Statistics and Probability Commons^™

Application Of Support Vector Machine Modeling And Graph Theory Metrics For Disease Classification, Jessica M. Rudd

Published and Grey Literature from PhD Candidates

Disease classification is a crucial element of biomedical research. Recent studies have demonstrated that machine learning techniques, such as Support Vector Machine (SVM) modeling, produce similar or improved predictive capabilities in comparison to the traditional method of Logistic Regression. In addition, it has been found that social network metrics can provide useful predictive information for disease modeling. In this study, we combine simulated social network metrics with SVM to predict diabetes in a sample of data from the Behavioral Risk Factor Surveillance System. In this dataset, Logistic Regression outperformed SVM with ROC index of 81.8 and 81.7 for models with …

Trace Formulas For Perturbations Of Operators With Hilbert-Schmidt Resolvents, Bishnu Prasad Sedai

Mathematics & Statistics ETDs

In this dissertation, we study Taylor approximations of functions of operators with Hilbert-Schmidt resolvents. We obtain integral representations for traces of the respective Taylor remainders that are analogous to trace formulas obtained in the case of Schatten perturbations in [10, 11, 16].

Combining Biomarkers By Maximizing The True Positive Rate For A Fixed False Positive Rate, Allison Meisner, Marco Carone, Margaret Pepe, Kathleen F. Kerr

UW Biostatistics Working Paper Series

Biomarkers abound in many areas of clinical research, and often investigators are interested in combining them for diagnosis, prognosis and screening. In many applications, the true positive rate for a biomarker combination at a prespecified, clinically acceptable false positive rate is the most relevant measure of predictive capacity. We propose a distribution-free method for constructing biomarker combinations by maximizing the true positive rate while constraining the false positive rate. Theoretical results demonstrate good operating characteristics for the resulting combination. In simulations, the biomarker combination provided by our method demonstrated improved operating characteristics in a variety of scenarios when compared with …

Developing Biomarker Combinations In Multicenter Studies Via Direct Maximization And Penalization, Allison Meisner, Chirag R. Parikh, Kathleen F. Kerr

UW Biostatistics Working Paper Series

When biomarker studies involve patients at multiple centers and the goal is to develop biomarker combinations for diagnosis, prognosis, or screening, we consider evaluating the predictive capacity of a given combination with the center-adjusted AUC (aAUC), a summary of conditional performance. Rather than using a general method to construct the biomarker combination, such as logistic regression, we propose estimating the combination by directly maximizing the aAUC. Furthermore, it may be desirable to have a biomarker combination with similar predictive capacity across centers. To that end, we allow for penalization of the variability in center-specific performance. We demonstrate good asymptotic properties …

Socioeconomic Status, Air Quality And Geographic Variation In Emergency Room Visits For Acute Bronchitis On The California Central Coast, Sean Lang-Brown, Heather W. Starnes, Gary B. Hughes

Symposium

IMPORTANCE: Analysis of geospatial variation in acute bronchitis due to socioeconomic and environmental factors can allow the efficient delivery of resources to populations most at risk.

OBJECTIVE: We sought to determine if small scale variation in socioeconomic factors and emergency room (ER) visits for acute bronchitis are associated in small cities or rural communities. We also modeled the effects of air quality on daily rates of ER visits for acute bronchitis in the context of socioeconomic factors to investigate modifying relationships.

DESIGN, SETTING, AND PARTICIPANTS: We examined ER visits for acute bronchitis in San Luis Obispo and Santa Barbara counties …

High Order Hermite And Sobolev Discontinuous Galerkin Methods For Hyperbolic Partial Differential Equations, Adeline Kornelus

Mathematics & Statistics ETDs

Many real-world problems involving dynamics of solid or fluid bodies can be modeled by hyperbolic partial differential equations (PDEs). Up to this point, only solutions to selected PDEs are available. Many PDEs are physically or geometrically complex, resulting in difficulties computing the analytical solutions. In this thesis, we focus on numerical methods for approximating solutions to hyperbolic PDEs. Long-term simulation for the motion of the body described by the PDE requires a method that is not only robust and efficient, but also produces small error because the error will be propagated and accumulated over the course of the simulation. Therefore, …

Merging Peg Solitaire In Graphs, John Engbers, Ryan Weber

Mathematics, Statistics and Computer Science Faculty Research and Publications

Peg solitaire has recently been generalized to graphs. Here, pegs start on all but one of the vertices in a graph. A move takes pegs on adjacent vertices x and y, with y also adjacent to a hole on vertex z, and jumps the peg on x over the peg ony to z, removing the peg on y. The goal of the game is to reduce the number of pegs to one.

