Calibration estimation in dual-frame surveys Ranalli, Maria Giovanna Arcos Cebrián, Antonio Rueda García, María Del Mar Teodoro, Annalisa Auxiliary information Kullback-Leibler distance Raking ratio Regression estimation Survey Methodology Unequal probability sampling 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. 2021-05-14T11:25:58Z 2021-05-14T11:25:58Z 2015-09-01 info:eu-repo/semantics/article Ranalli, M.G., Arcos, A., Rueda, M.d.M. et al. Calibration estimation in dual-frame surveys. Stat Methods Appl 25, 321–349 (2016). https://doi.org/10.1007/s10260-015-0336-5 http://hdl.handle.net/10481/68532 https://doi.org/10.1007/s10260-015-0336-5 eng MTM2012-35650 SEJ2954 2012F42NS8 http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/openAccess Atribución-NoComercial-SinDerivadas 3.0 España