David A Savitz

Interpreting Epidemiologic Evidence

Strategies for Study Design & Analysis

• Gebundenes Buch

Produktbeschreibung

Evaluating the strength or persuasiveness of epidemiologic evidence is inherently challenging, both for those new to the field and for experienced researchers. There is a myriad of potential biases to consider, but little guidance about how to assess the likely impact on study results. This book offers a strategy for assessing epidemiologic research findings, explicitly describing the goals and products of epidemiologic research in order to better evaluate its successes and limitations. The focus throughout is on practical tools for making optimal use of available data to assess whether hypothesised biases are operative and to anticipate concerns at the point of study design in order to ensure that needed information is generated. Specific tools for assessing the presence and impact of selection bias in both cohort and case-control studies, bias from non-response, confounding, exposure measurement error, disease measurement error, and random error are identified and evaluated. The potential value of each approach as well as its limitations are discussed, using examples from the published literature. Such information should help those who generate and interpret epidemiologic research to apply methodological principles more effectively to substantive issues, leading to a more accurate appraisal of the current evidence and greater clarity about research needs.

Produktdetails

• Verlag: Oxford University Press
• Seitenzahl: 336
• Erscheinungstermin: 5. Juni 2003
• Englisch
• Abmessung: 246mm x 167mm x 32mm
• Gewicht: 622g
• ISBN-13: 9780195108408
• ISBN-10: 019510840X
• Artikelnr.: 22316391

