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