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Assessment of Child Anthropometry in a Large Epidemiologic Study
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Calibration Weighting Methods for the National Center for Health Statistics Research and Development Survey.

Katherine E Irimata, Yulei He, Van L Parsons

    Vital and Health Statistics. Series 2, Data Evaluation and Methods Research
    |March 20, 2023
    PubMed
    Summary

    The National Center for Health Statistics uses calibration weighting to improve data accuracy from web-based Research and Development Surveys (RANDS). This method addresses potential biases in commercial panel data, enhancing survey estimation reliability.

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    Area of Science:

    • Health Statistics
    • Survey Methodology
    • Data Science

    Background:

    • The National Center for Health Statistics (NCHS) conducts the Research and Development Survey (RANDS) using web-based commercial panels since 2015.
    • Web surveys face limitations like coverage and nonresponse bias, impacting data accuracy.

    Purpose of the Study:

    • To explore methods for integrating commercial survey panel data with high-quality collections.
    • To improve survey estimation by addressing limitations of web surveys.
    • To detail calibration weighting methods used at NCHS.

    Main Methods:

    • Investigated various calibration weighting methods.
    • Utilized the National Health Interview Survey (a national household survey) to adjust RANDS panel weights.
    • Described approaches for calibrating weights in NCHS web-based panel surveys.

    Main Results:

    • Calibration weighting methods were investigated to adjust RANDS panel weights.
    • The National Health Interview Survey was used as a benchmark for calibration.
    • Approaches for weight calibration in web-based panel surveys were described.

    Conclusions:

    • Calibration weighting is a key method to address biases in web-based commercial panel surveys.
    • Integrating data and employing robust weighting techniques can improve survey estimation.
    • NCHS continues to develop and refine methods for high-quality health statistics from diverse data sources.