Statistics and Probability Commons^™

Cramer Type Moderate Deviations For Random Fields And Mutual Information Estimation For Mixed-Pair Random Variables, Aleksandr Beknazaryan

Electronic Theses and Dissertations

In this dissertation we first study Cramer type moderate deviation for partial sums of random fields by applying the conjugate method. In 1938 Cramer published his results on large deviations of sums of i.i.d. random variables after which a lot of research has been done on establishing Cramer type moderate and large deviation theorems for different types of random variables and for various statistics. In particular results have been obtained for independent non-identically distributed random variables for the sum of independent random to estimate the mutual information between two random variables. The estimates enjoy a central limit theorem under some …

The Role Of Glucose Level On The Performance Of The Framingham Risk Score, Uohna June Thiessen

Walden Dissertations and Doctoral Studies

Cardiovascular diseases (CVD) are responsible for more deaths than any other disease, continue to threaten the quality of life for many, and is a major burden to the health care system. The Framingham Heart Study (FHS) identified the major CVD risk factors that became essential to effective CVD screening strategies and the Framingham Risk Score (FRS), is used to assess CVD risk. Based on the concepts of the health behavior model and CVD as a cardiometabolic disorder, multivariate logistic regression analysis was used to evaluate the association between fasting blood glucose (FBG) levels and a CHD event, and to determine …

A Geographic Study Of Lung And Bronchus Cancer Rates In Kentucky, Gabriel Njoh Dikong

Walden Dissertations and Doctoral Studies

The average age-adjusted incidence and mortality rates of lung and bronchus cancer is 55% and 56% higher in Kentucky than the national averages in the United States, respectively. Populations with low income and educational attainment, and those who live close to the mining regions across Kentucky are more affected by the high prevalence and resulting mortality rates of lung and bronchus cancer. This study was conducted because of the high incidence of lung and bronchus cancer and resulting mortality rates in the state of Kentucky that may not be caused solely by social and demographic factors. The theoretical foundation for …

Development Of A Data-Driven Patient Engagement Score Using Finite Mixture Models, Eric Bae

Electronic Theses and Dissertations

Patient activation measure (PAM) is widely adopted by health care providers to access individual's knowledge, skill, and confidence for managing one's health and healthcare. Patient activation measure (PAM), licensed by Insignia Health, is widely adopted by health care providers to access individual's knowledge, skill, and confidence for managing one's health and healthcare. Multiple studies corroborate the effectiveness of activation measure in predicting most health behaviors, including preventive behaviors, healthy behaviors, self-management behaviors, and health information seeking. However, PAM is heavily dependent on subjective patient-reported data, which are often incomplete. The purpose of this study is to develop an objective statistical …

Measuring Trace Element Concentrations In Artiodactyl Cannonbones Using Portable X-Ray Fluorescence, Joshua L. Henderson

All Master's Theses

Artiodactyl bones are the most common faunal remains found in Washington prehistoric archaeology sites, but they are often too fragmented to accurately identify a family, genus, or species. Traditional faunal analysis can only organize unidentifiable bone fragments into size class, and chemical methods often require the destruction of bone samples. In this thesis research, I tested a new, nondestructive faunal analysis technique using portable X-ray fluorescence (pXRF) to measure trace element concentrations in comparative collection and archaeological bone samples. Using cannonbones from five different artiodactyl species, I collected trace element data from 50 comparative collection specimens and 18 archaeological specimens …

Quasilinearization And Boundary Value Problems At Resonance For Caputo Fractional Differential Equations, Saleh S. Almuthaybiri, Paul W. Eloe, Jeffrey T. Neugebauer

Mathematics Faculty Publications

The quasilinearization method is applied to a boundary value problem at resonance for a Caputo fractional differential equation. The method of upper and lower solutions is first employed to obtain the uniqueness of solutions of the boundary value problem at resonance. The shift argument is applied to show the existence of solutions. The quasilinearization algorithm is then developed and sequences of approximate solutions are constructed that converge monotonically and quadratically to the unique solution of the boundary value problem at resonance. Two applications are provided to illustrate the main results.

