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

scientific article published on 07 December 2013

Detecting cancer clusters in a regional population with local cluster tests and Bayesian smoothing methods: a simulation study is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.1186/1476-072X-12-54
P932PMC publication ID3878948
P698PubMed publication ID24314148

P50authorEdzer J. PebesmaQ55030401
P2093author name stringHans-Werner Hense
Oliver Heidinger
Dorothea Lemke
Volkmar Mattauch
P2860cites workPower evaluation of disease clustering testsQ24795436
Lumping or splitting: seeking the preferred areal unit for health geography studiesQ24795758
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A flexibly shaped spatial scan statistic for detecting clustersQ24815925
Geostatistical analysis of disease data: accounting for spatial support and population density in the isopleth mapping of cancer mortality risk using area-to-point Poisson krigingQ31081670
Comparison of tests for spatial heterogeneity on data with global clustering patterns and outliersQ33509908
Cluster morphology analysisQ33726994
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Cancer map patterns: are they random or not?Q34974589
Cancer clusters in the USA: what do the last twenty years of state and federal investigations tell us?Q36129762
Cluster analysis and disease mapping--why, when, and how? A step by step guideQ36607000
Evaluating spatial methods for investigating global clustering and cluster detection of cancer casesQ36955554
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Effect of spatial resolution on cluster detection: a simulation studyQ42972911
Statistical power of disease cluster and clustering tests for rare diseases: a simulation study of point sourcesQ43758620
A sobering start for the cluster busters' conferenceQ44115663
The geography of power: statistical performance of tests of clusters and clustering in heterogeneous populationsQ46295839
A new proposal to adjust Moran's I for population density.Q52207297
Empirical Bayes estimates of age-standardized relative risks for use in disease mappingQ69417787
P304page(s)54
P577publication date2013-12-07
P1433published inInternational Journal of Health GeographicsQ15752546
P1476titleDetecting cancer clusters in a regional population with local cluster tests and Bayesian smoothing methods: a simulation study
P478volume12

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cites work (P2860)
Q35314535Comparing adaptive and fixed bandwidth-based kernel density estimates in spatial cancer epidemiology
Q36160758Impact of socioeconomic inequalities on geographic disparities in cancer incidence: comparison of methods for spatial disease mapping
Q55012714Sequential tests for monitoring methods to detect elevated incidence - a simulation study.
Q34070100Spatial epidemiology of dry eye disease: findings from South Korea

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