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  • Many important statistics are known from official records for the entire population, but have to be estimated for subpopulations. I describe two simple data combination methods that reduce the substantial sampling error of the commonly used direct survey estimates for small subpopulations. The first estimator incorporates information from repeated cross-sections, while the second estimator uses the knowledge of the statistic for the overall population to improve accuracy of the estimates for subpopulations. To evaluate the estimators, I compare the estimated number of female and elderly recipients of a government transfer program by county to the "true" number from administrative data on all recipients in New York. I find that even the simple estimators substantially improve survey error. Incorporating the statistic of interest for the overall population yields particularly large error reductions and can reduce non-sampling error. (xsd:string)
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?:dateModified
  • 2018 (xsd:gyear)
?:datePublished
  • 2018 (xsd:gyear)
?:doi
  • srm/2018.v12i3.7309 ()
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  • en (xsd:string)
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?:issn
  • 1864-3361 ()
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  • 3 (xsd:string)
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  • Two Simple Methods to Improve Official Statistics for Small Subpopulations (xsd:string)
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  • Zeitschriftenartikel (xsd:string)
  • journal_article (en)
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  • GESIS-SSOAR (xsd:string)
  • In: Survey Research Methods, 12, 2018, 3, 181-192 (xsd:string)
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  • 12 (xsd:string)