Abstract
Statistical simulation in survey statistics is usually based on repeatedly drawing samples from population data. Furthermore, population data may be used in courses on survey statistics to explain issues regarding, e.g., sampling designs. Since the availability of real population data is in general very limited, it is necessary to generate synthetic data for such applications. The simulated data need to be as realistic as possible, while at the same time ensuring data confidentiality. This paper proposes a method for generating close-to-reality population data for complex household surveys. The procedure consists of four steps for setting up the household structure, simulating categorical variables, simulating continuous variables and splitting continuous variables into different components. It is not required to perform all four steps so that the framework is applicable to a broad class of surveys. In addition, the proposed method is evaluated in an application to the European Union Statistics on Income and Living Conditions (EU-SILC).
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This work was partly funded by the European Union (represented by the European Commission) within the 7th framework programme for research (Theme 8, Socio-Economic Sciences and Humanities, Project AMELI (Advanced Methodology for European Laeken Indicators), Grant Agreement No. 217322). Visit http://ameli.surveystatistics.net for more information on the project.
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Alfons, A., Kraft, S., Templ, M. et al. Simulation of close-to-reality population data for household surveys with application to EU-SILC. Stat Methods Appl 20, 383–407 (2011). https://doi.org/10.1007/s10260-011-0163-2
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DOI: https://doi.org/10.1007/s10260-011-0163-2