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Nonlinear Hierarchical Models For Longitudinal Experimental Infection Studies, Michael David Singleton
Nonlinear Hierarchical Models For Longitudinal Experimental Infection Studies, Michael David Singleton
Theses and Dissertations--Epidemiology and Biostatistics
Experimental infection (EI) studies, involving the intentional inoculation of animal or human subjects with an infectious agent under controlled conditions, have a long history in infectious disease research. Longitudinal infection response data often arise in EI studies designed to demonstrate vaccine efficacy, explore disease etiology, pathogenesis and transmission, or understand the host immune response to infection. Viral loads, antibody titers, symptom scores and body temperature are a few of the outcome variables commonly studied. Longitudinal EI data are inherently nonlinear, often with single-peaked response trajectories with a common pre- and post-infection baseline. Such data are frequently analyzed with statistical methods …
Developments In Nonparametric Regression Methods With Application To Raman Spectroscopy Analysis, Jing Guo
Developments In Nonparametric Regression Methods With Application To Raman Spectroscopy Analysis, Jing Guo
Theses and Dissertations--Epidemiology and Biostatistics
Raman spectroscopy has been successfully employed in the classification of breast pathologies involving basis spectra for chemical constituents of breast tissue and resulted in high sensitivity (94%) and specificity (96%) (Haka et al, 2005). Motivated by recent developments in nonparametric regression, in this work, we adapt stacking, boosting, and dynamic ensemble learning into a nonparametric regression framework with application to Raman spectroscopy analysis for breast cancer diagnosis. In Chapter 2, we apply compound estimation (Charnigo and Srinivasan, 2011) in Raman spectra analysis to classify normal, benign, and malignant breast tissue. We explore both the spectra profiles and their derivatives to …