Analysis

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• 1. A Model-based Disaggregation Method for Estimation of Adult Competency Archived

  Articles and reports: 11-522-X202200100003

  Description: Estimation at fine levels of aggregation is necessary to better describe society. Small area estimation model-based approaches that combine sparse survey data with rich data from auxiliary sources have been proven useful to improve the reliability of estimates for small domains. Considered here is a scenario where small area model-based estimates, produced at a given aggregation level, needed to be disaggregated to better describe the social structure at finer levels. For this scenario, an allocation method was developed to implement the disaggregation, overcoming challenges associated with data availability and model development at such fine levels. The method is applied to adult literacy and numeracy estimation at the county-by-group-level, using data from the U.S. Program for the International Assessment of Adult Competencies. In this application the groups are defined in terms of age or education, but the method could be applied to estimation of other equity-deserving groups.

  Release date: 2024-03-25

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• 2. A case study in using model-assisted estimation to integrate survey and administrative data Archived

  Articles and reports: 11-522-X200600110403

  Description:

  This paper reports research to introduce model-assisted estimation into the American Community Survey (ACS), a large-scale ongoing survey intended to replace the long-form sample in the U.S. decennial censuses. The proposed application integrates information from administrative records into ACS estimation. The approach to model-assisted estimation restricts the use of the administrative records to adjustments to the survey weights, while retaining the data on characteristics reported by respondents in the ACS. Although the ACS is a general-purpose survey not specifically tied to health, this case study may suggest possible methodological applications in areas of health statistics.

  Release date: 2008-03-17

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• 3. Application of linear and log-linear models to data from complex samples Archived

  Articles and reports: 12-001-X198400114351

  Description:

  Most sample surveys conducted by organizations such as Statistics Canada or the U.S. Bureau of the Census employ complex designs. The design-based approach to statistical inference, typically the institutional standard of inference for simple population statistics such as means and totals, may be extended to parameters of analytic models as well. Most of this paper focuses on application of design-based inferences to such models, but rationales are offered for use of model-based alternatives in some instances, by way of explanation for the author’s observation that both modes of inference are used in practice at his own institution.

  Within the design-based approach to inference, the paper briefly describes experience with linear regression analysis. Recently, variance computations for a number of surveys of the Census Bureau have been implemented through “replicate weighting”; the principal application has been for variances of simple statistics, but this technique also facilitates variance computation for virtually any complex analytic model. Finally, approaches and experience with log-linear models are reported.

  Release date: 1984-06-15

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Articles and reports (3) ((3 results))

• 1. A Model-based Disaggregation Method for Estimation of Adult Competency Archived

  Articles and reports: 11-522-X202200100003

  Description: Estimation at fine levels of aggregation is necessary to better describe society. Small area estimation model-based approaches that combine sparse survey data with rich data from auxiliary sources have been proven useful to improve the reliability of estimates for small domains. Considered here is a scenario where small area model-based estimates, produced at a given aggregation level, needed to be disaggregated to better describe the social structure at finer levels. For this scenario, an allocation method was developed to implement the disaggregation, overcoming challenges associated with data availability and model development at such fine levels. The method is applied to adult literacy and numeracy estimation at the county-by-group-level, using data from the U.S. Program for the International Assessment of Adult Competencies. In this application the groups are defined in terms of age or education, but the method could be applied to estimation of other equity-deserving groups.

  Release date: 2024-03-25

  ---

• 2. A case study in using model-assisted estimation to integrate survey and administrative data Archived

  Articles and reports: 11-522-X200600110403

  Description:

  This paper reports research to introduce model-assisted estimation into the American Community Survey (ACS), a large-scale ongoing survey intended to replace the long-form sample in the U.S. decennial censuses. The proposed application integrates information from administrative records into ACS estimation. The approach to model-assisted estimation restricts the use of the administrative records to adjustments to the survey weights, while retaining the data on characteristics reported by respondents in the ACS. Although the ACS is a general-purpose survey not specifically tied to health, this case study may suggest possible methodological applications in areas of health statistics.

  Release date: 2008-03-17

  ---

• 3. Application of linear and log-linear models to data from complex samples Archived

  Articles and reports: 12-001-X198400114351

  Description:

  Most sample surveys conducted by organizations such as Statistics Canada or the U.S. Bureau of the Census employ complex designs. The design-based approach to statistical inference, typically the institutional standard of inference for simple population statistics such as means and totals, may be extended to parameters of analytic models as well. Most of this paper focuses on application of design-based inferences to such models, but rationales are offered for use of model-based alternatives in some instances, by way of explanation for the author’s observation that both modes of inference are used in practice at his own institution.

  Within the design-based approach to inference, the paper briefly describes experience with linear regression analysis. Recently, variance computations for a number of surveys of the Census Bureau have been implemented through “replicate weighting”; the principal application has been for variances of simple statistics, but this technique also facilitates variance computation for virtually any complex analytic model. Finally, approaches and experience with log-linear models are reported.

  Release date: 1984-06-15

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