Cargando…
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...
Autores principales: | , , , |
---|---|
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 |
_version_ | 1782232568401231872 |
---|---|
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. |
format | Online Article Text |
id | pubmed-3349855 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT benderalanp anonparametricapproachfordeterminingsignificanceofcountycancerratescomparedtotheoverallstaterateillustratedwithminnesotadata AT williamsallann anonparametricapproachfordeterminingsignificanceofcountycancerratescomparedtotheoverallstaterateillustratedwithminnesotadata AT solerjohn anonparametricapproachfordeterminingsignificanceofcountycancerratescomparedtotheoverallstaterateillustratedwithminnesotadata AT brownmargee anonparametricapproachfordeterminingsignificanceofcountycancerratescomparedtotheoverallstaterateillustratedwithminnesotadata AT benderalanp nonparametricapproachfordeterminingsignificanceofcountycancerratescomparedtotheoverallstaterateillustratedwithminnesotadata AT williamsallann nonparametricapproachfordeterminingsignificanceofcountycancerratescomparedtotheoverallstaterateillustratedwithminnesotadata AT solerjohn nonparametricapproachfordeterminingsignificanceofcountycancerratescomparedtotheoverallstaterateillustratedwithminnesotadata AT brownmargee nonparametricapproachfordeterminingsignificanceofcountycancerratescomparedtotheoverallstaterateillustratedwithminnesotadata |