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Articles 1 - 7 of 7
Full-Text Articles in Physical Sciences and Mathematics
Potential Alzheimer's Disease Plasma Biomarkers, Taylor Estepp
Potential Alzheimer's Disease Plasma Biomarkers, Taylor Estepp
Theses and Dissertations--Epidemiology and Biostatistics
In this series of studies, we examined the potential of a variety of blood-based plasma biomarkers for the identification of Alzheimer's disease (AD) progression and cognitive decline. With the end goal of studying these biomarkers via mixture modeling, we began with a literature review of the methodology. An examination of the biomarkers with demographics and other health factors found evidence of minimal risk of confounding along the causal pathway from biomarkers to cognitive performance. Further study examined the usefulness of linear combinations of biomarkers, achieved via partial least squares (PLS) analysis, as predictors of various cognitive assessment scores and clinical …
Investigations Into The Genetics Of Mixed Pathologies In Dementia, Adam Dugan
Investigations Into The Genetics Of Mixed Pathologies In Dementia, Adam Dugan
Theses and Dissertations--Epidemiology and Biostatistics
Alzheimer’s disease (AD) is an irreversible, progressive brain disorder that leads to a loss of memory and thinking skills. While tremendous progress has been made in our understanding of the genetics underlying AD, currently known genetic variants explain only approximately 30% of the heritable risk of developing AD. One hurdle to AD research is that it can only be definitively diagnosed at autopsy, making cruder, clinic-based diagnoses more common. In recent years, several brain pathologies that mimic AD’s clinical presentation have been identified including brain arteriolosclerosis, hippocampal sclerosis (HS), and, most recently, limbic-predominant age-related TDP-43 encephalopathy (LATE). It has become …
Improved Methods And Selecting Classification Types For Time-Dependent Covariates In The Marginal Analysis Of Longitudinal Data, I-Chen Chen
Theses and Dissertations--Epidemiology and Biostatistics
Generalized estimating equations (GEE) are popularly utilized for the marginal analysis of longitudinal data. In order to obtain consistent regression parameter estimates, these estimating equations must be unbiased. However, when certain types of time-dependent covariates are presented, these equations can be biased unless an independence working correlation structure is employed. Moreover, in this case regression parameter estimation can be very inefficient because not all valid moment conditions are incorporated within the corresponding estimating equations. Therefore, approaches using the generalized method of moments or quadratic inference functions have been proposed for utilizing all valid moment conditions. However, we have found that …
Improved Standard Error Estimation For Maintaining The Validities Of Inference In Small-Sample Cluster Randomized Trials And Longitudinal Studies, Whitney Ford Tanner
Improved Standard Error Estimation For Maintaining The Validities Of Inference In Small-Sample Cluster Randomized Trials And Longitudinal Studies, Whitney Ford Tanner
Theses and Dissertations--Epidemiology and Biostatistics
Data arising from Cluster Randomized Trials (CRTs) and longitudinal studies are correlated and generalized estimating equations (GEE) are a popular analysis method for correlated data. Previous research has shown that analyses using GEE could result in liberal inference due to the use of the empirical sandwich covariance matrix estimator, which can yield negatively biased standard error estimates when the number of clusters or subjects is not large. Many techniques have been presented to correct this negative bias; However, use of these corrections can still result in biased standard error estimates and thus test sizes that are not consistently at their …
An Exploratory Statistical Method For Finding Interactions In A Large Dataset With An Application Toward Periodontal Diseases, Joshua Lambert
An Exploratory Statistical Method For Finding Interactions In A Large Dataset With An Application Toward Periodontal Diseases, Joshua Lambert
Theses and Dissertations--Epidemiology and Biostatistics
It is estimated that Periodontal Diseases effects up to 90% of the adult population. Given the complexity of the host environment, many factors contribute to expression of the disease. Age, Gender, Socioeconomic Status, Smoking Status, and Race/Ethnicity are all known risk factors, as well as a handful of known comorbidities. Certain vitamins and minerals have been shown to be protective for the disease, while some toxins and chemicals have been associated with an increased prevalence. The role of toxins, chemicals, vitamins, and minerals in relation to disease is believed to be complex and potentially modified by known risk factors. A …
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 …
The Psychological Impacts Of False Positive Ovarian Cancer Screening: Assessment Via Mixed And Trajectory Modeling, Amanda T. Wiggins
The Psychological Impacts Of False Positive Ovarian Cancer Screening: Assessment Via Mixed And Trajectory Modeling, Amanda T. Wiggins
Theses and Dissertations--Epidemiology and Biostatistics
Ovarian cancer (OC) is the fifth most common cancer among women and has the highest mortality of any cancer of the female reproductive system. The majority (61%) of OC cases are diagnosed at a distant stage. Because diagnoses occur most commonly at a late-stage and prognosis for advanced disease is poor, research focusing on the development of effective OC screening methods to facilitate early detection in high-risk, asymptomatic women is fundamental in reducing OC-specific mortality. Presently, there is no screening modality proven efficacious in reducing OC-mortality. However, transvaginal ultrasonography (TVS) has shown value in early detection of OC. TVS presents …