Statistics and Probability Commons^™

Assessing The Impact Of Incorporating Residential Histories Into The Spatial Analysis Of Cancer Risk, Anny-Claude Joseph

Theses and Dissertations

In many spatial epidemiologic studies, investigators use residential location at diagnosis as a surrogate for unknown environmental exposures or as a geographic basis for assigning measured exposures. Inherently, they make assumptions about the timing and location of pertinent exposures which may prove problematic when studying long latency diseases such as cancer.

In this work we explored how the association between environmental exposures and disease risk for long-latency health outcomes like cancer is affected by residential mobility. We used simulation studies conditioned on real data to evaluate the extent to which the commonly held assumption of no residential mobility 1) affected …

Methods For Joint Normalization And Comparison Of Hi-C Data, John C. Stansfield

Theses and Dissertations

The development of chromatin conformation capture technology has opened new avenues of study into the 3D structure and function of the genome. Chromatin structure is known to influence gene regulation, and differences in structure are now emerging as a mechanism of regulation between, e.g., cell differentiation and disease vs. normal states. Hi-C sequencing technology now provides a way to study the 3D interactions of the chromatin over the whole genome. However, like all sequencing technologies, Hi-C suffers from several forms of bias stemming from both the technology and the DNA sequence itself. Several normalization methods have been developed for normalizing …

Latent Growth Model Approach To Characterize Maternal Prenatal Dna Methylation Trajectories, Dana Lapato

Theses and Dissertations

Background. DNA methylation (DNAm) is a removable chemical modification to the DNA sequence intimately associated with genomic stability, cellular identity, and gene expression. DNAm patterning reflects joint contributions from genetic, environmental, and behavioral factors. As such, differences in DNAm patterns may explain interindividual variability in risk liability for complex traits like major depression (MD). Hundreds of significant DNAm loci have been identified using cross-sectional association studies. This dissertation builds on that foundational work to explore novel statistical approaches for longitudinal DNAm analyses. Methods. Repeated measures of genome-wide DNAm and social and environmental determinants of health were collected up to six …

Genome-Wide Systems Genetics Of Alcohol Consumption And Dependence, Kristin Mignogna

Theses and Dissertations

Widely effective treatment for alcohol use disorder is not yet available, because the exact biological mechanisms that underlie this disorder are not completely understood. One way to gain a better understanding of these mechanisms is to examine the genetic frameworks that contribute to the risk for developing this disorder. This dissertation examines genetic association data in combination with gene expression networks in the brain to identify functional groups of genes associated with alcohol consumption and dependence.

The first study took advantage of the behavioral complexity of human samples, and experimental capabilities provided by mouse models, by co-analyzing gene expression networks …

Spectral Methods For The Detection And Characterization Of Topologically Associated Domains, Kellen Garrison Cresswell

Theses and Dissertations

The three-dimensional (3D) structure of the genome plays a crucial role in gene expression regulation. Chromatin conformation capture technologies (Hi-C) have revealed that the genome is organized in a hierarchy of topologically associated domains (TADs), sub-TADs, and chromatin loops which is relatively stable across cell-lines and even across species. These TADs dynamically reorganize during development of disease, and exhibit cell- and conditionspecific differences. Identifying such hierarchical structures and how they change between conditions is a critical step in understanding genome regulation and disease development. Despite their importance, there are relatively few tools for identification of TADs and even fewer for …

Statistical Designs For Network A/B Testing, Victoria V. Pokhilko

Theses and Dissertations

A/B testing refers to the statistical procedure of experimental design and analysis to compare two treatments, A and B, applied to different testing subjects. It is widely used by technology companies such as Facebook, LinkedIn, and Netflix, to compare different algorithms, web-designs, and other online products and services. The subjects participating in these online A/B testing experiments are users who are connected in different scales of social networks. Two connected subjects are similar in terms of their social behaviors, education and financial background, and other demographic aspects. Hence, it is only natural to assume that their reactions to online products …

Applying Conditional Distributions To Individuals: Using Latent Variable Models, Feng Ji

Theses and Dissertations

This study proposes a new method to interpret individual results of psychological test batteries. The Mahalanobis distance is a commonly-used measure of how unusual an individual’s profile of scores is compared to a population of score profiles. In models in which there is a set of predictors and a set of dependent variables (e.g., cognitive abilities predicting academic abilities), it is useful to distinguish between a profile of dependent scores that is unusual because its profile of predictor scores is unusual and a profile of dependent scores that is unusual even after controlling for the predictors. The conditional Mahalanobis distance …

