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  • 1. Weighting sample data subject to independent controls Archived
    Articles and reports: 12-001-X20040016992
    Description:

    In the U.S. Census of Population and Housing, a sample of about one-in-six of the households receives a longer version of the census questionnaire called the long form. All others receive a version called the short form. Raking, using selected control totals from the short form, has been used to create two sets of weights for long form estimation; one for individuals and one for households. We describe a weight construction method based on quadratic programming that produces household weights such that the weighted sum for individual characteristics and for household characteristics agree closely with selected short form totals. The method is broadly applicable to situations where weights are to be constructed to meet both size bounds and sum-to-control restrictions. Application to the situation where the controls are estimates with an estimated covariance matrix is described.

    Release date: 2004-07-14
  • 2. Estimation of census adjustment factors Archived
    Articles and reports: 12-001-X20000015176
    Description:

    A components-of-variance approach and an estimated covariance error structure were used in constructing predictors of adjustment factors for the 1990 Decennial Census. The variability of the estimated covariance matrix is the suspected cause of certain anomalies that appeared in the regression estimation and in the estimated adjustment factors. We investigate alternative prediction methods and propose a procedure that is less influenced by variability in the estimated covariance matrix. The proposed methodology is applied to a data set composed of 336 adjustment factors from the 1990 Post Enumeration Survey.

    Release date: 2000-08-30
  • 3. Hierarchical and empirical Bayes methods for adjustment of census undercount: The 1988 Missouri dress rehearsal data Archived
    Articles and reports: 12-001-X199200114497
    Description:

    The present article discusses a model-based approach towards adjustment of the 1988 Census Dress Rehearsal Data collected from test sites in Missouri. The primary objective is to develop procedures that can be used to model data from the 1990 Census Post Enumeration Survey in April, 1991 and smooth survey-based estimates of the adjustment factors. We have proposed in this paper hierarchical Bayes (HB) and empirical Bayes (EB) procedures which meet this objective. The resulting estimators seem to improve consistently on the estimators of the adjustment factors based on dual system estimation (DSE) as well as the smoothed regression estimators.

    Release date: 1992-06-15
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Articles and reports (3)

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

  • 1. Weighting sample data subject to independent controls Archived
    Articles and reports: 12-001-X20040016992
    Description:

    In the U.S. Census of Population and Housing, a sample of about one-in-six of the households receives a longer version of the census questionnaire called the long form. All others receive a version called the short form. Raking, using selected control totals from the short form, has been used to create two sets of weights for long form estimation; one for individuals and one for households. We describe a weight construction method based on quadratic programming that produces household weights such that the weighted sum for individual characteristics and for household characteristics agree closely with selected short form totals. The method is broadly applicable to situations where weights are to be constructed to meet both size bounds and sum-to-control restrictions. Application to the situation where the controls are estimates with an estimated covariance matrix is described.

    Release date: 2004-07-14
  • 2. Estimation of census adjustment factors Archived
    Articles and reports: 12-001-X20000015176
    Description:

    A components-of-variance approach and an estimated covariance error structure were used in constructing predictors of adjustment factors for the 1990 Decennial Census. The variability of the estimated covariance matrix is the suspected cause of certain anomalies that appeared in the regression estimation and in the estimated adjustment factors. We investigate alternative prediction methods and propose a procedure that is less influenced by variability in the estimated covariance matrix. The proposed methodology is applied to a data set composed of 336 adjustment factors from the 1990 Post Enumeration Survey.

    Release date: 2000-08-30
  • 3. Hierarchical and empirical Bayes methods for adjustment of census undercount: The 1988 Missouri dress rehearsal data Archived
    Articles and reports: 12-001-X199200114497
    Description:

    The present article discusses a model-based approach towards adjustment of the 1988 Census Dress Rehearsal Data collected from test sites in Missouri. The primary objective is to develop procedures that can be used to model data from the 1990 Census Post Enumeration Survey in April, 1991 and smooth survey-based estimates of the adjustment factors. We have proposed in this paper hierarchical Bayes (HB) and empirical Bayes (EB) procedures which meet this objective. The resulting estimators seem to improve consistently on the estimators of the adjustment factors based on dual system estimation (DSE) as well as the smoothed regression estimators.

    Release date: 1992-06-15
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