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dc.contributorDepartment of Applied Mathematicsen_US
dc.contributor.advisorZhao, Xingqiu (AMA)-
dc.creatorLiu, Kin Yat-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/7915-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleRobust estimation for longitudinal data with informative observation timesen_US
dcterms.abstractIn this thesis, we focus on regression analysis of longitudinal data that often occur in medical follow-up studies and observational investigations. The analysis of these data involves two processes. One is the underlying recurrent event process of interest and the other is the observation process that controls observation times. Most of the existing methods, however, rely on some restrictive models or assumptions such as the Poisson assumption. For this, we propose a more general and robust estimation approach for regression analysis of longitudinal data with related observation times. The asymptotic properties of the proposed estimators are established and numerical studies indicate that the proposed method works well for practical situations.en_US
dcterms.extent53 leaves ; 30 cmen_US
dcterms.issued2014en_US
dcterms.educationalLevelAll Masteren_US
dcterms.educationalLevelM.Phil.en_US
dcterms.LCSHLongitudinal method.en_US
dcterms.LCSHRegression analysis.en_US
dcterms.LCSHMedicine -- Research -- Statistical methods.en_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsopen accessen_US

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