Literature DB >> 22749209

Statistical power of disease cluster and clustering tests for rare diseases: a simulation study of point sources.

Sven Schmiedel1, Maria Blettner, Joachim Schüz.   

Abstract

Two recent epidemiological studies on clustering of childhood leukemia showed different results on the statistical power of disease cluster and clustering tests, possibly an effect of spatial data aggregation. Eight different leukemia cluster scenarios were simulated using individual addresses of all 1,009,332 children living in Denmark in 2006. For each scenario, a number of point sources were defined with an increased risk ratio at centroid, decreasing linearly to 1.0 at the edge; aggregation levels were administrative units of Danish municipalities and squares of 5, 12.5 and 25 km(2). Six statistical methods were compared. Generally, statistical power decreased with increasing size of aggregated units. In our scenarios, statistical tests based on individual data usually had lower statistical power than the best test based on aggregated data. In conclusion, spatial aggregation does not necessarily blur a clustering effect; this depends on the nature of clustering and the aggregated units.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 22749209     DOI: 10.1016/j.sste.2012.02.011

Source DB:  PubMed          Journal:  Spat Spatiotemporal Epidemiol        ISSN: 1877-5845


  4 in total

1.  Influence of Detection Method and Study Area Scale on Syphilis Cluster Identification in North Carolina.

Authors:  Veronica Escamilla; Kristen H Hampton; Dionne C Gesink; Marc L Serre; Michael Emch; Peter A Leone; Erika Samoff; William C Miller
Journal:  Sex Transm Dis       Date:  2016-04       Impact factor: 2.830

2.  Mapping disease at an approximated individual level using aggregate data: a case study of mapping New Hampshire birth defects.

Authors:  Xun Shi; Stephanie Miller; Kevin Mwenda; Akikazu Onda; Judy Reese; Tracy Onega; Jiang Gui; Margret Karagas; Eugene Demidenko; John Moeschler
Journal:  Int J Environ Res Public Health       Date:  2013-09-06       Impact factor: 3.390

3.  Detecting cancer clusters in a regional population with local cluster tests and Bayesian smoothing methods: a simulation study.

Authors:  Dorothea Lemke; Volkmar Mattauch; Oliver Heidinger; Edzer Pebesma; Hans-Werner Hense
Journal:  Int J Health Geogr       Date:  2013-12-07       Impact factor: 3.918

4.  Influence of spatial resolution on space-time disease cluster detection.

Authors:  Stephen G Jones; Martin Kulldorff
Journal:  PLoS One       Date:  2012-10-24       Impact factor: 3.240

  4 in total

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