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pubmed-article:11318228pubmed:abstractTextIn this paper, we consider the problem of testing the mean equality of several independent populations that contain log-normal and possibly zero observations. We first showed that the currently used methods in statistical practice, including the nonparametric Kruskal-Wallis test, the standard ANOVA F-test and its two modified versions, the Welch test and the Brown-Forsythe test, could have poor Type I error control. Then we propose a likelihood ratio test that is shown to have much better Type I error control than the existing methods. Finally, we analyze two real data sets that motivated our study using the proposed test.lld:pubmed
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pubmed-article:11318228pubmed:authorpubmed-author:ZhuX NXNlld:pubmed
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pubmed-article:11318228pubmed:pagination645-51lld:pubmed
pubmed-article:11318228pubmed:dateRevised2007-11-15lld:pubmed
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pubmed-article:11318228pubmed:articleTitleComparison of several independent population means when their samples contain log-normal and possibly zero observations.lld:pubmed
pubmed-article:11318228pubmed:affiliationDepartment of Medicine, Indiana University School of Medicine, Indianapolis 46202-2859, USA. zhou@mako.biostat.iupui.edulld:pubmed
pubmed-article:11318228pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:11318228pubmed:publicationTypeComparative Studylld:pubmed
pubmed-article:11318228pubmed:publicationTypeResearch Support, U.S. Gov't, P.H.S.lld:pubmed
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