Calibration estimation in dual-frame surveys
| Autor: | María del Mar Rueda, Annalisa Teodoro, Antonio Arcos, M. Giovanna Ranalli |
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| Rok vydání: | 2015 |
| Předmět: |
Statistics and Probability
Kullback–Leibler divergence Survey methodology Calibration (statistics) Computer science 010103 numerical & computational mathematics computer.software_genre Auxiliary information Raking ratio Regression estimation Survey Methodology 01 natural sciences Undercoverage 010104 statistics & probability Statistics Probability and Uncertainty Benchmark (surveying) 0101 mathematics Unequal probability sampling Statistics Frame (networking) Estimator Sampling (statistics) Kullback-Leibler distance Variable (computer science) Probability and Uncertainty Data mining computer |
| Zdroj: | Digibug: Repositorio Institucional de la Universidad de Granada Universidad de Granada (UGR) Digibug. Repositorio Institucional de la Universidad de Granada instname |
| ISSN: | 1613-981X 1618-2510 |
| DOI: | 10.1007/s10260-015-0336-5 |
| Popis: | Survey statisticians make use of auxiliary information to improve estimates. One important example is calibration estimation, which constructs new weights that match benchmark constraints on auxiliary variables while remaining “close” to the design weights. Multiple-frame surveys are increasingly used by statistical agencies and private organizations to reduce sampling costs and/or avoid frame undercoverage errors. Several ways of combining estimates derived from such frames have been proposed elsewhere; in this paper, we extend the calibration paradigm, previously used for single-frame surveys, to calculate the total value of a variable of interest in a dual-frame survey. Calibration is a general tool that allows to include auxiliary information from two frames. It also incorporates, as a special case, certain dual-frame estimators that have been proposed previously. The theoretical properties of our class of estimators are derived and discussed, and simulation studies conducted to compare the efficiency of the procedure, using different sets of auxiliary variables. Finally, the proposed methodology is applied to real data obtained from the Barometer of Culture of Andalusia survey. Ministerio de Educación y Ciencia Consejería de Economía, Innovación, Ciencia y Empleo PRIN-SURWEY |
| Databáze: | OpenAIRE |
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