The Effect Of Neonicotinoids On Apis Mellifera: A Revisit, Qingchen Liang

Master's Theses and Doctoral Dissertations

Colony collapse disorder (CCD), which has caused high colony mortality rates in the European honeybee (Apis mellifera), is a pressing economical and ecological problem. I revisited Woodcock et al.'s (2017a) paper, "Country-specic Effects of Neonicotinoid Pesticides on Honey Bees and Wild Bees", in light of unsound statistical methods used in the original study. In the first part of this paper, I attempted to replicate the analysis underlying key findings in the original paper. In the second part, I reanalyzed the data using mostly non-parametric methods in order to obtain robust results. I did not find any evidence for a harmful …

Time-Reflective Text Representations For Semantic Evolution Tracking And Trend Analytics, Roberto Camacho Barranco

Open Access Theses & Dissertations

The extraction of significant, relevant, and useful trends from massive document collections, such as a streaming newswire or scientific publications, is a challenging and significant problem in many different fields, including intelligence analysis, recommendation systems, and scientific research. However, techniques that tackle trend analytics of such large text corpora are limited because research that addresses the temporal nature of these publications is still in its early stages. In this work, we first show that it is possible to capture the evolution of a story (or trend) by connecting the dots between different documents in a text corpus. The observed results …

Robust And Adaptive Design Approaches For Stepped Wedge Cluster Randomized Trials, Jijia Wang

Statistical Science Theses and Dissertations

The stepped wedge (SW) cluster randomized design has been increasingly employed by pragmatic trials in health services research. In this study, based on the GEE approach, I present a closed-form sample size that is applicable to both closed-cohort and cross-sectional SW trials with outcomes from the exponential family. On the other hand, I proposed a Bayesian adaptive design for cross-sectional SW cluster randomized trials. It is more adaptable than traditional designs because it allows early termination of the trial when interim data indicate that the intervention is sufficient efficacious or inefficacious. A decision to terminate or continue the trial will …

Estimation And Variable Selection In High-Dimensional Settings With Mismeasured Observations, Michael Byrd

Statistical Science Theses and Dissertations

Understanding high-dimensional data has become essential for practitioners across many disciplines. The general increase in ability to collect large amounts of data has prompted statistical methods to adapt for the rising number of possible relationships to be uncovered. The key to this adaptation has been the notion of sparse models, or, rather, models where most relationships between variables are assumed to be negligible at best. Driving these sparse models have been constraints on the solution set, yielding regularization penalties imposed on the optimization procedure. While these penalties have found great success, they are typically formulated with strong assumptions on the …

Modeling Stochastically Intransitive Relationships In Paired Comparison Data, Ryan Patrick Alexander Mcshane

Statistical Science Theses and Dissertations

If the Warriors beat the Rockets and the Rockets beat the Spurs, does that mean that the Warriors are better than the Spurs? Sophisticated fans would argue that the Warriors are better by the transitive property, but could Spurs fans make a legitimate argument that their team is better despite this chain of evidence?

We first explore the nature of intransitive (rock-scissors-paper) relationships with a graph theoretic approach to the method of paired comparisons framework popularized by Kendall and Smith (1940). Then, we focus on the setting where all pairs of items, teams, players, or objects have been compared to …

Spatial Boundary Detection And Estimation Of Jet Stream As A Key Factor For Tornado Environments, Mingzeng Sun

Legacy Theses & Dissertations (2009 - 2024)

Understanding the impact of spatial patterns and processing features on health is a key element in public health and epidemiology fields. This thesis investigates these fundamental tasks using two approaches: high dimensional Kolmogorov-Zurbenko Adaptive smoothing and spatial boundary identification by rolling variation algorithm.

