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Related Experiment Videos

Correlation bias in U.S. census adjustment.

K W Wachter1, D A Freedman

  • 1Department of Demography, University of California, Berkeley, USA.

Evaluation Review
|June 10, 2000
PubMed
Summary
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Correlation bias, where individuals are missed in both census counts and adjustments, affects millions. This study estimates 3 million doubly-missing people in the 1990 U.S. census, highlighting a significant issue for future census adjustments.

Area of Science:

  • Demography
  • Statistical methodology
  • Social statistics

Background:

  • Census adjustments aim to correct for undercounts but can introduce new errors.
  • Correlation bias occurs when individuals missed in the census are also missed in adjustment processes.
  • This bias affects the accuracy of demographic data and population estimates.

Purpose of the Study:

  • To develop a method for estimating the national number of "doubly-missing" individuals.
  • To determine the distribution of these individuals by race and sex.
  • To assess the impact of correlation bias on U.S. census adjustments.

Main Methods:

  • The study presents a novel statistical method for quantifying correlation bias.
  • The method was applied to data from the 1990 U.S. census.

Related Experiment Videos

  • Estimation of the doubly-missing population by race and sex was performed.

    • Main Results:

    • An estimated 3 million people were "doubly-missing" in the 1990 U.S. census adjustment.
    • The distribution of these individuals across different racial groups and sexes was estimated.
    • Correlation bias was identified as a substantial source of error.

    Conclusions:

    • Correlation bias poses a significant challenge to the accuracy of census adjustments.
    • The developed methodology is effective for measuring the magnitude of correlation bias.
    • Accurate census data is crucial for demographic research and policy-making, underscoring the need to address such biases.