Provides students and practitioners with a clear concise introduction to the statistics they will come across in their regular reading of clinical papers. Written by three experts with wide teaching and consulting experience "Medical Statistics: A Textbook for the Health Sciences Fourth Edition: " Assumes no prior knowledge of statistics Covers all essential statistical methods Completely revised updated and expanded Includes numerous examples and exercises on the interpretation of the statistics in papers published in medical journals From the reviews of the previous edition: ""The book has several excellent features: it is written by statisticians is.... well presented is well referenced.... and is short."" THE LANCET ""Many statisticians are concerned at the generally poor standard of statistics in papers published in medical journals. Perhaps this could be remedied if more research workers would spare a few hours to read through Campbell and Machin's book."" BRITISH MEDICAL JOURNAL "." a simple interesting and insightful introduction to medical statistics... highly recommended."" STATISTICAL METHODS IN MEDICAL RESEARCH ""Campbell and Machin found the golden mean... this book can be recommended for all students and all medical researchers."" ISCB NEWSLETTER

Contents.Preface.

Chapter 1 Uses and abuses of medical statistics. 1.1 Introduction. 1.2 Why use statistics? 1.3 Statistics is about common sense and good design. 1.4 Types of data. 1.5 How a statistician can help. 1.6 Further reading. 1.7 Exercises.

Chapter 2 Describing and displaying categorical data. 2.1 Summarising categorical data. 2.2 Displaying categorical data. 2.3 Points when reading the literature. 2.4 Exercises.

Chapter 3 Describing and displaying quantitative data. 3.1 Summarising continuous data. 3.2 Displaying continuous data. 3.3 Within-subject variability. 3.4 Presentation. 3.5 Points when reading the literature. 3.6 Exercises.

Chapter 4 Probability and decision making. 4.1 Types of probability. 4.2 Diagnostic tests. 4.3 Bayesa?? Theorem. 4.4 Relative (receiver)-operating characteristic (ROC) curve. 4.5 Points when reading the literature. 4.6 Exercises.

Chapter 5 Distributions. 5.1 Introduction. 5.2 The Binomial distribution. 5.3 The Poisson distribution. 5.4 Probability for continuous outcomes. 5.5 The Normal distribution. 5.6 Reference ranges. 5.7 Points when reading the literature. 5.8 Technical details. 5.9 Exercises.

Chapter 6 Populations samples standard errors and confidence intervals. 6.1 Populations. 6.2 Samples. 6.3 The standard error. 6.4 The Central Limit Theorem. 6.5 Standard errors for proportions and rates. 6.6 Standard errors of differences. 6.7 Confidence intervals for an estimate. 6.8 Confidence intervals for differences. 6.9 Points when reading the literature. 6.10 Technical details. 6.11 Exercises.

Chapter 7 p-Values and statistical inference. 7.1 Introduction. 7.2 The null hypothesis. 7.3 The p-value. 7.4 Statistical inference. 7.5 Statistical power. 7.6 Confidence intervals rather than p-values. 7.7 One-sided and two-sided tests. 7.8 Points when reading the literature. 7.9 Technical details. 7.10 Exercises.

Chapter 8 Tests for comparing two groups of categorical or continuous data. 8.1 Introduction. 8.2 Comparison of two groups of paired observations - continuous outcomes. 8.3 Comparison of two independent groups - continuous outcomes. 8.4 Comparison of two independent groups - categorical outcomes. 8.5 Comparison of two groups of paired observations - categorical outcomes. 8.6 Non-Normal distributions. 8.7 Degrees of freedom. 8.8 Points when reading the literature. 8.9 Technical details. 8.10 Exercises.

Chapter 9 Correlation and linear regression. 9.1 Introduction. 9.2 Correlation. 9.3 Linear regression. 9.4 Comparison of assumptions between correlation and regression. 9.5 Multiple regression. 9.6 Logistic regression. 9.7 Correlation is not causation. 9.8 Points when reading the literature. 9.9 Technical details. 9.10 Exercises.

Chapter 10 Survival analysis. 10.1 Time to event data. 10.2 Kaplan-Meier survival curve. 10.3 The logrank test. 10.4 The hazard ratio. 10.5 Modelling time to event data. 10.6 Points when reading the literature. 10.7 Exercises.

Chapter 11 Reliability and method comparison studies. 11.1 Introduction. 11.2 Repeatability. 11.3 Agreement. 11.4 Validity. 11.5 Method comparison studies. 11.6 Points when reading the literature. 11.7 Technical details. 11.8 Exercises.

Chapter 12 Observational studies. 12.1 Introduction. 12.2 Risk and rates. 12.3 Taking a random sample. 12.4 Questionnaire and form design. 12.5 Cross-sectional surveys. 12.6 Non-randomised studies. 12.7 Cohort studies. 12.8 Case-control studies. 12.9 Association and causality. 12.10 Points when reading the literature. 12.11 Technical details. 12.12 Exercises.

Chapter 13 The randomised controlled trial. 13.1 Introduction. 13.2 Why randomise? 13.3 Methods of randomisa