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dc.contributor.authorBoudreau, Christianen 14:22:38 (GMT) 14:22:38 (GMT)
dc.description.abstractConsiderable amounts of event history data are collected through longitudinal surveys. These surveys have many particularities or features that are the results of the dynamic nature of the population under study and of the fact that data collected through longitudinal surveys involve the use of complex survey designs, with clustering and stratification. These particularities include: attrition, seam-effect, censoring, left-truncation and complications in the variance estimation due to the use of complex survey designs. This thesis focuses on the last two points. Statistical methods based on the stratified Cox proportional hazards model that account for intra-cluster dependence, when the sampling design is uninformative, are proposed. This is achieved using the theory of estimating equations in conjunction with empirical process theory. Issues concerning analytic inference from survey data and the use of weighted versus unweighted procedures are also discussed. The proposed methodology is applied to data from the U. S. Survey of Income and Program Participation (SIPP) and data from the Canadian Survey of Labour and Income Dynamics (SLID). Finally, different statistical methods for handling left-truncated sojourns are explored and compared. These include the conditional partial likelihood and other methods, based on the Exponential or the Weibull distributions.en
dc.format.extent1203181 bytes
dc.publisherUniversity of Waterlooen
dc.rightsCopyright: 2003, Boudreau, Christian. All rights reserved.en
dc.subjectLongitudinal surveysen
dc.subjectsurvival analysisen
dc.subjectproportional hazards modelen
dc.subjectestimating equationsen
dc.titleDuration Data Analysis in Longitudinal Surveyen
dc.typeDoctoral Thesisen
dc.pendingfalseen and Actuarial Science (Statistics)en
uws-etd.degreeDoctor of Philosophyen

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