The aim of the book
How to use the book

A. Basic Concepts and Procedures

A1 Introduction
A2 Determining what the facts are, Summarizing the facts
A3 Absolute and relative differences
A4 Diagrams
A5 Seeking explanations for the facts, Testing explanations
A6 The basic scientific process, Rates
A7 Rates (continued), Inspecting a two-dimensional table
A8 Inspecting a two-dimensional table (continued)
A9 Inspecting a two-dimensional table (continued), Associations
A10 Associations (continued), Confounding
A11 Confounding (continued), Effect modification
A12 Refinement, skeleton tables, Elaborating an association
A13 Modifying and confounding effects
A14 Elaborating an association (continued)
A15 The use of rates, Causal explanations, Testing causal explanations
A16 Testing causal explanations (continued, Basic procedure for appraisal of data, What are the facts? What are the possible explanations? What additional information is required?
A17 Uses of epidemiological data
A18 Test yourself (A)

B. Rates and Other Measures

B1 Introduction, What is a rate? Prevalence rates
B2 Prevalence rates (continued)
B3 Questions about a rate, What kind of rate is it? Of what is it a rate? To what population or group does the rate refer? How was the information obtained?
B4 Sources of bias, Confidence interval, Validity, Qualitative studies
B5 Use of prevalence data, Incidence rates
B6 Incidence rates (continued)
B7 Bias in incidence studies
B8 Uses of incidence rates
B9 Estimating the individual's chances, Time to event (survival time)
B10 Estimating the individual's chances (continued), Other rates, What are the odds?
B11 Other rates (continued), Odds ratio
B12 Other measures
B13 Indirect standardization
B14 Indirect standardization (continued), Direct standardization
B15 The use of standardized rates
B16 Test yourself (B)

C. How Good Are the Measures?

C1 Introduction
C2 Validity of a measure, Sensitivity and specificity
C3 Misclassification
C4 Differential misclassification
C5 Effects of misclassification
C6 Effects of misclassification (continued)
C7 Other ways of appraising validity, Reliability
C8 Appraisal of reliability
C9 Appraisal of reliability (continued), Regression towards the mean, Taking account of validity and reliability, Screening tests
C10 Appraisal of a screening test
C11 Appraisal of a screening test (continued)
C12 Appraisal of diagnostic tests, ROC curves, The meaning of "normal"
C13 Test yourself (C)

D. Making Sense of Associations

D1 Introduction
D2 Explanations for an association
D3 Effects of misclassification, Statistical significance
D4 Statistical significance (continued)
D5 Confounding effects
D6 Confounding effects (continued)
D7 Multivariate analysis
D8 Explanations for the findings, Risk factors and risk markers, Appraising a risk marker, Uses of the findings
D9 Risk factors and risk markers (continued), Measures of the strength of an association
D10 Measures of strength
D11 Measures of strength (continued), Matched samples
D12 Synergism
D13 Appraising stratified data, Making sense of multivariate analysis
D14 Multiple logistic regression
D15 Multiple logistic regression (continued)
D16 Proportional hazards regression
D17 Multiple linear regression
D18 Test yourself (D)

E. Causes and Effects

E1 Introduction, Kinds of Study
E2 Appraising the results of a cross-sectional study
E3 Appraising the results of a case-control study
E4 Appraising the results of a cohort study
E5 Appraising the results of a group-based study
E6 Appraising the results of an experiment
E7 Appraising the results of a quasi-experiment
E8 Artifact, confounding or cause? E9 Coping with confounding, Delving into causesE10 Evidence for a causal relationship
E11 Evidence for a causal relationship (continued), The impact of a causal factor
E12 The attributable fraction
E13 Prevented and preventable fractions
E14 Test yourself (E)

F. Meta-Analysis: Putting It All Together

F1 Introduction
F2 The scope of meta-analysis
F3 Measures used in meta-analysis
F4 Measures used in meta-analysis (continued), Basic information
F5 Finding the studies
F6 Selecting studies
F7 The quality of the studies, Extracting the findings, Apples and oranges
F8 Appraising combinability, Explaining heterogeneity
F9 Explaining heterogeneity (continued)
F10 Effect modification
F11 Using the results, Evaluating a meta-analysis
F12 Test yourself (F)

G. Putting Study Findings to Use

G1 Introduction
G2 Are the results accurately known
G3 Validity of the findings
G4 Relevance of the findings
G5 Expected effects
G6 Feasibility and cost
G7 Test yourself (G)

References
Index