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Combining difference and equivalence test results in spatial maps

BACKGROUND: Regionally partitioned health indicator values are commonly presented in choropleth maps. Policymakers and health authorities use them among others for health reporting, demand planning and quality assessment. Quite often there are concerns whether the health situation in certain areas c...

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Detalles Bibliográficos
Autores principales: Waldhoer, Thomas, Heinzl, Harald
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3032638/
https://www.ncbi.nlm.nih.gov/pubmed/21219612
http://dx.doi.org/10.1186/1476-072X-10-3
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author Waldhoer, Thomas
Heinzl, Harald
author_facet Waldhoer, Thomas
Heinzl, Harald
author_sort Waldhoer, Thomas
collection PubMed
description BACKGROUND: Regionally partitioned health indicator values are commonly presented in choropleth maps. Policymakers and health authorities use them among others for health reporting, demand planning and quality assessment. Quite often there are concerns whether the health situation in certain areas can be considered different or equivalent to a reference value. RESULTS: Highlighting statistically significant areas enables the statement that these areas differ from the reference value. However, this approach does not allow conclusions which areas are sufficiently close to the reference value, although these are crucial for health policy making as well. In order to overcome this weakness a combined integration of statistical difference and equivalence tests into choropleth maps is suggested and the approach is exemplified with health data of Austrian newborns. CONCLUSIONS: The suggested method will improve the interpretability of choropleth maps for policymakers and health authorities.
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spelling pubmed-30326382011-02-03 Combining difference and equivalence test results in spatial maps Waldhoer, Thomas Heinzl, Harald Int J Health Geogr Research BACKGROUND: Regionally partitioned health indicator values are commonly presented in choropleth maps. Policymakers and health authorities use them among others for health reporting, demand planning and quality assessment. Quite often there are concerns whether the health situation in certain areas can be considered different or equivalent to a reference value. RESULTS: Highlighting statistically significant areas enables the statement that these areas differ from the reference value. However, this approach does not allow conclusions which areas are sufficiently close to the reference value, although these are crucial for health policy making as well. In order to overcome this weakness a combined integration of statistical difference and equivalence tests into choropleth maps is suggested and the approach is exemplified with health data of Austrian newborns. CONCLUSIONS: The suggested method will improve the interpretability of choropleth maps for policymakers and health authorities. BioMed Central 2011-01-10 /pmc/articles/PMC3032638/ /pubmed/21219612 http://dx.doi.org/10.1186/1476-072X-10-3 Text en Copyright ©2011 Waldhoer and Heinzl; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Waldhoer, Thomas
Heinzl, Harald
Combining difference and equivalence test results in spatial maps
title Combining difference and equivalence test results in spatial maps
title_full Combining difference and equivalence test results in spatial maps
title_fullStr Combining difference and equivalence test results in spatial maps
title_full_unstemmed Combining difference and equivalence test results in spatial maps
title_short Combining difference and equivalence test results in spatial maps
title_sort combining difference and equivalence test results in spatial maps
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3032638/
https://www.ncbi.nlm.nih.gov/pubmed/21219612
http://dx.doi.org/10.1186/1476-072X-10-3
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