The Epsilon-Skew Exponentiated Beta Distribution, Chary Akmyradov

Theses and Dissertations

In this dissertation, we develop the Epsilon Skew Exponentiated Beta Distribution. This distribution is a bimodal skew distribution with shape, location, and skewness parameters. This distribution is useful in applications with bimodal data, such as in the biological data. The shape properties and the effects of parameters are discussed. Furthermore, we derived the mode and the expected values, mean and variance. In addition, we derive the moment generating function and develop the likelihood function. Parameter estimates are also developed. Then, we develop a simulation to generate the Epsilon Skew Exponentiated Beta random variables and use this new distribution in real …

Determining The Relationship Between Aging And Oxidative Stress In A Drosophila Melanogaster P38 Kb Framework, Aleksandra J. Majewski

Theses and Dissertations

Aging is inevitable for all organisms and can be characterized by degeneration of tissue, adecrease in motor function, and impaired stress response. In humans, it is often accompanied by an increased propensity for age related diseases. While all adults experience biological aging (senescence) not all adults experience age-associated disease. Thus, we claim these are not normal prospects of aging. Although the implications of aging are well understood, the molecular underpinnings for these processes remain elusive. As advances in medical science have been successful at prolonging lifespan, they concurrently extend the amount of time spend in diseased states. If we wish …

Clustering Biological Data With Self-Adjusting High-Dimensional Sieve, Josselyn Gonzalez

Theses and Dissertations

Data classification as a preprocessing technique is a crucial step in the analysis and understanding of numerical data. Cluster analysis, in particular, provides insight into the inherent patterns found in data which makes the interpretation of any follow-up analyses more meaningful. A clustering algorithm groups together data points according to a predefined similarity criterion. This allows the data set to be broken up into segments which, in turn, gives way for a more targeted statistical analysis. Cluster analysis has applications in numerous fields of study and, as a result, countless algorithms have been developed. However, the quantity of options makes …

The Impact Of Changing Requirements, James C. Ellis

Theses and Dissertations

The fundamental purpose of an Engineering Change Proposal (ECP) is to change the requirements of a contract. To build in flexibility, the acquisition practice is to estimate a dollar value to hold in reserve after the contract is awarded. There appears to be no empirical-based method for estimating this ECP withhold in the literature. Using the Cost Assessment Data Enterprise (CADE) database, 533 contracts were randomly selected to build two regression models: one to predict the likelihood of a contract experiencing an ECP, and the other to determine the expected median percent increase in baseline contract cost if an ECP …

Satellite Communications In The V And W Band: Tropospheric Effects, Bertus A. Shelters

Theses and Dissertations

An investigation into the use of Weather Cubes compiled by the atmospheric characterization package, Laser Environmental Effects Definition and Reference (LEEDR), to develop accurate, long-term attenuation statistics for link-budget analysis is presented. A Weather Cube is a three-dimensional mesh of numerical weather prediction (NWP) data plus LEEDR calculations that allows for the quantification of rain, cloud, aerosol, and molecular effects at any UV to RF wavelength on any path contained within the cube. The development of this methodology is motivated by the potential use of V (40-75 GHz) and W (75-110 GHz) band frequencies for the satellite communication application, as …

Analysis Of A Voting Method For Ranking Network Centrality Measures On A Node-Aligned Multiplex Network, Kyle S. Wilkinson

Theses and Dissertations

Identifying relevant actors using information gleaned from multiple networks is a key goal within the context of human aspects of military operations. The application of a voting theory methodology for determining nodes of critical importance—in ranked order of importance—for a node-aligned multiplex network is demonstrated. Both statistical and qualitative analyses on the differences of ranking outcomes under this methodology is provided. As a corollary, a multilayer network reduction algorithm is investigated within the context of the proposed ranking methodology. The application of the methodology detailed in this thesis will allow meaningful rankings of relevant actors to be produced on a …

Characterization Of Ambient Noise, Rachel C. Ramirez

Theses and Dissertations

An Air Force sponsor is interested in improving an acoustic detection model by providing better estimates on how to characterize the background noise of various environments. This would inform decision makers on the probability of acoustic detection of different systems of interest given different levels of noise. Data mining and statistical learning techniques are applied to a National Park Service acoustic summary data set to find overall trends over varying environments. Linear regression, conditional inference trees, and random forest techniques are discussed. Findings indicate only sixteen geospatial variables at different resolutions are necessary to characterize the first ten ⅓ octave …

Modeling Multimodal Failure Effects Of Complex Systems Using Polyweibull Distribution, Daniel A. Timme

Theses and Dissertations

The Department of Defense (DoD) enlists multiple complex systems across each of their departments. Between the aging systems going through an overhaul and emerging new systems, quality assurance to complete the mission and secure the nation‘s objectives is an absolute necessity. The U.S. Air Force‘s increased interest in Remotely Piloted Aircraft (RPA) and the Space Warfighting domain are current examples of complex systems that must maintain high reliability and sustainability in order to complete missions moving forward. DoD systems continue to grow in complexity with an increasing number of components and parts in more complex arrangements. Bathtub-shaped hazard functions arise …