The Effect Of Maternal Dietary Habits During Pregnancy On Neonate Leptin Methylation Patterns And Gestational Age, Sean Fitzpatrick

Legacy Theses & Dissertations (2009 - 2024)

The health of a newborn baby is inextricably linked to the health status of its mother and in turn the mother’s diet during pregnancy. Leptin (LEP) is an adipokine hormone involved in metabolism regulation and has been linked fetal development through the hypothalamic-pituitary-adrenal axis (HPA). Prior work suggests that gestational epigenetic alterations the LEP gene may be sensitive to adverse exposures during pregnancy, which in turn could explain variation in neonate outcomes. However, no prior work has examined this possibility explicitly. The objective of this study was to investigate the association between dietary patterns of mothers during pregnancy and their …

Depression, Sensation-Seeking Behavior And Violence As Mediators Of The Association Between Childhood Adversity And Substance Use Disorder, Calvin Wong

Legacy Theses & Dissertations (2009 - 2024)

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Evaluating The Impacts Of Antidepressant Use On The Risk Of Dementia, Ran Duan

Theses and Dissertations--Epidemiology and Biostatistics

Dementia is a clinical syndrome caused by neurodegeneration or cerebrovascular injury. Patients with dementia suffer from deterioration in memory, thinking, behavior and the ability to perform everyday activities. Since there are no cures or disease-modifying therapies for dementia, there is much interest in identifying modifiable risk factors that may help prevent or slow the progression of cognitive decline. Medications are a common focus of this type of research.

Importantly, according to a report from the Centers for Disease Control and Prevention (CDC), 19.1% of the population aged 60 and over report taking antidepressants during 2011-2014, and this number tends to …

Pawnee Dam Inflow Design Flood (Idf) Update And Stage-Frequency Curve Development Using Rmcrfa, Jennifer P. Christensen, Joshua J. Melliger

United States Geological Survey: Water Reports and Publications

Pawnee Dam is one of the ten Salt Creek Dams designed and built in the 1960s to mitigate flooding in Lincoln, Nebraska. This short paper illustrates the update of the Pawnee Dam inflow design flood (IDF) through calibration to recent high flow events and the development of its stage-frequency or hydrologic loading curve with the U.S. Army Corps of Engineers’ Risk Management Center Reservoir Frequency Analysis (RMC-RFA) model. The IDF update follows Engineering Regulation 1110-8-2, Inflow Design Flood for Dams and Reservoirs, including unit hydrograph peaking and two antecedent pool elevations. Background information on the original design of the dam …

On Cluster Robust Models, José Bayoán Santiago Calderón

CGU Theses & Dissertations

Cluster robust models are a kind of statistical models that attempt to estimate parameters considering potential heterogeneity in treatment effects. Absent heterogeneity in treatment effects, the partial and average treatment effect are the same. When heterogeneity in treatment effects occurs, the average treatment effect is a function of the various partial treatment effects and the composition of the population of interest. The first chapter explores the performance of common estimators as a function of the presence of heterogeneity in treatment effects and other characteristics that may influence their performance for estimating average treatment effects. The second chapter examines various approaches …

The Impact Of College Athletic Success On Donations And Applicant Quality, Benjamin Baumer, Andrew Zimbalist

Mathematics Sciences: Faculty Publications

For the 65 colleges and universities that participate in the Power Five athletic conferences (Pac 12, Big 10, SEC, ACC, and Big 12), the football and men’s basketball teams are highly visible. While these programs generate tens of millions of dollars in revenue annually, very few of them turn an operating “profit.” Their existence is thus justified by the claim that athletic success leads to ancillary benefits for the academic institution, in terms of both quantity (e.g., more applications, donations, and state funding) and quality (e.g., stronger applicants, lower acceptance rates, higher yields). Previous studies provide only weak support for …

Canadian Hockey Leagues Game-To-Game Performance, Nick R. Riccardi

Sport Management - All Scholarship

This study examines game-to-game performance of players across the three Canadian Hockey Leagues (Western Hockey League, Ontario Hockey League, and Quebec Major Junior Hockey League) for the 2017-2018 season. It tests the importance of factors such as rest, travel, weather conditions, and more. Data for this study were collected from each of the three CHL websites and from www.weatherunderground.com. The null hypotheses of different factors affecting performance were tested through regression models using Ordinary Least Squares. The dependent variables, used across different specifications, were on-ice performance variables such as points, goals, and penalty minutes on a per-game basis.