We introduce the game merging peg solitaire on graphs, where a move takes pegs on vertices x and z (with a hole on y) and merges them to …

Testing The Independence Hypothesis Of Accepted Mutations For Pairs Of Adjacent Amino Acids In Protein Sequences, Jyotsna Ramanan, Peter Revesz

School of Computing: Faculty Publications

Evolutionary studies usually assume that the genetic mutations are independent of each other. However, that does not imply that the observed mutations are independent of each other because it is possible that when a nucleotide is mutated, then it may be biologically beneficial if an adjacent nucleotide mutates too. With a number of decoded genes currently available in various genome libraries and online databases, it is now possible to have a large-scale computer-based study to test whether the independence assumption holds for pairs of adjacent amino acids. Hence the independence question also arises for pairs of adjacent amino acids within …

Peripheral Inflammation, Apolipoprotein E4, And Amyloid-Β Interact To Induce Cognitive And Cerebrovascular Dysfunction, Felecia M. Marottoli, Yuriko Katsumata, Kevin P. Koster, Riya Thomas, David W. Fardo, Leon M. Tai

Biostatistics Faculty Publications

Cerebrovascular dysfunction is rapidly reemerging as a major process of Alzheimer’s disease (AD). It is, therefore, crucial to delineate the roles of AD risk factors in cerebrovascular dysfunction. While apolipoprotein E4 (APOE4), Amyloid-β (Aβ), and peripheral inflammation independently induce cerebrovascular damage, their collective effects remain to be elucidated. The goal of this study was to determine the interactive effect of APOE4, Aβ, and chronic repeated peripheral inflammation on cerebrovascular and cognitive dysfunction in vivo. EFAD mice are a well-characterized mouse model that express human APOE3 (E3FAD) or APOE4 (E4FAD) and overproduce human Aβ42 via expression of …

Visualizing Lab And Phenotype Associations Using Phewas And Electronic Health Records, Brenda Emerson, Miriam Goldman, Sahiti Kolli

Honors Projects

As the digitization of patient health records is becoming more common, we are given a great opportunity to analyze these records and hopefully make discoveries about diseases or medicines. Being given large datasets of Electronic Health Records, I and two other students decided to look for novel phenotype associations with mean lab values, look to see whether the presence of a lab had associations with a phenotype, and create an interactive application to visual the associations between labs and phenotypes.

Burden Of Atopic Dermatitis In The United States: Analysis Of Healthcare Claims Data In The Commercial, Medicare, And Medi-Cal Databases, Sulena Shrestha, Raymond Miao, Li Wang, Jingdong Chao, Huseyin Yuce, Wenhui Wei

Publications and Research

Comparative data on the burden of atopic dermatitis (AD) in adults relative to the general population are limited. We performed a large-scale evaluation of the burden of disease among US adults with AD relative to matched non-AD controls, encompassing comorbidities, healthcare resource utilization (HCRU), and costs, using healthcare claims data. The impact of AD disease severity on these outcomes was also evaluated.

Comparison Of Two Methods In Estimating Standard Error Of Simulated Moments Estimators For Generalized Linear Mixed Models, Danielle K. Duran

Mathematics & Statistics ETDs

We consider standard error of the method of simulated moment (MSM) estimator for generalized linear mixed models (GLMM). Parametric bootstrap (PB) has been used to estimate the covariance matrix, in which we use the estimates to generate the simulated moments. To avoid the bias introduced by estimating the parameters and to deal with the correlated observations, (Lu, 2012) proposed a multi-stage block nonparametric bootstrap to estimate the standard errors. In this research, we compare PB and nonparametric bootstrap methods (NPB) in estimating the standard errors of MSM estimators for GLMM. Simulation results show that when the group size is large, …

A Perspective On The Challenges And Issues In Developing Biomarkers For Human Allergic Risk Assessments, Ying Mu, Dianne E. Godar, Stephen Merrill

Mathematics, Statistics and Computer Science Faculty Research and Publications

No abstract provided.

