Medical Statistics at a Glance

Medical Statistics at a Glance is a concise and accessible introduction and revision aid for this complex subject. The self-contained chapters explain the underlying concepts of medical statistics and provide a guide to the most commonly used statistical procedures.
This new edition of Medical Statistics at a Glance:
Presents key facts accompanied by clear and informative tables and diagrams
Focuses on illustrative examples which show statistics in action, with an emphasis on the interpretation of computer data analysis rather than complex hand calculations
Includes extensive cross-referencing, a comprehensive glossary of terms and flow-charts to make it easier to choose appropriate tests
Now provides the learning objectives for each chapter
Includes a new chapter on Developing Prognostic Scores
Includes new or expanded material on study management, multi-centre studies, sequential trials, bias and different methods to remove confounding in observational studies, multiple comparisons, ROC curves and checking assumptions in a logistic regression analysis
The companion website at www.medstatsaag.com contains supplementary material including an extensive reference list and multiple choice questions (MCQs) with interactive answers for self-assessment.
Medical Statistics at a Glance will appeal to all medical students, junior doctors and researchers in biomedical and pharmaceutical disciplines.
Reviews of the previous editions
"The more familiar I have become with this book, the more I appreciate the clear presentation and unthreatening prose. It is now a valuable companion to my formal statistics course."
–International Journal of Epidemiology
"I heartily recommend it, especially to first years, but it's equally appropriate for an intercalated BSc or Postgraduate research. If statistics give you headaches - buy it. If statistics are all you think about - buy it."
–GKT Gazette
"...I unreservedly recommend this book to all medical students, especially those that dislike reading reams of text. This is one book that will not sit on your shelf collecting dust once you have graduated and will also function as a reference book."
–4th Year Medical Student, Barts and the London Chronicle, Spring 2003

Aviva Petrie, Head of Biostatistics Unit and Senior Lecturer, Eastman Dental Institute, University College London; Honorary Lecturer in Medical Statistics, Medical Statistics Unit, London School of Hygiene and Tropical Medicine



Caroline Sabin, Professor of Medical Statistics and Epidemiology, Department of Primary Care and Population Sciences, Royal Free and University College Medical School, London.

"Overall, Medical Statistics at a Glance is very useful to students who are aiming to learn basic medical statistics concepts. Clinicians and statistics students can keep a copy of this book as a quick initial reference. This book is highly recommended as an excellent Medical Statistics guide." (Journal of Biopharmaceutical Statistics, August 2010)

Preface
Learning objectives
Handling data
1 Types of data
2 Data entry
3 Error checking and outliers
4 Displaying data graphically
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 67
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 Glossary of terms
Index