Longitudinal studies are widely used in various fields, such as public health, clinic trials and financial data analysis. A major
challenge for longitudinal studies is repeated measurements from each subject, which cause time dependent correlation within subjects.
Generalized Estimating Equations can deal with correlated outcomes for longitudinal data through marginal effect. My model will base on
Generalized Estimating Equations with semi-parametric approach, providing a flexible structure for regression models: coefficients for
parametric covariates will be estimated and nuisance covariates will be fitted in kernel smoothers for non-parametric part. Profile kernel
estimator and the seemingly unrelated kernel estimator (SUR) will be used to deliver consistent and efficient semi-parametric estimators
comparing to parametric models. We provide simulation results for estimating semi-parametric models with one or multiple non-parametric
terms. In application part, we would like to focus on financial market: a credit card loan data will be used with the payment information for
each customer across 6 months, investigating whether gender, income, age or other factors will influence payment status significantly.
Furthermore, we propose model comparisons to evaluate whether our model should be fitted based on different levels of factors, such as male
and female or based on different types of estimating methods, such as parametric estimation or semi-parametric estimation. / A Dissertation submitted to the Department of Statistics in partial fulfillment of the requirements for the
degree of Doctor of Philosophy. / Fall Semester 2017. / November 15, 2017. / Includes bibliographical references. / Xufeng Niu, Professor Directing Dissertation; Yingmei Cheng, University Representative; Fred Huffer,
Committee Member; Minjing Tao, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_605038 |
| Contributors | Yang, Liu (author), Niu, Xufeng, 1954- (professor directing dissertation), Cheng, Yingmei (university representative), Huffer, Fred W. (Fred William) (committee member), Tao, Minjing (committee member), Florida State University (degree granting institution), College of Arts and Sciences (degree granting college), Department of Statistics (degree granting departmentdgg) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text, doctoral thesis |
| Format | 1 online resource (105 pages), computer, application/pdf |
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