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FUNCTIONAL BASED MULTI-LEVEL FLEXIBLE MODELS FOR MULTIVARIATE LONGITUDINAL DATA by Nuoo-Ting (Jassy) Molitor A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Ful¯llment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (BIOSTATISTICS) December 2006 Copyright 2006 Nuoo-Ting (Jassy) Molitor
Object Description
Title | Functional based multi-level flexible models for multivariate longitudinal data |
Author | Molitor, Nuoo-Ting (Jassy) |
Author email | nuootinl@usc.edu |
Degree | Doctor of Philosophy |
Document type | Dissertation |
Degree program | Biostatistics |
School | Keck School of Medicine |
Date defended/completed | 2006-05-16 |
Restricted until | Unrestricted |
Date published | 2006-09-28 |
Advisor (committee chair) | Berhane, Kiros |
Advisor (committee member) |
McConnell, Robert Stram, Daniel O. Thomas, Duncan Sugar, Catherine |
Abstract | The examination of the relationship between ecologic covariates and functionals related to various lung function growth curves is of main interest in studying the long term effects of air pollution on children's health. However, such a modeling process leads to several challenging and unresolved issues such as non-linearity in the growth curves, and the correlation between and within outcomes. In this dissertation, flexible multi-level modeling techniques are proposed using penalized splines to model longitudinal outcomes (e.g. lung functions). This new method not only allows for the flexibility in modeling non-linear growth curves but also allows for joint-modeling of the smoothing parameter and the variance components. Second, the penalized-spline based mixed effects model is extended by modeling multiple outcomes jointly via latent variables approach. Hence, this extended model provides a way of accounting for the correlation between outcomes. All proposed models are implemented in a Bayesian setting. These techniques are illustrated throughout via analysis of data from the Southern California Children's Health Study. |
Keyword | longitudinal data; air pollution; penalized splines; growth curves; Bayesian; multi-level modeling |
Language | English |
Part of collection | University of Southern California dissertations and theses |
Publisher (of the original version) | University of Southern California |
Place of publication (of the original version) | Los Angeles, California |
Publisher (of the digital version) | University of Southern California. Libraries |
Type | texts |
Legacy record ID | usctheses-m49 |
Contributing entity | University of Southern California |
Rights | Molitor, Nuoo-Ting (Jassy) |
Repository name | Libraries, University of Southern California |
Repository address | Los Angeles, California |
Repository email | cisadmin@lib.usc.edu |
Filename | etd-Molitor-20060928 |
Archival file | uscthesesreloadpub_Volume11/etd-Molitor-20060928-0.pdf |
Description
Title | Page 1 |
Contributing entity | University of Southern California |
Repository email | cisadmin@lib.usc.edu |
Full text | FUNCTIONAL BASED MULTI-LEVEL FLEXIBLE MODELS FOR MULTIVARIATE LONGITUDINAL DATA by Nuoo-Ting (Jassy) Molitor A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Ful¯llment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (BIOSTATISTICS) December 2006 Copyright 2006 Nuoo-Ting (Jassy) Molitor |