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.

Preface
Learning objectives
Handling data
1 Types of data
2 Data entry
3 Error checking and outliers
4 Displaying data diagrammatically
5 Describing data: the 'average'
6 Describing data: the 'spread'
7 Theoretical distributions: the Normal distribution
8 Theoretical distributions: other distributions
9 Transformations
Sampling and estimation
10 Sampling and sampling distributions
11 Confidence intervals
Study design
12 Study design I
13 Study design II
14 Clinical trials
15 Cohort studies
16 Case-control studies
Hypothesis testing
17 Hypothesis testing
18 Errors in hypothesis testing
Basic techniques for analysing data
Numerical data
19 Numerical data: a single group
20 Numerical data: two related groups
21 Numerical data: two unrelated groups
22 Numerical data: more than two groups
Categorical data
23 Categorical data: a single proportion
24 Categorical data: two proportions
25 Categorical data: more than two categories
Regression and correlation
26 Correlation
27 The theory of linear regression
28 Performing a linear regression analysis
29 Multiple linear regression
30 Binary outcomes and logistic regression
31 Rates and Poisson regression
32 Generalized linear models
33 Explanatory variables in statistical models
Important considerations
34 Bias and confounding
35 Checking assumptions
36 Sample size calculations
37 Presenting results
Additional chapters
38 Diagnostic tools
39 Assessing agreement
40 Evidence-based medicine
41 Methods for clustered data
42 Regression methods for clustered data
43 Systematic reviews and meta-analysis
44 Survival analysis
45 Bayesian methods
46 Developing prognostic scores
Appendices
A Statistical tables
B Altman's nomogram for sample size calculations
C Typical computer output
D EQUATOR network checklists and critical appraisal templates
E Glossary of terms
F Chapter numbers with relevant multiple-choice questions and structured questions from Medical Statistics at a Glance Workbook
Index

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.