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The problem of multiple inference in identifying point-source environmental hazards.

D C Thomas

    Environmental Health Perspectives
    |October 1, 1985
    PubMed
    Summary

    Investigating disease clusters requires statistical methods to avoid false positives from multiple comparisons. Empirical Bayes procedures offer a robust approach for prioritizing and confirming environmental hazard-disease associations.

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    Area of Science:

    • Environmental epidemiology
    • Biostatistics
    • Public health

    Background:

    • Identifying point-source environmental hazards often involves detecting unusual disease clusters.
    • The statistical challenge of "multiple inference" increases the risk of false-positive associations when examining numerous clusters.
    • Distinguishing between anecdotal and systematic cluster identification is crucial.

    Purpose of the Study:

    • To propose statistical methods for analyzing disease clusters and environmental hazards.
    • To address the problem of multiple inference in cluster detection.
    • To provide a framework for prioritizing and confirming exposure-disease associations.

    Main Methods:

    • Distinction between anecdotal and systematic cluster identification.
    • Application of empirical Bayes procedures for ranking clusters when exposure data is unavailable.
    • Utilizing empirical Bayes for selecting and ranking associations when exposure data is systematically available.
    • Procedures for global null hypothesis testing and estimating true-positive associations.

    Main Results:

    • Empirical Bayes procedures provide a basis for prioritizing clusters for investigation, even without systematic exposure data.
    • These methods facilitate the selection and ranking of exposure-disease associations for confirmation.
    • The study outlines methods for testing overall associations and estimating the number of true findings.

    Conclusions:

    • Empirical Bayes methods are recommended over classical frequentist approaches for analyzing disease clusters and environmental exposures.
    • These statistical strategies help mitigate the risks associated with multiple inference in epidemiological studies.
    • The proposed methods enhance the reliability of identifying true environmental hazard-disease links.

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