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All (5) ((5 results))

  • 1. Total error in the dual system estimator: The 1986 Census of Central Los Angeles County Archived
    Articles and reports: 12-001-X198800214589
    Description:

    The U.S. Bureau of the Census uses dual system estimates (DSEs) for measuring census coverage error. The dual system estimate uses data from the original enumeration and a Post Enumeration Survey. In measuring the accuracy of the DSE, it is important to know that the DSE is subject to several components of nonsampling error, as well as sampling error. This paper gives models of the total error and the components of error in the dual system estimates. The models relate observed indicators of data quality, such as a matching error rate, to the first two moments of the components of error. The propagation of error in the DSE is studied and its bias and variance are assessed. The methodology is applied to the 1986 Census of Central Los Angeles County in the Census Bureau’s Test of Adjustment Related Operations. The methodology also will be useful to assess error in the DSE for the 1990 census as well as other applications.

    Release date: 1988-12-15
  • 2. Imputation strategies for missing values in post-enumeration surveys Archived
    Articles and reports: 12-001-X198800214591
    Description:

    To estimate census undercount, a post-enumeration survey (PES) is taken, and an attempt is made to find a matching census record for each individual in the PES; the rate of successful matching provides an estimate of census coverage. Undercount estimation is performed within poststrata defined by geographic, demographic, and housing characteristics, X. Portions of X are missing for some individuals due to survey nonresponse; moreover, a match status Y cannot be determined for all individuals. A procedure is needed for imputing the missing values of X and Y. This paper reviews the imputation methods used in the 1986 Test of Adjustment Related Operations (Schenker 1988) and proposes two alternative model-based methods: (1) a maximum-likelihood contingency-table estimation procedure that ignores the missing-data mechanism; and (2) a new Bayesian contingency table estimation procedure that does not ignore the missing-data mechanism. The first method is computationally simpler, but the second is preferred on conceptual and scientific grounds.

    Release date: 1988-12-15
  • 3. Adjusting the 1986 Australian Census count for under-enumeration Archived
    Articles and reports: 12-001-X198800214593
    Description:

    In Australia, population estimates have been obtained from census counts, incorporating an adjustment for under-enumeration in 1976, 1981 and 1986. The adjustments are based on the results of a Post Enumeration Survey and demographic analysis. This paper describes the methods used and the results obtained in adjusting the 1986 census. The formal use of sex ratios as suggested by Wolter (1986) is examined as a possible improvement of the less formal use made of these ratios in adjusting census counts.

    Release date: 1988-12-15
  • 4. Handling missing data in coverage estimation, with application to the 1986 Test of Adjustment Related Operations Archived
    Articles and reports: 12-001-X198800114598
    Description:

    This paper discusses methods used to handle missing data in post-enumeration surveys for estimating census coverage error, as illustrated for the 1986 Test of Adjustment Related Operations (Diffendal 1988). The methods include imputation schemes based on hot-deck and logistic regression models as well as weighting adjustments. The sensitivity of undercount estimates from the 1986 test to variations in the imputation models is also explored.

    Release date: 1988-06-15
  • 5. Personal computer variance software for complex surveys Archived
    Articles and reports: 12-001-X198800114600
    Description:

    A personal computer program for variance estimation with large scale surveys is described. The program, called PC CARP, will compute estimates and estimated variances for totals, ratios, means, quantiles, and regression coefficients.

    Release date: 1988-06-15
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Articles and reports (5)

Articles and reports (5) ((5 results))

  • 1. Total error in the dual system estimator: The 1986 Census of Central Los Angeles County Archived
    Articles and reports: 12-001-X198800214589
    Description:

    The U.S. Bureau of the Census uses dual system estimates (DSEs) for measuring census coverage error. The dual system estimate uses data from the original enumeration and a Post Enumeration Survey. In measuring the accuracy of the DSE, it is important to know that the DSE is subject to several components of nonsampling error, as well as sampling error. This paper gives models of the total error and the components of error in the dual system estimates. The models relate observed indicators of data quality, such as a matching error rate, to the first two moments of the components of error. The propagation of error in the DSE is studied and its bias and variance are assessed. The methodology is applied to the 1986 Census of Central Los Angeles County in the Census Bureau’s Test of Adjustment Related Operations. The methodology also will be useful to assess error in the DSE for the 1990 census as well as other applications.

    Release date: 1988-12-15
  • 2. Imputation strategies for missing values in post-enumeration surveys Archived
    Articles and reports: 12-001-X198800214591
    Description:

    To estimate census undercount, a post-enumeration survey (PES) is taken, and an attempt is made to find a matching census record for each individual in the PES; the rate of successful matching provides an estimate of census coverage. Undercount estimation is performed within poststrata defined by geographic, demographic, and housing characteristics, X. Portions of X are missing for some individuals due to survey nonresponse; moreover, a match status Y cannot be determined for all individuals. A procedure is needed for imputing the missing values of X and Y. This paper reviews the imputation methods used in the 1986 Test of Adjustment Related Operations (Schenker 1988) and proposes two alternative model-based methods: (1) a maximum-likelihood contingency-table estimation procedure that ignores the missing-data mechanism; and (2) a new Bayesian contingency table estimation procedure that does not ignore the missing-data mechanism. The first method is computationally simpler, but the second is preferred on conceptual and scientific grounds.

    Release date: 1988-12-15
  • 3. Adjusting the 1986 Australian Census count for under-enumeration Archived
    Articles and reports: 12-001-X198800214593
    Description:

    In Australia, population estimates have been obtained from census counts, incorporating an adjustment for under-enumeration in 1976, 1981 and 1986. The adjustments are based on the results of a Post Enumeration Survey and demographic analysis. This paper describes the methods used and the results obtained in adjusting the 1986 census. The formal use of sex ratios as suggested by Wolter (1986) is examined as a possible improvement of the less formal use made of these ratios in adjusting census counts.

    Release date: 1988-12-15
  • 4. Handling missing data in coverage estimation, with application to the 1986 Test of Adjustment Related Operations Archived
    Articles and reports: 12-001-X198800114598
    Description:

    This paper discusses methods used to handle missing data in post-enumeration surveys for estimating census coverage error, as illustrated for the 1986 Test of Adjustment Related Operations (Diffendal 1988). The methods include imputation schemes based on hot-deck and logistic regression models as well as weighting adjustments. The sensitivity of undercount estimates from the 1986 test to variations in the imputation models is also explored.

    Release date: 1988-06-15
  • 5. Personal computer variance software for complex surveys Archived
    Articles and reports: 12-001-X198800114600
    Description:

    A personal computer program for variance estimation with large scale surveys is described. The program, called PC CARP, will compute estimates and estimated variances for totals, ratios, means, quantiles, and regression coefficients.

    Release date: 1988-06-15
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