Register data in sample allocations for small-area estimation
Keto, M., Hakanen, J., & Pahkinen, E. (2018). Register data in sample allocations for small-area estimation. Mathematical Population Studies, 25(4), 184-214. https://doi.org/10.1080/08898480.2018.1437318
Published inMathematical Population Studies
© 2018 Taylor & Francis Group, LLC.
The inadequate control of sample sizes in surveys using stratified sampling and area estimation may occur when the overall sample size is small or auxiliary information is insufficiently used. Very small sample sizes are possible for some areas. The proposed allocation based on multi-objective optimization uses a small-area model and estimation method and semi-collected empirical data annually collected empirical data. The assessment of its performance at the area and at the population levels is based on design-based sample simulations. Five previously developed allocations serve as references. The model-based estimator is more accurate than the design-based Horvitz–Thompson estimator and the model-assisted regression estimator. Two trade-off issues are between accuracy and bias and between the area- and the population-level qualities of estimates. If the survey uses model-based estimation, the sampling design should incorporate the underlying model and the estimation method.
PublisherTaylor & Francis Inc.
Publication in research information system
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