Some of the material in is restricted to members of the community. By logging in, you may be able to gain additional access to certain collections or items. If you have questions about access or logging in, please use the form on the Contact Page.
Royal-Thomas, T. Y. N. (2011). Interrelating of Longitudinal Processes: An Empirical Example. Retrieved from http://purl.flvc.org/fsu/fd/FSU_migr_etd-1792
The Barker Hypothesis states that maternal and `in utero' attributes during pregnancy affects a child's cardiovascular health throughout life. We present an analysis of a unique longitudinal dataset from Jamaica that consists of three longitudinal processes: (i) Maternal longitudinal process- Blood pressure and anthropometric measurements at seven time-points on the mother during pregnancy. (ii) In Utero measurements - Ultrasound measurements of the fetus taken at six time-points during pregnancy. (iii) Birth to present process - Children's anthropometric and blood pressure measurements at 24 time-points from birth to 14 years. A comprehensive analysis of the interrelationship of these three longitudinal processes is presented using joint modeling for multivariate longitudinal profiles. We propose a new methodology of examining child's cardiovascular risk by extending a current view of likelihood estimation. Joint modeling of multivariate longitudinal profiles is done and the extension of the traditional likelihood method is utilized in this paper and compared to the maximum likelihood estimates. Our main goal is to examine whether the process in mothers predicts fetal development which in turn predicts the future cardiovascular health of the children. One of the difficulties with `in utero' and early childhood data is that certain variables are highly correlated and so using dimension reduction techniques are quite applicable in this scenario. Principal component analysis (PCA) is utilized in creating a smaller dimension of uncorrelated data which is then utilized in a longitudinal analysis setting. These principal components are then utilized in an optimal linear mixed model for longitudinal data which indicates that in utero and early childhood attributes predicts the future cardiovascular health of the children. This dissertation has added a body of knowledge to developmental origins of adult diseases and has supplied some significant results while utilizing a rich diversity of statistical methodologies.
Principal Component, Cardiovascular, Fetal Origins, Pseudolikelihood, Linear Mixed Model, Longitudinal
Date of Defense
May 16, 2011.
Submitted Note
A Dissertation Submitted to the Department of Statistics in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy.
Bibliography Note
Includes bibliographical references.
Publisher
Florida State University
Identifier
FSU_migr_etd-1792
Use and Reproduction
This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them.
Royal-Thomas, T. Y. N. (2011). Interrelating of Longitudinal Processes: An Empirical Example. Retrieved from http://purl.flvc.org/fsu/fd/FSU_migr_etd-1792
