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Improving accuracy in multiple regression estimates of population using principles from causal modelling

D A Swanson

    Demography
    |November 1, 1980
    PubMed
    Summary

    This study introduces a novel method to enhance population estimation accuracy by adjusting regression coefficients. The technique accounts for changing variable relationships, improving post-censal estimates.

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    Area of Science:

    • Demography
    • Statistical Modeling

    Background:

    • Accurate post-censal population estimation is crucial for resource allocation and policy.
    • Traditional methods like the ratio-correlation method can be affected by temporal changes in variable relationships.
    • Improving the accuracy of population estimates requires addressing these dynamic structural changes.

    Purpose of the Study:

    • To develop and evaluate a procedure for modifying regression coefficients to enhance the accuracy of the ratio-correlation method for population estimation.
    • To incorporate theoretical causal ordering and path analysis principles to account for temporal shifts in variable relationships.
    • To provide a conservative modification approach based on rank-ordering for improved estimation.

    Main Methods:

    • A mildly restricted procedure was developed using theoretical causal ordering and path analysis.

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  • Regression coefficients were modified to account for temporal changes in variable relationships.
  • The modification approach utilized rank-ordering for conservative adjustments.

    • Main Results:

    • Empirical results demonstrated increased accuracy in population estimation using the proposed procedure.
    • The method effectively addressed temporal changes in the structure of variable relationships.
    • The modified ratio-correlation method showed improved performance in Washington state counties.

    Conclusions:

    • The proposed procedure offers a statistically sound method for improving population estimation accuracy.
    • Accounting for temporal dynamics in variable relationships is essential for reliable post-censal estimates.
    • The rank-ordering based modification provides a robust approach to enhance demographic estimation techniques.