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?:abstract
  • The joint usage of unit- and area-level data for model-based small area estimation is investigated. The combination of levels within a single model encloses a variety of methodological problems. Firstly, it implies a critical decrease in degrees of freedom due to more model parameters that need to be estimated. This may destabilize model predictions in the presence of small samples. Secondly, unit- and area-level data has different distributional characteristics in terms of dispersion patterns and correlation structure. Thirdly, unit- and area-level data is usually subject to different kinds of measurement errors. We propose a multi-level model with level-specific penalization to overcome these issues and use unit- and area-level data jointly for model-based small area estimation. An application is provided on the example of regional health measurement in Germany. We combine health survey data on the unit-level and aggregated micro census records on the area-level to estimate hypertension prevalence. (xsd:string)
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?:comment
  • (Mikrozensus) (xsd:string)
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  • Mikrozensus-Bibliography (xsd:string)
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  • 2019 (xsd:gyear)
?:datePublished
  • 2019 (xsd:gyear)
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  • 21 (xsd:string)
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  • english (xsd:string)
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  • 5/19 (xsd:string)
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  • Penalized small area models for the combination of unit- and area-level data (xsd:string)
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  • techreport (xsd:string)
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  • (5/19), 21, 2019 (xsd:string)
  • Bibsonomy (xsd:string)
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  • Mikrozensus (MZ) (xsd:string)
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  • 2019 (xsd:string)
  • FDZ_GML (xsd:string)
  • MZ_input2020 (xsd:string)
  • MZ_pro (xsd:string)
  • Mikrozensus (xsd:string)
  • imported (xsd:string)
  • techreport (xsd:string)
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  • 21 (xsd:string)
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