Looking Past The Spark To Find The Fuel Of The Arab Spring Fire, Luke M. Brantley

Theses and Dissertations

The field of statistical conflict prediction addresses region-wide analysis in eras of stable conflict and peace. This study improves upon those prediction rates in times of volatile conflict and peace seen during the Arab Spring of 2011 to 2015. During this time, higher rates of conflict transition in certain Middle Eastern and North African countries occurred than normally observed in previous studies. Due to the fact that previous prediction models decrease in accuracy during times of volatile conflict transition and since the proper strategy for handling the Arab Spring has been highly debated, this study considers alterations to previous studies …

They're Only Nuclear Weapons: An Exploratory Analysis Of Safety Climate Within The Nuclear Enterprise, Brandon M. Clements

Theses and Dissertations

By possessing nuclear weapons, the United States Air Force is inherently exposed to extreme safety concerns. With multiple setbacks in recent years (e.g., unauthorized transport of nuclear weapons, cheating scandals, and career dissatisfaction), some have begun to wonder how safe the nuclear enterprise truly is. Building upon the concept of safety climate, this study explores safety climate constructs and trends associated with current nuclear maintenance safety climate survey data.

Forecasting Country Conflict Within Modified Combatant Command Regions Using Statistical Learning Methods, Sarah Neumann

Theses and Dissertations

Conflict forecasts are crucial to Combatant Commanders’ understanding of the dynamic environment encompassing countries within their area of responsibility. The current structure of the Combatant Commands (COCOMs) is rooted in geography by grouping nations in geographic proximity to the same regional command. However, leaders today question the effectiveness of the current structure. A novel modified k-means clustering algorithm is developed and implemented that groups countries based on data similarities and geographic proximity resulting in new COCOM groupings that improve conflict forecasts. The data spans various political, military, economic, and social characteristics of countries, and is used to develop conditional logistic …

Dimension Reduction For Classification With Many Covariates And Pathway Activity Level Estimation, Seungchul Baek

Theses and Dissertations

The development of science and technology has enabled the use of more covariates. As a result, it has become more difficult to identify dependencies among many covariates. Dimension reduction provides an efficient way to handle this issue by summarizing the effect of covariates via a few linear combinations of covariates. In this dissertation, two methodologies for real-life problems are provided by using dimension reduction equipped with semiparametric theory. The use of semiparametrics allows maximal flexibility of the model by letting some features of the model completely unspecified, while we still enjoy the interpretability of the model through estimating the parameters …

Discovery Of Community Structures In Static And Dynamic Networks, Shiwen Shen

Theses and Dissertations

With the development of computer technology, researchers are able to observe and collect enormous amount of data, where the independent and identical distributed assumption is violated. For example, in sociology, individuals in an organization interact with each other to change the underlying social structure; in biology, understanding the gene-gene interaction helps researchers to detect potential diseases; in politics, voters are mutually influenced before the election via private/public speeches and parades, which might ultimately change the election results. It is crucial to study how individuals interact with each other from the data, which would lead to tremendous contributions to the society. …

A Rotatable Asymmetric Variable Compensation Mirt Model, Xinchu Zhao

Theses and Dissertations

The purpose of this study is to develop, estimate, and interpret a new variable compensation multidimensional item response theory (MIRT) model, named the Rotatable Asymmetric Variable Compensation Model (RAVCM), that allows for transformation between different correlation structures. Since the model is rotatable like the common compensatory models (CM), it is not necessary to specify or estimate the correlation of abilities to recover the model. Also, it can approximate the existing MIRT models well. In simulation, the RAVCM is shown to estimate the parameters with small error, especially when the non-compensatory model (NCM) is the true model and the correlation of …

Penalized Mixed-Effects Ordinal Response Models For High-Dimensional Genomic Data In Twins And Families, Amanda E. Gentry

Theses and Dissertations

The Brisbane Longitudinal Twin Study (BLTS) was being conducted in Australia and was funded by the US National Institute on Drug Abuse (NIDA). Adolescent twins were sampled as a part of this study and surveyed about their substance use as part of the Pathways to Cannabis Use, Abuse and Dependence project. The methods developed in this dissertation were designed for the purpose of analyzing a subset of the Pathways data that includes demographics, cannabis use metrics, personality measures, and imputed genotypes (SNPs) for 493 complete twin pairs (986 subjects.) The primary goal was to determine what combination of SNPs and …