Combination Of Resampling Based Lasso Feature Selection And Ensembles Of Regularized Regression Models, Abhijeet R. Patil

Open Access Theses & Dissertations

In high-dimensional data, the performance of various classiers is largely dependent on the selection of important features. Most of the individual classiers using existing feature selection (FS) methods do not perform well for highly correlated data. Obtaining important

features using the FS method and selecting the best performing classier is a challenging task in high throughput data. In this research, we propose a combination of resampling based least absolute shrinkage and selection operator (LASSO) feature selection (RLFS)

and ensembles of regularized regression models (ERRM) capable of handling data with the high correlation structures. The ERRM boosts the prediction accuracy with …

Improving Access To Clean Water In Rural Ecuador: The Connection Between Willingness To Pay And Population Health, Micalea Leaska

Capstone Collection

Climate change is affecting social and environmental determinants of health through access to safe drinking water, safely managed sanitation systems, and access to health care services and the ability for individuals to break free from unsuitable circumstances. Ecological disturbances such as those caused by climate change can cause a shift in host vectors or a change in habitat that results in a greater likelihood of the pathogen coming in contact with humans. Water, sanitation, and hygiene (WASH) services and their accessibility to populations can directly impact a community’s vulnerability to diseases and limiting factors to increase economic growth. If rural …

Health Risk Tolerance As A Key Determinant Of (Un)Willingness To Behavior Change: Conceptualization And Scale Development, Hyoyeun Jun, Yan Jin

International Crisis and Risk Communication Conference

After the study of testing determinants of risk tolerance affecting information sharing, this study was conducted as a second step to actually develop the scale for risk tolerance. Firstly, this study followed qualitative steps, such as in-depth interview and focus group, to capture how public describes the situation when they are tolerating the risk, when they knew what the recommended behavior is to relieve the risk. Secondly, this study collected 1000 U.S. public sample for the survey questionnaire that are the items generated from the qualitative steps.

A New Independence Measure And Its Applications In High Dimensional Data Analysis, Chenlu Ke

Theses and Dissertations--Statistics

This dissertation has three consecutive topics. First, we propose a novel class of independence measures for testing independence between two random vectors based on the discrepancy between the conditional and the marginal characteristic functions. If one of the variables is categorical, our asymmetric index extends the typical ANOVA to a kernel ANOVA that can test a more general hypothesis of equal distributions among groups. The index is also applicable when both variables are continuous. Second, we develop a sufficient variable selection procedure based on the new measure in a large p small n setting. Our approach incorporates marginal information between …

Transforms In Sufficient Dimension Reduction And Their Applications In High Dimensional Data, Jiaying Weng

Theses and Dissertations--Statistics

The big data era poses great challenges as well as opportunities for researchers to develop efficient statistical approaches to analyze massive data. Sufficient dimension reduction is such an important tool in modern data analysis and has received extensive attention in both academia and industry.

