Literature DB >> 22491962

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

Alan P Bender1, Allan N Williams, John Soler, Margee Brown.   

Abstract

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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Mesh:

Year:  2012        PMID: 22491962      PMCID: PMC3349855          DOI: 10.1007/s10552-012-9920-2

Source DB:  PubMed          Journal:  Cancer Causes Control        ISSN: 0957-5243            Impact factor:   2.506


  19 in total

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6.  Reliability-adjusted disease maps.

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Journal:  Soc Sci Med       Date:  1995-11       Impact factor: 4.634

7.  Multiple significance tests: the Bonferroni method.

Authors:  J M Bland; D G Altman
Journal:  BMJ       Date:  1995-01-21

8.  Efficient interval estimation for age-adjusted cancer rates.

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Journal:  Stat Methods Med Res       Date:  2006-12       Impact factor: 3.021

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Authors:  Yongping Hao; Elizabeth M Ward; Ahmedin Jemal; Linda W Pickle; Michael J Thun
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Review 10.  Current practices in spatial analysis of cancer data: mapping health statistics to inform policymakers and the public.

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Journal:  Int J Health Geogr       Date:  2006-11-08       Impact factor: 3.918

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