Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/207037 
Erscheinungsjahr: 
2019
Schriftenreihe/Nr.: 
Research Papers in Economics No. 5/19
Verlag: 
Universität Trier, Fachbereich IV - Volkswirtschaftslehre, Trier
Zusammenfassung: 
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.
Schlagwörter: 
disease mapping
multi-level model
multi-source estimation
penalization
stochastic gradient descent
Dokumentart: 
Working Paper

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