Handling complex multilevel data structures

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dc.contributor.advisorBeretvas, Susan Natasha
dc.creatorLi, Yuanhanen
dc.date.accessioned2013-12-05T18:48:42Zen
dc.date.accessioned2017-05-11T22:39:47Z
dc.date.available2017-05-11T22:39:47Z
dc.date.issued2013-05en
dc.date.submittedMay 2013en
dc.date.updated2013-12-05T18:48:42Zen
dc.descriptiontexten
dc.description.abstractThis report focuses on introducing two statistical models for dealing with data involving complex social structures. Appropriate handling of data structures is a concern in the context of educational settings. From base single-level data to complex hierarchical with cross-classifications and multiple-memberships, we explain and demonstrate their distinction and establish appropriate regression models. Real data from the National Center for Education Statistics (NECS) is used to demonstrate different way of handling a cross-classified data structure as well as appropriate models. Results will be presented and compared to examine the practical operation for each model.en
dc.description.departmentStatisticsen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/2152/22569en
dc.language.isoen_USen
dc.subjectHierarchical modelen
dc.subjectCross-classificationen
dc.subjectMultiple-membershipen
dc.titleHandling complex multilevel data structuresen

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