About: Power comparisons for disease clustering tests

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description	wetenschappelijk artikel (nl) наукова стаття, опублікована у квітні 2003 (uk) im April 2003 veröffentlichter wissenschaftlicher Artikel (de) article scientifique publié en 2003 (fr)
publication date	wds:Q57590159-CE32AE18-D24D-4CD6-B37E-B9DDB3DF34D9
publication date	2003-04-01 00:00:00Z (xsd:dateTime)
cites work	wds:Q57590159-14BD484B-35E2-4BD9-81DE-620F7A147D73 wds:Q57590159-417B6DEB-B1A8-48CE-83A7-A2A34C71FA56 wds:Q57590159-47FE9054-4AFE-4139-AB8B-1D1AEFAC3C8B wds:Q57590159-7491BFF3-3B45-44CF-92F6-67364D50BD1B wds:Q57590159-7D3F9C7C-D541-4968-A974-322748E60EC9 wds:Q57590159-80EEF050-458C-41F0-9417-0CD1AD70733E wds:Q57590159-812E02CF-3E5F-467B-89D2-F4A8748B62A7 wds:Q57590159-9AD80CF0-AE18-4E9F-AE78-1C6C9FCE5357 wds:Q57590159-9C74481B-4052-4668-BAD6-941981DADC05 wds:Q57590159-B0EF27E3-C79A-4917-A849-A5A6192DBCDD wds:Q57590159-B35F6953-104B-494B-B27A-5AF2E722FDA9 wds:Q57590159-B54A9D76-C033-4502-A71E-7935E166DA79 wds:Q57590159-B96769C7-A8DC-4AAB-8084-47DD3F1B9D4B wds:Q57590159-BFC7B9BF-0852-4040-B79F-3DF65CE6712E wds:Q57590159-C1C05B7C-9C67-44F9-8395-927E5CE0B49A wds:Q57590159-D34D6B26-0886-457B-9743-E3F2DBA5F28A wds:Q57590159-DBD8488F-6952-4033-BD6C-4A0893AD97F2 wds:Q57590159-F0D34D74-A93E-49D5-BF55-7F11D879B83E wds:Q57590159-F535AA0C-BF66-4FC8-B07E-DDE86D9E13B8 wds:Q57590159-F83C123E-7534-4638-9D52-432606FAF4B5 wds:Q57590159-F9C817F6-A626-4552-83D4-860267E6EFC5
cites work	Soft-tissue sarcoma and non-Hodgkin's lymphoma clusters around a municipal solid waste incinerator with high dioxin emission levels Modified Randomization Tests for Nonparametric Hypotheses Disease models implicit in statistical tests of disease clustering. Clustering of childhood mortality in rural Burkina Faso A test for spatial disease clustering adjusted for multiple testing Spatial disease clusters: detection and inference An entropy-based algorithm for detecting clusters of cases and controls and its comparison with a method using nearest neighbours Adjusting Moran's I for population density A class of tests for detecting 'general' and 'focused' clustering of rare diseases. Spatial analytical methods and geographic information systems: use in health research and epidemiology Spatial statistical methods in environmental epidemiology: a critique Estimating the degree of heterogeneity between event rates using likelihood Breast cancer clusters in the northeast United States: a geographic analysis The origins of a new Trypanosoma brucei rhodesiense sleeping sickness outbreak in eastern Uganda Second-order analysis of spatial clustering for inhomogeneous populations Monitoring for clusters of disease: application to leukemia incidence in upstate New York. Geographical distribution of variant Creutzfeldt-Jakob disease in Great Britain, 1994-2000. Spatial autocorrelation in biology: 1. Methodology Random number generators: good ones are hard to find An examination of three spatial disease clustering methodologies Stochastic process and archaeological mechanism in spatial analysis
author name string	wds:Q57590159-42626359-E4F3-4B39-9413-258FD1587E12 wds:Q57590159-6210509C-811B-4235-B9B0-F45395741040
author name string	Peter J Park Toshiro Tango
rdfs:label	Power comparisons for disease clustering tests (en) Power comparisons for disease clustering tests (nl)
skos:prefLabel	Power comparisons for disease clustering tests (en) Power comparisons for disease clustering tests (nl)
name	Power comparisons for disease clustering tests (en) Power comparisons for disease clustering tests (nl)
author	wds:Q57590159-41123B08-6537-40CF-9ABD-648628D36E9C
author	Martin Kulldorff
title	wds:Q57590159-CD20CE18-07EF-4013-8D32-680E5B8754B8
title	Power comparisons for disease clustering tests (en)
page(s)	wds:Q57590159-A3843E43-1BC7-4312-8724-D052F6E29364
page(s)	665-684
instance of	wds:Q57590159-A1739F48-481B-487C-8850-7AA26ABD139C
instance of	scholarly article
DBLP publication ID	wds:Q57590159-0B54D469-1A2B-4846-91C8-2D5F80781DC9
DBLP publication ID	https://dblp.org/rec/journals/csda/KulldorffTP03
DBLP publication ID	journals/csda/KulldorffTP03
published in	wds:Q57590159-E324A0C1-B5AB-4777-B0BB-611D88C332FD
published in	Computational Statistics & Data Analysis
issue	wds:Q57590159-ED20A13D-000B-4D8E-AAFE-EF16D7BC97C5
volume	wds:Q57590159-5DB35E0E-2DCA-4526-8A3D-5A9B04C30FD6
issue	4
volume	42
DOI	wds:Q57590159-6BB4CF07-401C-49E0-9257-6912DDB78A87
DOI	http://dx.doi.org/10.1016/S0167-9473(02)00160-3
DOI	10.1016/S0167-9473(02)00160-3
maintained by WikiProject	wds:Q57590159-CA6E9B6F-C3C6-4DF3-AEAB-2B4573E09786
maintained by WikiProject	WikiProject Mathematics
zbMATH Open document ID	wds:Q57590159-756872D3-2617-4C59-88B9-FD4D0D1F472D
zbMATH Open document ID	1429.62558
is about of	https://www.wikidata.org/wiki/Special:EntityData/Q57590159
is cites work of	Cluster detection methods applied to the Upper Cape Cod cancer data Childhood Diarrhea Exhibits Spatiotemporal Variation in Northwest Ethiopia: A SaTScan Spatial Statistical Analysis A spatial scan statistic for nonisotropic two-level risk cluster. Geographical spread of gastrointestinal tract cancer incidence in the Caspian Sea region of Iran: spatial analysis of cancer registry data. Issues of scale and uncertainty in the global remote sensing of disease. Relative risk estimates from spatial and space-time scan statistics: are they biased? Spatial and space-time clustering of childhood acute leukaemia in France from 1990 to 2000: a nationwide study The spatial structure of autism in California, 1993-2001 Influence of spatial resolution on space-time disease cluster detection Detection of clusters of a rare disease over a large territory: performance of cluster detection methods Spatiotemporal patterns of Japanese encephalitis in China, 2002-2010. Spatial event cluster detection using a compound Poisson distribution. Using Gini coefficient to determining optimal cluster reporting sizes for spatial scan statistics Identifying pediatric cancer clusters in Florida using loglinear models and generalized lasso penalties Cluster Detection Tests in Spatial Epidemiology: A Global Indicator for Performance Assessment Voronoi distance based prospective space-time scans for point data sets: a dengue fever cluster analysis in a southeast Brazilian town.

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