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  • 1. Multiple imputation with census data Archived
    Articles and reports: 12-001-X201200211759
    Description:

    A benefit of multiple imputation is that it allows users to make valid inferences using standard methods with simple combining rules. Existing combining rules for multivariate hypothesis tests fail when the sampling error is zero. This paper proposes modified tests for use with finite population analyses of multiply imputed census data for the applications of disclosure limitation and missing data and evaluates their frequentist properties through simulation.

    Release date: 2012-12-19
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  • 1. Multiple imputation with census data Archived
    Articles and reports: 12-001-X201200211759
    Description:

    A benefit of multiple imputation is that it allows users to make valid inferences using standard methods with simple combining rules. Existing combining rules for multivariate hypothesis tests fail when the sampling error is zero. This paper proposes modified tests for use with finite population analyses of multiply imputed census data for the applications of disclosure limitation and missing data and evaluates their frequentist properties through simulation.

    Release date: 2012-12-19
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