Linked Life Data

11318228

Source:http://linkedlifedata.com/resource/pubmed/id/11318228

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2001-4-24
pubmed:abstractText
In 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.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
0006-341X
pubmed:author
pubmed:issnType
Print
pubmed:volume
55
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
645-51
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Comparison of several independent population means when their samples contain log-normal and possibly zero observations.
pubmed:affiliation
Department of Medicine, Indiana University School of Medicine, Indianapolis 46202-2859, USA. zhou@mako.biostat.iupui.edu
pubmed:publicationType
Journal Article, Comparative Study, Research Support, U.S. Gov't, P.H.S.