Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/99148
DC FieldValueLanguage
dc.contributor.authorLin, Tsung-Izh_TW
dc.contributor.author林宗儀zh_TW
dc.contributor.authorLachos, Victor Hzh_TW
dc.contributor.authorWang, Wan-Lunzh_TW
dc.date2018-05-08-
dc.date.accessioned2019-10-16T06:49:35Z-
dc.date.available2019-10-16T06:49:35Z-
dc.identifier.urihttp://hdl.handle.net/11455/99148-
dc.description.abstractThe multivariate linear mixed model (MLMM) has emerged as an important analytical tool for longitudinal data with multiple outcomes. However, the analysis of multivariate longitudinal data could be complicated by the presence of censored measurements because of a detection limit of the assay in combination with unavoidable missing values arising when subjects miss some of their scheduled visits intermittently. This paper presents a generalization of the MLMM approach, called the MLMM-CM, for a joint analysis of the multivariate longitudinal data with censored and intermittent missing responses. A computationally feasible expectation maximization-based procedure is developed to carry out maximum likelihood estimation within the MLMM-CM framework. Moreover, the asymptotic standard errors of fixed effects are explicitly obtained via the information-based method. We illustrate our methodology by using simulated data and a case study from an AIDS clinical trial. Experimental results reveal that the proposed method is able to provide more satisfactory performance as compared with the traditional MLMM approach.zh_TW
dc.language.isoenzh_TW
dc.relationStatistics in medicinezh_TW
dc.subjectECM algorithmzh_TW
dc.subjectHIV AIDS studyzh_TW
dc.subjectcensored datazh_TW
dc.subjectmissing-data imputationzh_TW
dc.subjecttruncated multivariate normal distributionzh_TW
dc.titleMultivariate longitudinal data analysis with censored and intermittent missing responseszh_TW
dc.typeJournal Articlezh_TW
dc.identifier.doi10.1002/sim.7692zh_TW
dc.awards2018zh_TW
item.cerifentitytypePublications-
item.grantfulltextrestricted-
item.languageiso639-1en-
item.fulltextwith fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeJournal Article-
Appears in Collections:統計學研究所
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