Almeida, Alexandre Celestino Leite deDuarte, Anderson RibeiroDuczmal, Luiz HenriqueOliveira, Fernando Luiz Pereira deTakahashi, Ricardo Hiroshi Caldeira2012-10-222012-10-222011ALMEIDA, A. C. L. de et al. Data-driven inference for the spatial scan statistic. International Journal of Health Geographics, v. 10, n. 47, p. 1-8, 2011. Disponível em: <http://www.ij-healthgeographics.com/content/pdf/1476-072X-10-47.pdf>. Acesso em: 22 out. 2012.1476072Xhttp://www.repositorio.ufop.br/handle/123456789/1735Background: 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.en-USArtigo publicado em periodicoAutores 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.