Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Two Sample Nonparametric Test under the Additive Hazards Model

Full metadata record
DC Field Value Language
dc.contributor.author홍승만-
dc.contributor.author박효일-
dc.date.accessioned2021-09-09T00:12:05Z-
dc.date.available2021-09-09T00:12:05Z-
dc.date.created2021-06-17-
dc.date.issued2009-
dc.identifier.issn1229-2354-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/121843-
dc.description.abstractIn this study, we propose a nonparametric test procedure between two samples for comparing the hazard functions under the additive hazards model. In this study, we consider to deal with the grouped and right censored data. We derive the test statistic based on the maximum likelihood principle and convert it into the weighted log-rank statistic using the relation between the scores for the censored and uncensored observations. Then we comment briefly about the limiting distribution of the proposed test statistic under the null hypothesis. Then we illustrate our procedure with an example. Finally we discuss some peculiar aspects of our test as concluding remarks.-
dc.languageEnglish-
dc.language.isoen-
dc.publisher한국자료분석학회-
dc.titleTwo Sample Nonparametric Test under the Additive Hazards Model-
dc.title.alternativeTwo Sample Nonparametric Test under the Additive Hazards Model-
dc.typeArticle-
dc.contributor.affiliatedAuthor홍승만-
dc.identifier.bibliographicCitationJournal of The Korean Data Analysis Society, v.11, no.1, pp.43 - 51-
dc.relation.isPartOfJournal of The Korean Data Analysis Society-
dc.citation.titleJournal of The Korean Data Analysis Society-
dc.citation.volume11-
dc.citation.number1-
dc.citation.startPage43-
dc.citation.endPage51-
dc.type.rimsART-
dc.identifier.kciidART001320230-
dc.description.journalClass2-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthoradditive model-
dc.subject.keywordAuthorlog-rank statistic-
dc.subject.keywordAuthortwo-sample problem.-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Public Policy > Division of Big Data Science > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE