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Some coverage error models for census data.

K M Wolter

    Journal of the American Statistical Association
    |June 1, 1986
    PubMed
    Summary
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    New models address coverage error in human population surveys and censuses, drawing from capture-recapture and dual-system methods. This research offers estimation techniques and distinguishes between sampling error and model error.

    Area of Science:

    • Statistics
    • Demography
    • Survey Methodology

    Background:

    • Coverage error is a significant challenge in human population surveys and censuses.
    • Existing methods often rely on assumptions that may not fully capture the complexities of coverage error.
    • Understanding and quantifying coverage error is crucial for accurate demographic estimates.

    Purpose of the Study:

    • To present alternative statistical models for representing coverage error in surveys and censuses.
    • To explore the relationship between these models and established methods like capture-recapture and dual-system models.
    • To discuss estimation methodologies for one of the proposed coverage error models.

    Main Methods:

    • Development of alternative models for coverage error.
    Keywords:
    AmericasCensusData CollectionDeveloped CountriesDeveloping CountriesDual Data CollectionError SourcesMeasurementMethodological StudiesNorth AmericaNorthern AmericaPopulation StatisticsResearch MethodologySampling StudiesStudiesSurveysUndercountUnited States

    Related Experiment Videos

  • Relating these models to capture-recapture (wildlife) and dual-system (vital events) models.
  • Discussion of estimation methodologies for a chosen coverage error model.

    • Main Results:

    • The study introduces novel models for coverage error in population studies.
    • It demonstrates the connection between these models and existing statistical frameworks.
    • An example using 1980 U.S. census data illustrates the application of the methodology.

    Conclusions:

    • The proposed models offer a new perspective on understanding and quantifying coverage error.
    • Distinctions are made between sampling error and model-associated error.
    • The research provides a foundation for adjusting census and survey data to correct for coverage error.