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  • 1. Methods for estimating the precision of survey estimates when imputation has been used Archived
    Articles and reports: 12-001-X199200214483
    Description:

    In almost all large surveys, some form of imputation is used. This paper develops a method for variance estimation when single (as opposed to multiple) imputation is used to create a completed data set. Imputation will never reproduce the true values (except in truly exceptional cases). The total error of the survey estimate is viewed in this paper as the sum of sampling error and imputation error. Consequently, an overall variance is derived as the sum of a sampling variance and an imputation variance. The principal theme is the estimation of these two components, using the data after imputation, that is, the actually observed values and the imputed values. The approach is model assisted in the sense that the model implied by the imputation method and the randomization distribution used for sample selection will together determine the appearance of the variance estimators. The theoretical findings are confirmed by a Monte Carlo simulation.

    Release date: 1992-12-15
  • 2. A variation of the housing unit method for estimating the population of small, rural areas: A case study of the local expert procedure Archived
    Articles and reports: 12-001-X199200114493
    Description:

    This paper examines the suitability of a survey-based procedure for estimating populations in small, rural areas. The procedure is a variation of the Housing Unit Method. It employs the use of local experts enlisted to provide information about the demographic characteristics of households randomly selected from residential unit sample frames developed from utility records. The procedure is nonintrusive and less costly than traditional survey data collection efforts. Because the procedure is based on random sampling, confidence intervals can be constructed around the population estimated by the technique. The results of a case study are provided in which the total population is estimated for three unincorporated communities in rural, southern Nevada.

    Release date: 1992-06-15
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Articles and reports (2)

Articles and reports (2) ((2 results))

  • 1. Methods for estimating the precision of survey estimates when imputation has been used Archived
    Articles and reports: 12-001-X199200214483
    Description:

    In almost all large surveys, some form of imputation is used. This paper develops a method for variance estimation when single (as opposed to multiple) imputation is used to create a completed data set. Imputation will never reproduce the true values (except in truly exceptional cases). The total error of the survey estimate is viewed in this paper as the sum of sampling error and imputation error. Consequently, an overall variance is derived as the sum of a sampling variance and an imputation variance. The principal theme is the estimation of these two components, using the data after imputation, that is, the actually observed values and the imputed values. The approach is model assisted in the sense that the model implied by the imputation method and the randomization distribution used for sample selection will together determine the appearance of the variance estimators. The theoretical findings are confirmed by a Monte Carlo simulation.

    Release date: 1992-12-15
  • 2. A variation of the housing unit method for estimating the population of small, rural areas: A case study of the local expert procedure Archived
    Articles and reports: 12-001-X199200114493
    Description:

    This paper examines the suitability of a survey-based procedure for estimating populations in small, rural areas. The procedure is a variation of the Housing Unit Method. It employs the use of local experts enlisted to provide information about the demographic characteristics of households randomly selected from residential unit sample frames developed from utility records. The procedure is nonintrusive and less costly than traditional survey data collection efforts. Because the procedure is based on random sampling, confidence intervals can be constructed around the population estimated by the technique. The results of a case study are provided in which the total population is estimated for three unincorporated communities in rural, southern Nevada.

    Release date: 1992-06-15
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