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Medical Statistics: A Textbook for the Health Sciences, Fourth Edition

Authors:
Michael J. Campbell, David Machin, and Stephen Walters
Publisher: Wiley
Copyright: 2007
ISBN-13: 978-0-470-02519-2
Pages: 344; paperback
Price: $29.50

Comment from the Stata technical group

Medical Statistics: A Textbook for the Health Sciences, Fourth Edition, by Michael J. Campbell, David Machin, and Stephen J. Walters, is one of many texts suitable for a semester-long statistics course for health professionals. However, it is both thorough and easy to read, setting it apart from other texts. The authors include the standard tools relevant to health professionals: odds ratios, survival analysis, observational studies, and more. Another helpful feature in this text is a section at the end of each chapter listing points the reader should consider when reading research publications about the use of the discussed methods.


Table of 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 Bayes’ 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 randomisation
13.4 Design features
13.5 Design options
13.6 Meta-analysis
13.7 The protocol
13.8 Checklists for design, analysis and reporting
13.9 Number needed to treat (NNT)
13.10 Points when reading the literature
13.11 Exercises
Chapter 14 Sample size issues
14.1 Introduction
14.2 Study size
14.3 Continuous data
14.4 Binary data
14.5 Prevalence
14.6 Subject withdrawals
14.7 Internal pilot studies
14.8 Points when reading the literature
14.9 Technical details
14.10 Exercises
Chapter 15 Common pitfalls
15.1 Introduction
15.2 Using the t-test
15.3 Plotting change against initial value
15.4 Repeated measures
15.5 Clinical and statistical significance
15.6 Exploratory data analysis
15.7 Points when reading the literature
15.8 Exercises
References
Solutions to exercises
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