Making sense of data : a self-instruction manual on the interpretation of epidemiological data /

This is a self-instructed manual on the interpretation and use of epidemiologic data that deal with the basic concepts and skills needed for appraising published reports or study findings.

Bibliographic Details
Main Author:	Abramson, J. H. (Joseph Herbert), 1924-
Other Authors:	Abramson, Z. H.
Format:	eBook
Language:	English
Published:	Oxford ; New York : Oxford University Press, 2001.
Edition:	3rd ed.
Subjects:	Epidemiology > Statistical methods. Epidemiology > Statistical methods > Problems, exercises, etc. Epidemiologic Methods Data Interpretation, Statistical Épidémiologie > Méthodes statistiques. Épidémiologie > Méthodes statistiques > Problèmes et exercices. MEDICAL > Health Risk Assessment. MEDICAL > Epidemiology. Epidemiology > Statistical methods Epidemiologie. Statistiek. Epidemiologia. Métodos epidemiológicos. Electronic books. Programmed Instruction Problems and Exercises exercise books. programmed textbooks. self-instructional materials. Programmed instructional materials Problems and exercises Problems and exercises. Programmed instructional materials. Self-instructional works. Matériel d'enseignement programmé. Problèmes et exercices. Matériel d'auto-enseignement.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Contents
Introduction
The aim of this book
How to use this 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
A17. Uses of epidemiological data
A18. TEST YOURSELF (A)
B. Rates and Other Measures
B1. Introduction
What is a rate?
Prevalence ratesB2. 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 toward 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