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- All Subjects: Functional Data Analysis
- Creators: Suk, Hye Won
Description
This paper investigates a relatively new analysis method for longitudinal data in the framework of functional data analysis. This approach treats longitudinal data as so-called sparse functional data. The first section of the paper introduces functional data and the general ideas of functional data analysis. The second section discusses the analysis of longitudinal data in the context of functional data analysis, while considering the unique characteristics of longitudinal data such, in particular sparseness and missing data. The third section introduces functional mixed-effects models that can handle these unique characteristics of sparseness and missingness. The next section discusses a preliminary simulation study conducted to examine the performance of a functional mixed-effects model under various conditions. An extended simulation study was carried out to evaluate the estimation accuracy of a functional mixed-effects model. Specifically, the accuracy of the estimated trajectories was examined under various conditions including different types of missing data and varying levels of sparseness.
ContributorsWard, Kimberly l (Author) / Suk, Hye Won (Thesis advisor) / Aiken, Leona (Committee member) / Grimm, Kevin (Committee member) / Arizona State University (Publisher)
Created2016
Description
Socioeconomic status (SES) is linked with poorer health outcomes across the range of SES. The Reserve Capacity Model (RCM) proposes that low SES fuels repeated and/or chronic exposure to elevated levels of stress, producing deleterious emotional, psychological, social, and physiological changes that result in development of disease over time. The RCM further asserts that a relative lack of social and psychological resources, including efficacy and social support, among low SES individuals accounts for their greater vulnerability to the effects of stress. Although the links between stress, reserve capacity, and health outcomes are framed in the RCM as an ongoing process that produces disease, the majority of investigations testing the model have not examined its utility in explaining 1) coping with daily stressors or 2) symptom flares among individuals managing a chronic illness. This study investigated the effects of SES, reflected in income level, on the: 1) levels of daily financial events and financial worry; 2) relations between daily financial worry and symptoms of pain and fatigue; and 3) extent to which daily coping efficacy and social support mediated the daily financial worry-symptom relation across 21 daily diary reports collected from 220 individuals with fibromyalgia (FM). Simple correlations showed that income was inversely related to frequency of financial events and level of financial worry across 21 days. Results from multilevel models indicated that daily increases in financial worry were unrelated to pain regardless of income level, but were related to increased fatigue among individuals with lower relative to higher income. Daily efficacy and support mediated the relations between financial worry and pain and fatigue, but the extent of mediation did not differ based on high versus low income level. Taken together, the findings suggest that individuals of low versus high income encounter more frequent financial stress and experience greater daily fatigue exacerbation related to that stress, in line with the RCM. Over time, the greater exposure and reactivity to financial strain may account for the inverse relation between income and disability among those with chronic pain.
ContributorsMoore, Shannon Victoria (Author) / Davis, Mary C. (Thesis advisor) / Luecken, Linda J. (Committee member) / Suk, Hye Won (Committee member) / Arizona State University (Publisher)
Created2017