Literature DB >> 24872726

Power Evaluation of Focused Cluster Tests.

Rc Puett1, Ab Lawson2, Ab Clark3, Jr Hebert4, M Kulldorff5.   

Abstract

Many statistical tests have been developed to assess the significance of clusters of disease located around known sources of environmental contaminants, also known as focused disease clusters. The majority of focused-cluster tests were designed to detect a particular spatial pattern of clustering, one in which the disease cluster centers around the pollution source and declines in a radial fashion with distance. However, other spatial patterns of environmentally related disease clusters are likely given that the spatial dispersion patterns of environmental contaminants, and thus human exposure, depend on a number of factors (i.e., meteorology and topography). For this study, data were simulated with five different spatial patterns of disease clusters, reflecting potential pollutant dispersion scenarios: 1) a radial effect decreasing with increasing distance, 2) a radial effect with a defined peak and decreasing with distance, 3) a simple angular effect, 4) an angular effect decreasing with increasing distance and 5) an angular effect with a defined peak and decreasing with distance. The power to detect each type of spatially distributed disease cluster was evaluated using Stone's Maximum Likelihood Ratio Test, Tango's Focused Test, Bithell's Linear Risk Score Test, and variations of the Lawson-Waller Score Test. Study findings underscore the importance of considering environmental contaminant dispersion patterns, particularly directional effects, with respect to focused-cluster test selection in cluster investigations. The effect of extra variation in risk also is considered, although its effect is not substantial in terms of the power of tests.

Entities:  

Keywords:  clusters; power; small area analysis; spatial statistics

Year:  2010        PMID: 24872726      PMCID: PMC4033302          DOI: 10.1007/s10651-009-0108-1

Source DB:  PubMed          Journal:  Environ Ecol Stat        ISSN: 1352-8505            Impact factor:   1.119


  9 in total

1.  Score tests for detecting excess risks around putative sources.

Authors:  Toshiro Tango
Journal:  Stat Med       Date:  2002-02-28       Impact factor: 2.373

2.  On the analysis of mortality events associated with a prespecified fixed point.

Authors:  A B Lawson
Journal:  J R Stat Soc Ser A Stat Soc       Date:  1993       Impact factor: 2.483

Review 3.  A comparison of Bayesian spatial models for disease mapping.

Authors:  Nicky Best; Sylvia Richardson; Andrew Thomson
Journal:  Stat Methods Med Res       Date:  2005-02       Impact factor: 3.021

Review 4.  Empirical Bayes methods for disease mapping.

Authors:  Alastair H Leyland; Carolyn A Davies
Journal:  Stat Methods Med Res       Date:  2005-02       Impact factor: 3.021

5.  A class of tests for detecting 'general' and 'focused' clustering of rare diseases.

Authors:  T Tango
Journal:  Stat Med       Date:  1995 Nov 15-30       Impact factor: 2.373

6.  The power of focused tests to detect disease clustering.

Authors:  L A Waller; A B Lawson
Journal:  Stat Med       Date:  1995 Nov 15-30       Impact factor: 2.373

7.  The choice of test for detecting raised disease risk near a point source.

Authors:  J F Bithell
Journal:  Stat Med       Date:  1995 Nov 15-30       Impact factor: 2.373

Review 8.  Statistical power and design of focused clustering studies.

Authors:  L A Waller
Journal:  Stat Med       Date:  1996 Apr 15-May 15       Impact factor: 2.373

9.  Investigations of excess environmental risks around putative sources: statistical problems and a proposed test.

Authors:  R A Stone
Journal:  Stat Med       Date:  1988-06       Impact factor: 2.373

  9 in total
  1 in total

1.  Childhood cancer in small geographical areas and proximity to air-polluting industries.

Authors:  Juan A Ortega-García; Fernando A López-Hernández; Alberto Cárceles-Álvarez; José L Fuster-Soler; Diana I Sotomayor; Rebeca Ramis
Journal:  Environ Res       Date:  2017-03-19       Impact factor: 6.498

  1 in total

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