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Small area estimation to quantify discontinuities in repeated sample surveys
Author(s) -
Brakel Jan A.,
Buelens Bart,
Boonstra HarmJan
Publication year - 2016
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/rssa.12110
Subject(s) - small area estimation , estimator , classification of discontinuities , estimation , sample (material) , randomized experiment , computer science , sample size determination , domain (mathematical analysis) , survey sampling , process (computing) , survey research , statistics , survey data collection , econometrics , mathematics , engineering , psychology , applied psychology , mathematical analysis , population , chemistry , demography , systems engineering , chromatography , sociology , operating system
Summary 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.