Literature DB >> 9132905

Realistic power simulations compare point- and area-based disease cluster tests.

N Oden1, G Jacquez, R Grimson.   

Abstract

One can roughly divide disease cluster tests into area-based (using regional data) and point-based (using exact locations). We have compared the power of two area-based methods (Moran's I and I* (pop), a new method) to that of two point-based methods (the Cuzick-Edwards test and Grimson's test), using three realistic simulations of disease (fox rabies in England, childhood leukaemia in North Humberside, England, and Lyme disease in Georgia). The naive belief that point-based methods should be better is not supported: for the complex data simulated here, I* (pop) and the Cuzick-Edwards test had higher power than Grimson's method or Moran's I. I* (pop) capitalizes on high inter-region variability, while Moran's I cannot.

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Year:  1996        PMID: 9132905     DOI: 10.1002/(sici)1097-0258(19960415)15:7/9<783::aid-sim249>3.0.co;2-o

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  3 in total

1.  An assessment of spatial clustering of leukaemias and lymphomas among young people in New Zealand.

Authors:  J D Dockerty; K J Sharples; B Borman
Journal:  J Epidemiol Community Health       Date:  1999-03       Impact factor: 3.710

2.  Spatial clusters of cancers in Illinois 1986-2000.

Authors:  Fahui Wang
Journal:  J Med Syst       Date:  2004-06       Impact factor: 4.460

3.  Spatial cluster analysis of early stage breast cancer: a method for public health practice using cancer registry data.

Authors:  Jaymie R Meliker; Geoffrey M Jacquez; Pierre Goovaerts; Glenn Copeland; May Yassine
Journal:  Cancer Causes Control       Date:  2009-02-15       Impact factor: 2.506

  3 in total

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