Data-driven inference for the spatial scan statistic

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Autor(es): dc.creatorAlmeida, Alexandre Celestino Leite de-
Autor(es): dc.creatorDuarte, Anderson Ribeiro-
Autor(es): dc.creatorDuczmal, Luiz Henrique-
Autor(es): dc.creatorOliveira, Fernando Luiz Pereira de-
Autor(es): dc.creatorTakahashi, Ricardo Hiroshi Caldeira-
Data de aceite: dc.date.accessioned2019-11-06T13:25:29Z-
Data de disponibilização: dc.date.available2019-11-06T13:25:29Z-
Data de envio: dc.date.issued2012-10-22-
Data de envio: dc.date.issued2012-10-22-
Data de envio: dc.date.issued2011-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/123456789/1735-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/555085-
Descrição: dc.descriptionBackground: Kulldorff’s spatial scan statistic for aggregated area map s searches for cluster s of case s without specifying their size (numb er of areas) or geo graphic location in advance . Their statistical significance is tested while adjusting for the multiple testing inherent in such a procedure. However, as is shown in this work, this adjustment is not don e in an even manner for all possible cluster sizes .Results: A modification is proposed to the usual inference test of the spatial scan statistic, incorporating additional information about the size of the most likely cluster found. A new interpretation of the results of the spatial scan statistic is done, posing a modified inference question: what is the probability that the null hypo thesis is rejected for the original observed cases map with a most likely cluster of size k, taking into account only those most likely clusters of size k found un der null hypothesis for comparison? This question is especially important when the p-value computed by the usual inference process is near the alpha significance level, regarding the correctness of the decision based in this inference. Conclusions : A practical procedure is provide d to make more accurate inferences about the most likely cluster found by the spatial scan statistic.-
Idioma: dc.languageen-
Direitos: dc.rightsAutores de artigos publicados no International Journal of Health Geographics são os detentores do copyright de seus artigos e concederam a qualquer terceiro o direito de usar, repoduzir ou disseminar o artigo. Fonte: International Journal of Health Geographics <http://www.ij-healthgeographics.com/about> Acesso em 01 Dez. 2013.-
Título: dc.titleData-driven inference for the spatial scan statistic-
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