Goodness Of Fit Via Residual Plots In Item Response Theory, Bryonna Bowen

Theses and Dissertations

Goodness-of-fit criteria developed for the evaluation of item response functions have been examined by many scholars using different theories and criteria. A number of potential graphical analysis approaches, such as residual plots, have been described in literature, but have received little attention from researchers. While many tests of goodness-of-fit are available, those that incorporate the analysis of residuals may be most useful. The unmistakable presence of a pattern in the residual plot for the logistic model item response functions even when we know the model fits raises a red flag up and calls for greater analysis. This study explores different …

Adjusting For Mis-Reporting In Count Data, Gelareh Rahimighazikalayeh

Theses and Dissertations

Any counting system is prone to recording errors including underreporting and overreporting. Ignoring the misreporting pattern in count data can give rise to bias in the estimation of model parameters. Accordingly, Poisson, negative binomial and generalized Poisson regression have been expanded in some instances to capture reporting biases. However, to our knowledge, no program has been developed to allow users to apply all of these models when needed. In the first part of the dissertation, we review the available models for underreported counts and develop a Stata command to estimate Poisson, negative binomial and generalized Poisson regression models for underreported …

The South Carolina Safety Belt Study: Large-Scale Location Sampling, Stephanie Jones

Theses and Dissertations

The South Carolina Safety Belt Study is a statewide survey completed yearly to assess the prevalence of safety belt usage on of South Carolina roads through observations from different locations across the state. Every five years the sites for observation are resampled. This thesis breaks down the most recent sampling done for the years of 2018 through 2022. Both the methodology of large scale location sampling and the mathematical idea behind the strategy employed are covered. Further, three different software packages were utilized: R, SAS, and ArcGIS. The steps that were taken and the written function code run for each …

Comparison Of The Performance Of Simple Linear Regression And Quantile Regression With Non-Normal Data: A Simulation Study, Marjorie Howard

Theses and Dissertations

Linear regression is a widely used method for analysis that is well understood across a wide variety of disciplines. In order to use linear regression, a number of assumptions must be met. These assumptions, specifically normality and homoscedasticity of the error distribution can at best be met only approximately with real data. Quantile regression requires fewer assumptions, which offers a potential advantage over linear regression. In this simulation study, we compare the performance of linear (least squares) regression to quantile regression when these assumptions are violated, in order to investigate under what conditions quantile regression becomes the more advantageous method …

Semiparametric Regression In The Presence Of Measurement Error, Xiang Li

Theses and Dissertations

The error-in-covariates problem has received great attention among researchers who study semiparametric and nonparametric inference for regression models over the past two decades. Without correcting for the measurement error in covariates, estimators for covariate effect usually contain bias. To account for measurement error, much research have been done in mean regression (Liang et al., 1999; Fuller, 2009; Carroll et al., 2006) and quantile regression (He and Liang, 2000; Hardle et al., 2000; Wei and Carroll, 2009). In contrast, there is little research in mode regression and this motivates us to propose semiparametric methods to address this error-incovariates problem in Chapters …

Bayesian Semiparametric Methods For Analyzing Panel Count Data, Jianhong Wang

Theses and Dissertations

Panel count data commonly arise in epidemiological, social science, medical studies, in which subjects have repeated measurements on the recurrent events of interest at different observation times. Since the subjects are not under continuous monitoring, the exact times of those recurrent events are not observed but the counts of such events within the adjacent observation times are known. Panel count data can be considered as a special type of longitudinal data with a count response variable in the literature. Compared to the frequentist literature, very limited Bayesian approaches have been developed to analyze panel count data. In this dissertation, several …

Semiparametric Statistical Estimation And Inference With Latent Information, Qianqian Wang

Theses and Dissertations

In Chapter 1, we predicted disease risk by transformation models in the presence of missing subgroup identifiers. When a discrete covariate defining subgroup membership is missing for some of the subjects in a study, the distribution of the outcome follows a mixture distribution of the subgroup-specific distributions. Taking into account the uncertain distribution of the group membership and the covariates, we model the relation between the disease onset time and the covariates through transformation models in each sub-population, and develop a nonparametric maximum likelihood based estimation implemented through EM algorithm along with its inference procedure. We further propose methods to …

Estimation Procedures For Complex Survival Models And Their Applications In Epidemiology Studies, Jie Zhou

Theses and Dissertations

In this dissertation, we aim to address three important questions in practice, which can be solved through complex survival models. The first project focuses on studying the longitudinal fitness effect on cardiovascular disease (CVD) mortality. In the second project, we study the disease-death relation between CVD and all-cause mortality and evaluate important covariate effects on the disease or death transitions. In the third project, we compare antiretroviral treatment (ART) for HIV patients and consider both treatment effect and side effect of the drugs. The first two projects are motivated by the Aerobics Center Longitudinal Study (ACLS) datasets and the third …