Small area estimation to quantify discontinuities in repeated sample surveys

Jan van den Brakel*, Bart Buelens, Harm-Jan Boonstra

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

During redesigns of repeated surveys, the old and new approaches are often conducted in parallel to quantify discontinuities that are initiated by modifications in the survey process. For budget limitations, the sample size allocated to the alternative approach is often considerably smaller compared with the regular survey that is used for official publication. In this paper, small area estimation techniques are considered to improve the accuracy of domain estimates obtained under the alternative approach. Besides auxiliary information that is available from administrations, direct domain estimates available from the regular survey are useful auxiliary variables to construct model-based small area estimators. These methods are applied to a redesign of the Dutch Crime Victimization Survey.

Original languageEnglish
Pages (from-to)229-250
Number of pages22
JournalJournal of the Royal Statistical Society Series A-Statistics in Society
Volume179
Issue number1
DOIs
Publication statusPublished - Jan 2016

Keywords

  • Area level models
  • Empirical best linear unbiased prediction
  • Hierarchical Bayes
  • Survey sampling
  • ERROR

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