Now in its fourth edition, Medical Statistics at a Glance is a concise and accessible introduction to this complex subject. It provides clear instruction on how to apply commonly used statistical procedures in an easy-to-read, comprehensive and relevant volume. This new edition continues to be the ideal introductory manual and reference guide to medical statistics, an invaluable companion for statistics lectures and a very useful revision aid.
This new edition of Medical Statistics at a Glance:
* Offers guidance on the practical application of statistical methods in conducting research and presenting results
* Explains the underlying concepts of medical statistics and presents the key facts without being unduly mathematical
* Contains succinct self-contained chapters, each with one or more examples, many of them new, to illustrate the use of the methodology described in the chapter.
* Now provides templates for critical appraisal, checklists for the reporting of randomized controlled trials and observational studies and references to the EQUATOR guidelines for the presentation of study results for many other types of study
* Includes extensive cross-referencing, flowcharts to aid the choice of appropriate tests, learning objectives for each chapter, a glossary of terms and a glossary of annotated full computer output relevant to the examples in the text
* Provides cross-referencing to the multiple choice and structured questions in the companion Medical Statistics at a Glance Workbook
Medical Statistics at a Glance is a must-have text for undergraduate and post-graduate medical students, medical researchers and biomedical and pharmaceutical professionals.
Inhoudsopgave
Preface ix
Part 1 Handling data 1
1 Types of data 2
2 Data entry 4
3 Error checking and outliers 6
4 Displaying data diagrammatically 8
5 Describing data: the ‘average’ 10
6 Describing data: the ‘spread’ 12
7 Theoretical distributions: the Normal distribution 14
8 Theoretical distributions: other distributions 16
9 Transformations 18
Part 2 Sampling and estimation 21
10 Sampling and sampling distributions 22
11 Confidence intervals 24
Part 3 Study design 27
12 Study design I 28
13 Study design II 31
14 Clinical trials 34
15 Cohort studies 37
16 Case-control studies 40
Part 4 Hypothesis testing 43
17 Hypothesis testing 44
18 Errors in hypothesis testing 47
Part 5 Basic techniques for analysing data 51
Numerical data
19 Numerical data: a single group 52
20 Numerical data: two related groups 54
21 Numerical data: two unrelated groups 57
22 Numerical data: more than two groups 60
Categorical data
23 Categorical data: a single proportion 63
24 Categorical data: two proportions 66
25 Categorical data: more than two categories 69
Regression and correlation
26 Correlation 72
27 The theory of linear regression 75
28 Performing a linear regression analysis 77
29 Multiple linear regression 81
30 Binary outcomes and logistic regression 85
31 Rates and Poisson regression 89
32 Generalized linear models 93
33 Explanatory variables in statistical models 96
Important considerations
34 Bias and confounding 100
35 Checking assumptions 104
36 Sample size calculations 107
37 Presenting results 111
Part 6 Additional chapters 115
38 Diagnostic tools 116
39 Assessing agreement 119
40 Evidence-based medicine 124
41 Methods for clustered data 127
42 Regression methods for clustered data 130
43 Systematic reviews and meta-analysis 134
44 Survival analysis 138
45 Bayesian methods 142
46 Developing prognostic scores 144
Appendices 147
A Statistical tables 148
B Altman’s nomogram for sample size calculations (Chapter 36) 155
C Typical computer output 156
D Checklists and trial profile from the EQUATOR network and critical appraisal templates 169
E Glossary of terms 178
F Chapter numbers with relevant multiple-choice questions and structured questions from Medical Statistics at a Glance Workbook 188
Index 190
Over de auteur
Aviva Petrie is Honorary Associate Professor, Biostatistics Unit, UCL Eastman Dental Institute, London, UK.
Caroline Sabin is Professor of Medical Statistics and Epidemiology, Department of Primary Care and Population Sciences, Royal Free and University College Medical School, London, UK.