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Related Experiment Videos

Combining census, dual-system, and evaluation study data to estimate population shares.

A M Zaslavsky

    Journal of the American Statistical Association
    |September 1, 1993
    PubMed
    Summary

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    This study introduces methods to combine U.S. census data, dual system estimates (DSE), and bias estimates for more accurate population counts. Combining these sources improves population share estimations by balancing bias and variability.

    Area of Science:

    • Demography
    • Statistical Science
    • Survey Methodology

    Background:

    • The 1990 U.S. census and Post-Enumeration Survey (PES) generated census counts and dual system estimates (DSE) for population domains.
    • Bias estimates for the DSE were derived from PES evaluation programs.
    • Each data source (unadjusted census, DSE, bias estimates) presents trade-offs between variability and bias.

    Purpose of the Study:

    • To develop and evaluate methods for optimally combining census data, DSE, and bias estimates.
    • To produce accurate population share estimates by minimizing weighted squared- or absolute-error loss functions.
    • To address the challenges of integrating multiple data sources with differing statistical properties.

    Main Methods:

    • Utilized census counts and DSE from the 1990 U.S. census and PES.
    Keywords:
    AmericasBiasCensusCensus MethodsData AdjustmentData CollectionDeveloped CountriesDual Data CollectionError SourcesEstimation TechnicsEvaluationMeasurementMethodological StudiesNorth AmericaNorthern AmericaPopulation StatisticsResearch MethodologySampling StudiesStudiesSurveysUnited States

    Related Experiment Videos

  • Incorporated bias estimates derived from PES evaluation programs.
  • Applied weighted squared- or absolute-error loss functions to combine estimates and assess accuracy.

    • Main Results:

    • Demonstrated methods for integrating diverse population data sources.
    • Showcased the potential for improved accuracy in population share estimation.
    • Provided a framework for balancing bias and variability in demographic estimates.

    Conclusions:

    • Combining census, DSE, and bias estimates offers a robust approach to population estimation.
    • The proposed methods enhance the accuracy of population share calculations.
    • This research contributes to more reliable demographic data through integrated statistical techniques.