An introduction to medical statistics

includes index

1 INTRODUCTION
1.1 Statistics and medicine
1.2 Statistics and mathematics
1.3 Statistics and computing
1.4 Assumptions and approximations
1.5 The scope of this book
2 THE DESIGN OF EXPERIMENTS
2.1 Comparing treatments
2.2 Random allocation
2.3 Stratification
2.4 Methods of allocation without random numbers
2.5 Volunteer bias
2.6 Intention to treat
2.7 Cross-over designs
2.8 Selection of subjects for clinical trials
2.9 Response bias and double blind studies
2.10 Assessment bias and placebos
2.11 Laboratory experiments
2.12 Experimental units and cluster randomized trials
2.13 Consent in clinical trials
2.14 Minimization
2.15 Multiple choice questions
2.16 Exercise: the 'know your midwife' trial
3 SAMPLING AND OBSERVATIONAL STUDIES
3.1 Observational studies
3.2 Censuses
3.3 Sampling
3.4 Random sampling
3.5 Sampling in clinical and epidemiological studies
3.6 Cross-sectional studies
3.7 Cohort studies
3.8 Case-control studies
3.9 Questionnaire bias in observational studies
3.10 Ecological studies
3.11 Multiple choice questions: observational studies
3.12 Exercise: Campylobacter jejuni infection
4 SUMMARIZING DATA
4.1 Types of data
4.2 Frequency distributions
4.3 Histograms and other frequency graphs
4.4 Shapes of frequency distribution
4.5 Medians and quantiles
4.6 The mean
4.7 Variance, range, and interquartile range
4.8 Standard deviation
4.9 Multiple choice questions: summarizing data
4.10 Exercise: student measurements and a graph of study numbers
Appendix 4A: The divisor for the variance
Appendix 4B Formulae for the sum of squares
5 PRESENTING DATA
5.1 Rates and proportions
5.2 Significant figures
5.3 Presenting tables
5.4 Pie charts
5.5 Bar charts
5.6 Scatter diagrams
5.7 Line graphs and time series
5.8 Misleading graphs
5.9 Using different colours
5.10 Logarithmic scales
5.11 Multiple choice questions: data presentation
5.12 Exercise: creating presentation graphs
Appendix 5A: logarithms
6 PROBABILITY
6.1 Probability
6.2 Properties of probability
6.3 Probability distributions and random variables
6.4 The Binomial distribution
6.5 Mean and variance
6.6 Properties of means and variances
6.7 The Poisson distribution
6.8 Conditional probability
6.9 Multiple choice questions: probability
6.10 Exercise: probability in court
Appendix 6A: Permutations and combinations
Appendix 6B Expected value of a sum of squares
7 THE NORMAL DISTRIBUTION
7.1 Probability for continuous variables
7.2 The Normal distribution
7.3 Properties of the Normal distribution
7.4 Variables which follow a Normal distribution
7.5 The Normal plot
7.6 Multiple choice questions: the Normal distribution
7.7 Exercise: distribution of some measurements obtained by students
Appendix 7A: Chi-squared, t and F
8 ESTIMATION
8.1 Sampling distributions
8.2 Standard error of a sample man
8.3 Confidence intervals
8.4 Standard error and confidence interval for a proportion
8.5 The difference between two means
8.6 Comparison of two proportions
8.7 Number needed to treat
8.8 Standard error of a sample standard deviation
8.9 Confidence interval for a proportion when numbers are small
8.10 Confidence interval for a median and other quantiles
8.11 Bootstrap or resampling methods
8.12 What is the correct confidence interval?
8.13 Multiple choice answers: confidence intervals
8.14 Exercise: confidence intervals in two acupuncture studies
Appendix 8A: Standard error of a man
9 SIGNIFICANCE TESTS
9.1 Testing a hypothesis
9.2 An example: the sign test
9.3 Principles of significance tests
9.4 Significance levels and types of error
9.5 One and two sided tests of significance
9.6 Significance, real, and important
9.7 Comparing the means of large samples
9.8 Comparison of two proportions
9.9 The power of a test
9.10 Multiple significance tests
9.11 Repeated significance tests and sequential analysis
9.12 Significance tests and confidence intervals
9.13 Multiple choice questions: significance tests
9.14 Exercise: Crohn's disease and cornflakes
10 COMPARING THE MEANS OF SMALL SAMPLES
10.1 The t distribution
10.2 The one sample t method
10.3 The means of two independent samples
10.4 The use of transformations
10.5 Deviations from the assumptions of t methods
10.6 What is a large sample?
10.7 Serial data
10.8 Comparing two variances by the F test
10.9 Comparing several using analysis of variance
10.10 Assumptions of the analysis of variance
10.11 Comparison of means after analysis of variance
10.12 Random effects in analysis of variance
10.13 Units of analysis and cluster randomized trials
10.14 Multiple choice questions: comparison of means
10.15 Exercise: some analyses comparing means
Appendix 10A: the ratio mean/standard

An Introduction to Medical Statistics, fourth edition, is a 'must-have' textbook. Written in an easy-to-understand style and packed with real life examples, the text clearly explains the common statistical methods seen in published research and guidelines, as well as how to interpret and analyse statistics for clinical practice