming Acquainted 283
20 Measuring the association between two variables 285
21 Measuring agreement 298
IX Getting into a Relationship 307
22 Straight line models: linear regression 309
23 Curvy models: logistic regression 334
24 Counting models: Poisson regression 349
X Four More Chapters 363
25 Measuring survival 365
26 Systematic review and meta-analysis 380
27 Diagnostic testing 393
28 Missing data 400
Appendix: Table of random numbers 414
References 415
Solutions to exercises 424
Index 457