Bayesian Artificial Neural Networks In Health And Cybersecurity, Hansapani Sarasepa Rodrigo

USF Tampa Graduate Theses and Dissertations

Being in the era of Big data, the applicability and importance of data-driven models like artificial neural network (ANN) in the modern statistics have increased substantially. In this dissertation, our main goal is to contribute to the development and the expansion of these ANN models by incorporating Bayesian learning techniques. We have demonstrated the applicability of these Bayesian ANN models in interdisciplinary research including health and cybersecurity.

Breast cancer is one of the leading causes of deaths among females. Early and accurate diagnosis is a critical component which decides the survival of the patients. Including the well known ``Gail Model", …

Mining Diverse Consumer Preferences For Bundling And Recommendation, Ha Loc Do

Dissertations and Theses Collection

That consumers share similar tastes on some products does not guarantee their agreement on other products. Therefore, both similarity and dierence should be taken into account for a more rounded view on consumer preferences. This manuscript focuses on mining this diversity of consumer preferences from two perspectives, namely 1) between consumers and 2) between products. Diversity of preferences between consumers is studied in the context of recommendation systems. In some preference models, measuring similarities in preferences between two consumers plays the key role. These approaches assume two consumers would share certain degree of similarity on any products, ignoring the fact …

Letter To The Editor, Jarrod Bailey

Validation of Animal Experimentation Collection

It seems clear that heeding the opinions and recommendations of experienced neuroscientists such as Professor Beuter, the well-argued probable opinion of the time-travelling Parkinson, and Grimm and Eggel’s demands for high animal welfare and honest and realistic harm–benefit analyses, will be of paramount importance for the advancement and evolution of experiments involving NHPs, particularly in neuroscience. This will benefit animals and humans alike.

Motion-Capture-Based Hand Gesture Recognition For Computing And Control, Andrew Gardner

Doctoral Dissertations

This dissertation focuses on the study and development of algorithms that enable the analysis and recognition of hand gestures in a motion capture environment. Central to this work is the study of unlabeled point sets in a more abstract sense. Evaluations of proposed methods focus on examining their generalization to users not encountered during system training.

In an initial exploratory study, we compare various classification algorithms based upon multiple interpretations and feature transformations of point sets, including those based upon aggregate features (e.g. mean) and a pseudo-rasterization of the capture space. We find aggregate feature classifiers to be balanced across …

Lecture Notes For Openstax Introductory Statistics, Daphne Skipper, Neal Smith, Robert Scott, Marvalisa Payne, Christopher Terry

Mathematics Ancillary Materials

Authors' Description:

"Rising textbook costs are a potential barrier to student progression and retention. Therefore, a group of faculty in the department of Mathematics at Augusta University has decided to adopt an open textbook for use in an Elementary Statistics course.

We have developed a set of materials to accompany the OpenStax Introductory Statistics textbook by Illowsky and Dean including lecture/study notes and projects.

These materials are meant as a supplement for teachers and learners who are using the OpenStax Introductory Statistics textbook by Illowsky and Dean. These materials also incorporate the use of other technologies (R and Excel) in …

Failure Of Care Acquisition: Identifying Risk Factors In American Health Disparities, Nicholas Downing, Mamunur Rashid

Student Research

We examined the effects of various demographic and socioeconomic risk factors that influence an adult's decision not to obtain medical care in the United States utilizing data from the 2015 National Health Interview Survey (NHIS). Bivariate analysis and multivariate logistic regression revealed that family income, insurance status and whether one worries about paying medical bills make individuals nearly 80% less likely to obtain care than their counterparts. This study provides evidence that certain risk factors, especially those directly related to one's socioeconomic status, may put individuals at greater risk for failure to obtain care. Interventions in policy may be needed …

Elementary Statistics (Augusta), Neal Smith, Daphne Skipper, Marvalisa Payne, Robert Scott, Christopher Terry

Mathematics Grants Collections

This Grants Collection for Elementary Statistics was created under a Round Four ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

• Linked Syllabus
• Initial Proposal
• Final Report