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A nonparametric approach for determining significance of county cancer rates compared to the overall state rate: illustrated with Minnesota data

BACKGROUND: The study of the geographical distribution of disease has expanded greatly with GIS technology and its application to increasingly available public health data. The emergence of this technology has increased the challenges for public health practitioners to provide meaningful interpretat...

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Autores principales: Bender, Alan P., Williams, Allan N., Soler, John, Brown, Margee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3349855/
https://www.ncbi.nlm.nih.gov/pubmed/22491962
http://dx.doi.org/10.1007/s10552-012-9920-2
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author Bender, Alan P.
Williams, Allan N.
Soler, John
Brown, Margee
author_facet Bender, Alan P.
Williams, Allan N.
Soler, John
Brown, Margee
author_sort Bender, Alan P.
collection PubMed
description BACKGROUND: The study of the geographical distribution of disease has expanded greatly with GIS technology and its application to increasingly available public health data. The emergence of this technology has increased the challenges for public health practitioners to provide meaningful interpretations for county-based state cancer maps. METHODS: One of these challenges—spurious inferences about the significance of differences between county and overall state cancer rates—can be addressed through a nonparametric statistical method. The Wilcoxon’s signed rank test (WSRT) has a practical application for determining the significance of county cancer rates compared to the statewide rate. This extension of the WSRT, developed by John Tukey, forms the basis for constructing a single confidence interval for all differences in county and state directly age-adjusted cancer rates. Empirical evaluation of this WSRT application was conducted using Minnesota cancer incidence data. RESULTS: The WSRT procedure reduced the impact of statistical artifacts that are frequently encountered with standard normal significance testing of the difference between directly age-adjusted county and the overall state cancer rates. CONCLUSION: Although further assessment of its performance is required, the WSRT procedure appears to be a useful complement for mapping directly age-adjusted state cancer rates by county.
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spelling pubmed-33498552012-05-30 A nonparametric approach for determining significance of county cancer rates compared to the overall state rate: illustrated with Minnesota data Bender, Alan P. Williams, Allan N. Soler, John Brown, Margee Cancer Causes Control Original Paper BACKGROUND: The study of the geographical distribution of disease has expanded greatly with GIS technology and its application to increasingly available public health data. The emergence of this technology has increased the challenges for public health practitioners to provide meaningful interpretations for county-based state cancer maps. METHODS: One of these challenges—spurious inferences about the significance of differences between county and overall state cancer rates—can be addressed through a nonparametric statistical method. The Wilcoxon’s signed rank test (WSRT) has a practical application for determining the significance of county cancer rates compared to the statewide rate. This extension of the WSRT, developed by John Tukey, forms the basis for constructing a single confidence interval for all differences in county and state directly age-adjusted cancer rates. Empirical evaluation of this WSRT application was conducted using Minnesota cancer incidence data. RESULTS: The WSRT procedure reduced the impact of statistical artifacts that are frequently encountered with standard normal significance testing of the difference between directly age-adjusted county and the overall state cancer rates. CONCLUSION: Although further assessment of its performance is required, the WSRT procedure appears to be a useful complement for mapping directly age-adjusted state cancer rates by county. Springer Netherlands 2012-04-11 2012 /pmc/articles/PMC3349855/ /pubmed/22491962 http://dx.doi.org/10.1007/s10552-012-9920-2 Text en © The Author(s) 2012 https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Original Paper
Bender, Alan P.
Williams, Allan N.
Soler, John
Brown, Margee
A nonparametric approach for determining significance of county cancer rates compared to the overall state rate: illustrated with Minnesota data
title A nonparametric approach for determining significance of county cancer rates compared to the overall state rate: illustrated with Minnesota data
title_full A nonparametric approach for determining significance of county cancer rates compared to the overall state rate: illustrated with Minnesota data
title_fullStr A nonparametric approach for determining significance of county cancer rates compared to the overall state rate: illustrated with Minnesota data
title_full_unstemmed A nonparametric approach for determining significance of county cancer rates compared to the overall state rate: illustrated with Minnesota data
title_short A nonparametric approach for determining significance of county cancer rates compared to the overall state rate: illustrated with Minnesota data
title_sort nonparametric approach for determining significance of county cancer rates compared to the overall state rate: illustrated with minnesota data
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3349855/
https://www.ncbi.nlm.nih.gov/pubmed/22491962
http://dx.doi.org/10.1007/s10552-012-9920-2
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