Show simple item record

dc.contributor.authorJi, Kexin 18:26:16 (GMT) 18:26:16 (GMT)
dc.description.abstractIn this thesis, I propose and consider inference for a semiparametric stochastic mixed model for bivariate longitudinal data; and provide a prediction procedure of a future cycle utilizing past cycle information. This thesis is built on the work of Zhang et al (1998) and Zhang, Lin & Sowers (2000). However, the papers are missing big gaps in the theoretical results, are to be applied on univariate longitudinal data, and contain no coverage of prediction of future cycles. We fill in all the gaps in this thesis as well as consider real application of a dataset that contains bivariate longitudinal data. The proposed approach models the mean of outcome variables by parametric fixed effects and a smooth nonparametric function for the underlying time effects, and the relationship across the bivariate responses by a bivariate Gaussian random field and a joint distribution of random effects. The prediction approach is proposed from the frequentist prospective and a prediction density function with predictive intervals will be provided. Simulations studies are performed and a real application of a hormone dataset is considered.en
dc.publisherUniversity of Waterlooen
dc.subjectBivariate longitudinal dataen
dc.subjectGaussian fielden
dc.subjectPenalized likelihooden
dc.subjectSmoothing splineen
dc.titleEstimation and prediction methods for univariate and bivariate cyclic longitudinal data using a semiparametric stochastic mixed effects modelen
dc.typeDoctoral Thesisen
dc.pendingfalse and Actuarial Scienceen (Biostatistics)en of Waterlooen
uws-etd.degreeDoctor of Philosophyen
uws.contributor.advisorDubin, Joel
uws.contributor.affiliation1Faculty of Mathematicsen

Files in this item


This item appears in the following Collection(s)

Show simple item record


University of Waterloo Library
200 University Avenue West
Waterloo, Ontario, Canada N2L 3G1
519 888 4883

All items in UWSpace are protected by copyright, with all rights reserved.

DSpace software

Service outages