Espuny-Pujol, F;
Morrissey, K;
Williamson, P;
(2018)
A global optimisation approach to range-restricted survey calibration.
Statistics and Computing
, 28
(2)
pp. 427-439.
10.1007/s11222-017-9739-5.
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Abstract
Survey calibration methods modify minimally sample weights to satisfy domain-level benchmark constraints (BC), e.g. census totals. This allows exploitation of auxiliary information to improve the representativeness of sample data (addressing coverage limitations, non-response) and the quality of sample-based estimates of population parameters. Calibration methods may fail with samples presenting small/zero counts for some benchmark groups or when range restrictions (RR), such as positivity, are imposed to avoid unrealistic or extreme weights. User-defined modifications of BC/RR performed after encountering non-convergence allow little control on the solution, and penalisation approaches modelling infeasibility may not guarantee convergence. Paradoxically, this has led to underuse in calibration of highly disaggregated information, when available. We present an always-convergent flexible two-step global optimisation (GO) survey calibration approach. The feasibility of the calibration problem is assessed, and automatically controlled minimum errors in BC or changes in RR are allowed to guarantee convergence in advance, while preserving the good properties of calibration estimators. Modelling alternatives under different scenarios using various error/change and distance measures are formulated and discussed. The GO approach is validated by calibrating the weights of the 2012 Health Survey for England to a fine age–gender–region cross-tabulation (378 counts) from the 2011 Census in England and Wales.
| Type: | Article |
|---|---|
| Title: | A global optimisation approach to range-restricted survey calibration |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s11222-017-9739-5 |
| Publisher version: | http://doi.org/10.1007/s11222-017-9739-5 |
| Language: | English |
| Additional information: | Copyright © The Author(s) 2017. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
| Keywords: | Calibration estimation, Calibration weighting, Design-based inference, Generalised regression, Penalised calibration, Raking, Ridge calibration, Range restrictions |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Mathematics UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Mathematics > Clinical Operational Research Unit |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10067066 |
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