Inhaltsangabe

* Interpreting Epidemiologic Evidence: Connecting Research to
Applications
* 1. Introduction
* Synopsis
* Learning Objectives
* Perspective
* Approach to the Evaluation of Evidence
* Organization of Book
* 2. The Nature of Epidemiologic Evidence
* Synopsis
* Learning Objectives
* Goals of Epidemiologic Research
* Measurement of Causal Relations Between Exposure and Disease
* Applications of Epidemiologic Research
* Framework for Examining Epidemiologic Evidence
* Relationship of Epidemiology to Health Policy
* Exercise: Critical Assessment of Study Methods, Results, and
Applications
* 3. Causal Diagrams for Epidemiologic Inference
* Synopsis
* Learning Objectives
* Introduction
* Causal Diagrams in Epidemiology
* Purpose and Terminology
* DAGs Encode Our Assumptions
* Statistical Associations
* Connection to Data Analyses
* Depicting Passage of Time
* Direct vs. Indirect Effects
* Concluding Thoughts
* Recommended Additional Readings
* Exercise: Application of Causal Diagrams for Epidemiologic Inference
* 4. Strategy for Drawing Inferences from Epidemiologic Evidence
* Synopsis
* Learning Objectives
* Conceptual Framework for the Evaluation of Error
* Estimation of Measures of Association
* Systematic Evaluation of Sources of Error
* Objective Evaluation of Sources of Error
* Identifying the Most Important Sources of Error
* Specifying Bias Scenarios
* Exercise: Specifying Scenarios of Bias
* 5. Confounding I: Theoretical Considerations
* Synopsis
* Learning Objectives
* Definition
* Identifying Potential Confounders
* Traditional Approach to Assessing Confounding
* Modern Approach to Assessing Confounding
* Inappropriate Adjustments
* Assessing the Direction and Magnitude of Potential Confounding
* Methods of Controlling Confounding
* Randomization
* Selection of Study Setting Free of Confounding
* Restrict Study Groups to Enhance Comparability
* Statistical Adjustment for Confounding
* Recommended Additional Readings
* Exercise: Conceptual Basis of Confounding
* 6. Confounding II: Practical Considerations
* Synopsis
* Learning Objectives
* Evaluating the Presence and Impact of Confounding
* Specifying Scenarios of Confounding
* Assessing Whether Confounding is Present
* Consider Potential for Complete Confounding
* Assess Consequences of Inaccurate Confounder Measurement
* Applying Knowledge of Confounding Based on Other Studies
* Assessing Confounding When Risk Factors are Unknown
* Dose-Response Gradients and Potential for Confounding
* Integrated Assessment of Potential Confounding
* Exercise: Connecting Conceptual and Statistical Assessment of
Confounding
* 7. Selection Bias and Confounding Resulting from Selection in Cohort
Studies
* Synopsis
* Learning Objectives
* Study Designs
* Definition and Examples of Selection Bias
* Selection Bias Versus Confounding
* Evaluation of Bias in Cohort Studies
* Compare Those Included to Those Not Included
* Compare Disease Rates Among Unexposed to External Populations Assess
Whether Expected Patterns of Disease are Present
* Assess Pattern of Results in Relation to Markers of Susceptibility to
Bias Due to Participant Selection
* Assess Rates for Diseases Known Not to Be Affected by the Exposure
* Integrated Assessment of Potential for Bias in Cohort Studies
* Exercise: Assessment of Bias Due to Selection in Cohort Studies
* 8. Selection Bias in Case-Control Studies
* Synopsis
* Learning Objectives
* Control Selection
* Participant Selection in Case-Control and Cohort Studies
* Selection of Controls from the Source Population
* Coherence of Cases and Controls
* Evaluation of Selection Bias in Case-Control Studies
* Temporal Coherence of Cases and Controls
* Discretionary Health Care of Cases and Controls
* Compare Exposure Prevalence in Controls to an External Population
* Determine Whether Exposure Prevalence Varies as Expected Among
Controls
* Examine Markers of Potential Selection Bias in Relation to Measures
of Association
* Adjust Measures of Association for Known Sources of Non-
Comparability
* Determine Whether Established Associations Can Be Confirmed
* Integrated Assessment of Potential for Selection Bias in Case-Control
Studies
* Exercise: Assessing Selection Bias in Case-Control Studies
* 9. Bias Due to Loss of Study Participants
* Synopsis
* Learning Objectives
* Conceptual Framework for Examining Bias Due to Loss of Study
Participants
* Evaluation of Bias Due to Loss of Study Participants
* Characterize Nonparticipants
* Consider Gradient of Difficulty in Recruitment
* Stratify Study Base by Markers of Participation
* Impute Information for Nonparticipants
* Integrated Assessment of Potential for Bias Due to Loss of Study
Participants
* Exercise: Examining Implications of Non-Participation
* 10. Measurement and Classification of Exposure
* Synopsis
* Learning Objectives
* Introduction
* Ideal Versus Operational Measures of Exposure
* Biologically Relevant Exposure
* Temporally Relevant Exposure
* Optimal Level of Exposure Aggregation
* Comparison of Optimal to Operational Measures of Exposure
* Does Exposure Misclassification Differ by Disease Status?
* Definitions
* Mechanisms of Differential Exposure Misclassification
* Evaluation of Exposure Misclassification
* Compare Routine Measure to Superior Measures
* Examine Multiple Indicators of Exposure
* Examine Subsets of the Population with Differing Exposure Data
Quality
* Evaluate Known Predictors of Exposure
* Evaluate Known Consequences of Exposure
* Examine Dose-Response Gradients
* Evaluate Whether Exposure Misclassification Differs by Disease Status
* Identification of Subgroups with Nondifferential Exposure
Misclassification
* Integrated Assessment of Bias Due to Exposure Misclassification
* Exercise: Assessing the Presence and Impact of Exposure
* Misclassification
* 11. Measurement and Classification of Disease
* Synopsis
* Learning Objectives
* Framework for Evaluating Disease Misclassification
* Sources of Disease Misclassification
* Impact of Differential and Nondifferential Disease Misclassification
* Evaluation of Disease Misclassification
* Verify Diagnostic Accuracy for Subset of Study Participants
* Examine Results Across Levels of Diagnostic Certainty
* Evaluate Alternate Methods of Disease Grouping
* Determine Whether Misclassification is Differential by Exposure
Status
* Create Subgroups with Accurate Ascertainment or Non-Differential
* Underascertainment
* Restrict Inference to Disease Outcome That Can Be Ascertained
Accurately
* Integrated Assessment of Potential for Bias Due to Disease
Misclassification
* Exercise: Assessing the Presence and Impact of Disease
Misclassification
* 12. Random Error
* Synopsis
* Learning Objectives
* Nature of Random Variation
* Sequential Approach to Considering Random and Systematic Error
* Special Considerations in Evaluating Random Error in Observational
Studies
* Statistical Significance Testing
* Interpretation of Confidence Intervals
* Multiple Comparisons and Related Issues
* Integrated Assessment of Random Error
* Exercise: Assessing Random Error
* 13. Integration of Evidence Across Studies
* Synopsis
* Learning Objectives
* Introduction
* Systematic Evidence Reviews
* Data Pooling and Comparative Analyses
* Meta-Analysis
* Interpreting Consistency and Inconsistency Among Studies
* Inconsistent Findings
* Consistent Findings
* Evolution of Epidemiologic Research
* Integrated Assessment from Combining Evidence Across Studies
* Exercise: Interpreting Evidence from a Collection of Studies
* 14. Characterization and Communication of Conclusions
* Synopsis
* Learning Objectives
* Presenting Clear, Objective, and Informed Conclusions
* Applications of Epidemiology
* Integration of Epidemiologic Evidence with Other Information
* Identification of Key Concerns
* Controversy over Interpretation
* The Case Against Algorithms for Interpreting Epidemiologic Evidence
* Exercise: Communicating Summary Assessment of Epidemiologic Evidence