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Title: | Spatial modelling to inform public health based on health surveys: impact of unsampled areas at lower geographical scale | Authors: | WATJOU, Kevin FAES, Christel VANDENDIJCK, Yannick |
Issue Date: | 2020 | Publisher: | MDPI | Source: | International Journal of Environmental Research and Public Health, 17 (3) (Art N° 786) | Abstract: | Small area estimation is an important tool to provide area-specific estimates of populations characteristics for governmental organisations in the context of education, public health and care. However, many demographic and health surveys are unrepresentative at a small geographical level, as often areas at a lower level are not included in the sample due to financial or logistical reasons. In this paper, we investigated (1) the effect of these unsampled areas on a variety of design-based and hierarchical model-based estimates and (2) the benefits of using auxiliary information in the estimation process by means of an extensive simulation study. The results showed the benefits of hierarchical spatial smoothing models towards obtaining more reliable estimates for areas at the lowest geographical level in case a spatial trend is present in the data. Furthermore, the importance of auxiliary information was highlighted, especially for geographical areas that were not included in the sample. Methods are illustrated on the 2008 Mozambique Poverty and Social Impact Analysis survey, with interest in the district-specific prevalence of school attendance. | Keywords: | Model-based inference;Small Area Estimation;Spatial smoothing;Survey weighting;Missing areas 1 | Document URI: | http://hdl.handle.net/1942/30595 | ISSN: | 1661-7827 | e-ISSN: | 1660-4601 | DOI: | 10.3390/ijerph17030786 | ISI #: | WOS:000517783300111 | Rights: | 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2021 |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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IJERPH_Review_DSpace.pdf | Published version | 6.75 MB | Adobe PDF | View/Open |
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