In this dissertation, we introduce inverse regression estimators using Fourier transforms, which is superior to the existing SDR methods in two folds, (1) it avoids the slicing of the response variable, (2) it can be readily extended to solve the high dimensional data problem. For the ultra-high dimensional problem, we investigate both eigenvalue decomposition and minimum …

Unsupervised Learning In Phylogenomic Analysis Over The Space Of Phylogenetic Trees, Qiwen Kang

Theses and Dissertations--Statistics

A phylogenetic tree is a tree to represent an evolutionary history between species or other entities. Phylogenomics is a new field intersecting phylogenetics and genomics and it is well-known that we need statistical learning methods to handle and analyze a large amount of data which can be generated relatively cheaply with new technologies. Based on the existing Markov models, we introduce a new method, CURatio, to identify outliers in a given gene data set. This method, intrinsically an unsupervised method, can find outliers from thousands or even more genes. This ability to analyze large amounts of genes (even with missing …

Serial Testing For Detection Of Multilocus Genetic Interactions, Zaid T. Al-Khaledi

Theses and Dissertations--Statistics

A method to detect relationships between disease susceptibility and multilocus genetic interactions is the Multifactor-Dimensionality Reduction (MDR) technique pioneered by Ritchie et al. (2001). Since its introduction, many extensions have been pursued to deal with non-binary outcomes and/or account for multiple interactions simultaneously. Studying the effects of multilocus genetic interactions on continuous traits (blood pressure, weight, etc.) is one case that MDR does not handle. Culverhouse et al. (2004) and Gui et al. (2013) proposed two different methods to analyze such a case. In their research, Gui et al. (2013) introduced the Quantitative Multifactor-Dimensionality Reduction (QMDR) that uses the overall …

The Large Contraction Principle And Existence Of Periodic Solutions For Infinite Delay Volterra Difference Equations, Paul W. Eloe, Jaganmohan Jonnalagadda, Youssef Raffoul

Mathematics Faculty Publications

In this article, we establish sufficient conditions for the existence of periodic solutions of a nonlinear infinite delay Volterra difference equation. (See paper for equation.)

We employ a Krasnosel’skii type fixed point theorem, originally proved by Burton. The primary sufficient condition is not verifiable in terms of the parameters of the difference equation, and so we provide three applications in which the primary sufficient condition is verified.

Data Patterns Discovery Using Unsupervised Learning, Rachel A. Lewis

College of Graduate Studies: Theses & Dissertations

Self-care activities classification poses significant challenges in identifying children’s unique functional abilities and needs within the exceptional children healthcare system. The accuracy of diagnosing a child's self-care problem, such as toileting or dressing, is highly influenced by an occupational therapists’ experience and time constraints. Thus, there is a need for objective means to detect and predict in advance the self-care problems of children with physical and motor disabilities. We use clustering to discover interesting information from self-care problems, perform automatic classification of binary data, and discover outliers. The advantages are twofold: the advancement of knowledge on identifying self-care problems in …

Non-Marginal Decisions: A Novel Bayesian Multiple Testing Procedure, Noirrit Kiran Chandra, Sourabh Bhattacharya

Journal Articles

In this paper, we consider the problem of multiple testing where the hypotheses are dependent. In most of the existing literature, either Bayesian or non-Bayesian, the decision rules mainly focus on the validity of the test procedure rather than actually utilizing the dependency to increase efficiency. Moreover, the decisions regarding different hypotheses are marginal in the sense that they do not depend upon each other directly. However, in realistic situations, the hypotheses are usually dependent, and hence it is desirable that the decisions regarding the dependent hypotheses are taken jointly. In this article, we develop a novel Bayesian multiple testing …

Bayesian Hierarchical Meta-Analysis Of Asymptomatic Ebola Seroprevalence, Peter Brody-Moore

CMC Senior Theses

The continued study of asymptomatic Ebolavirus infection is necessary to develop a more complete understanding of Ebola transmission dynamics. This paper conducts a meta-analysis of eight studies that measure seroprevalence (the number of subjects that test positive for anti-Ebolavirus antibodies in their blood) in subjects with household exposure or known case-contact with Ebola, but that have shown no symptoms. In our two random effects Bayesian hierarchical models, we find estimated seroprevalences of 8.76% and 9.72%, significantly higher than the 3.3% found by a previous meta-analysis of these eight studies. We also produce a variation of this meta-analysis where we exclude …