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[A measure to evaluate estimates from the population census].

J C Pinheiro, J M De Lima

    Revista Brasileira De Estatistica
    |January 1, 1990
    PubMed
    Summary

    Reducing sampling fractions in surveys can decrease estimate precision. This study quantifies efficiency loss and determines necessary sampling fractions to maintain desired precision levels for survey characteristics.

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    Area of Science:

    • Statistics
    • Survey Methodology
    • Demography

    Background:

    • Precision of survey estimates is crucial for reliable data analysis.
    • Reducing sampling fractions can lead to significant efficiency loss in statistical estimates.
    • Understanding the trade-offs between sampling fraction and estimate precision is vital for survey design.

    Purpose of the Study:

    • To describe a method for measuring efficiency loss due to reduced sampling fractions.
    • To study the sampling fractions required to ensure a specific precision level for characteristic estimates.
    • To apply the proposed methodology using Brazilian census data.

    Main Methods:

    • Developing a measure for efficiency loss in survey estimates.
    • Analyzing the relationship between sampling fractions and estimate precision.
    Keywords:
    AmericasBrazilCensusComparative StudiesDeveloping CountriesError SourcesEstimation TechnicsFamily And HouseholdHouseholdsLatin AmericaMeasurementMethodological StudiesPopulation StatisticsResearch MethodologySampling ErrorsSampling StudiesSouth AmericaStudies

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  • Case study application using the 1980 and 1990 Brazilian Censuses.

    • Main Results:

    • Quantification of efficiency loss associated with decreasing sampling fractions.
    • Identification of optimal sampling fractions to achieve target precision levels.
    • Demonstration of the methodology's applicability in a real-world census context.

    Conclusions:

    • The proposed measure effectively quantifies efficiency loss in survey estimates.
    • Methodology provides guidance on selecting appropriate sampling fractions for desired precision.
    • The application highlights practical implications for census data estimation and planning.