Making Sense of Data: A Self-Instruction Manual on the Interpretation of Epidemiological Data - Brossura

Abramson, J. H.

Brossura

ISBN 10: 0195145259 ISBN 13: 9780195145250

Casa editrice: Oxford University Press, 2001

Riassunto

This is a self-instructional manual on the interpretation and use of epidemiologic data that deals with the basic concepts and skills needed for appraising published reports or study findings. Applications in clinical medicine, public health, community medicine, and research are presented. The numerous changes in this edition include the addition of a section on questions to be asked before deciding to apply study results in practice, discussions of new topics (Cox proportional hazards regression, qualitative studies, ROC curves), and fresh examples.

Su questo libro

L'autore

Z. H. Abramson is at both at Hebrew University.

Contenuti

• Introduction
• 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 causes
• E10: 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

Dettagli dell?edizione

• Editore: Oxford University Press
• Data di pubblicazione: 2001
• ISBN 10: 0195145259
• ISBN 13: 9780195145250
• Rilegatura: Copertina flessibile
• Lingua: Inglese
• Numero edizione: 3
• Numero di pagine: 384