Statistics and Probability Commons^™

Predictability Of Missing Data Theory To Improve U.S. Estimator’S Unreliable Data Problem, Tomeka S. Williams

Walden Dissertations and Doctoral Studies

Since the topic of improving data quality has not been addressed for the U.S. defense cost estimating discipline beyond changes in public policy, the goal of the study was to close this gap and provide empirical evidence that supports expanding options to improve software cost estimation data matrices for U.S. defense cost estimators. The purpose of this quantitative study was to test and measure the level of predictive accuracy of missing data theory techniques that were referenced as traditional approaches in the literature, compare each theories’ results to a complete data matrix used in support of the U.S. defense cost …

Assessing And Forecasting Chlorophyll Abundances In Minnesota Lake Using Remote Sensing And Statistical Approaches, Ben Von Korff

All Graduate Theses, Dissertations, and Other Capstone Projects

Harmful algae blooms (HABs) can negatively impact water quality, lake aesthetics, and can harm human and animal health. However, monitoring for HABs is rare in Minnesota. Detecting blooms which can vary spatially and may only be present briefly is challenging, so expanding monitoring in Minnesota would require the use of new and cost efficient technologies. Unmanned aerial vehicles (UAVs) were used for bloom mapping using RGB and near-infrared imagery. Real time monitoring was conducted in Bass Lake, in Faribault County, MN using trail cameras. Time series forecasting was conducted with high frequency chlorophyll-a data from a water quality sonde. Normalized …

Design And Analyses Of School-Based Violence Prevention Cluster Randomized Trials, Md. Tofial Azam

Theses and Dissertations--Epidemiology and Biostatistics

Interpersonal violence such as teen dating violence is a severe public health problem. Teen dating violence, including sexual violence (unwanted sexual contacts or activities), physical and psychological dating violence, sexual harassment, and stalking, affects high school students' physical and mental health and academic achievement in the United States. Dating violence is linked to psychological abuse perpetration in the future, depression, anxiety, and hostility. The teen dating violence victimization experience was related to antisocial behavior, drug abuse, increased heavy drinking, depression, suicidal ideation, smoking, and adult interpersonal violence victimization during adolescence. The detrimental effects of interpersonal violence demonstrate the critical importance …

Finite Mixture Models : Applications To Length Of Stay For Delivery Hospitalizations, Eva Williford

Legacy Theses & Dissertations (2009 - 2024)

In the United States (U.S.), childbirth is the most common reason for hospitalization, and the maternal mortality rate per 100,000 (2017-2018) is markedly elevated in the U.S. (17.4) compared to neighboring Canada (10), the United Kingdom (7), and Japan (5) (Trends in Maternal Mortality, 2000 to 2017: Estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division). These data, the increased focus on addressing severe maternal morbidity and mortality to improve patient outcomes and reduce healthcare costs is well deserved. These women often have a longer delivery length of stay (LOS) and experience complications of varying …

Evaluating The Incidence Of Melanoma And Lung Cancer Of Current And Former Active-Duty U.S. Military Who Were Deployed In Support Of Operation Enduring Freedom And Operation Iraqi Freedom, Brian Kovacic

Theses and Dissertations--Epidemiology and Biostatistics

The incidence of melanoma and lung cancer has been gradually increasing in the United States over the past three decades with the reputed causes due to etiological and environmental exposures, and tobacco usage. There has been concern that melanoma and lung cancer incidence among military personnel may be associated with deployment to environments with intense sun exposure and increased smoking rates due to post-traumatic stress disorder. The aim of this study was to examine associations between deployment in support of Operation Enduring Freedom (OEF) or Operation Iraqi Freedom (OIF), from 2001 through 2015, with subsequent melanoma and lung cancer incidence. …

Sexual Behaviors Associated With Online Partner-Seeking Among Men Who Have Sex With Men From Small/Midsized Towns Or Rural Areas In Kentucky, Vira Pravosud

Theses and Dissertations--Epidemiology and Biostatistics

The HIV epidemic remains one of the most significant public health issues in the United States, particularly among men who have sex with men (MSM). New avenues for partner-seeking have emerged over the past three decades, including through the Internet, social media, and geosocial networking applications. Consisting of three cross-sectional studies, this dissertation research aimed to determine associations between the use of various online tools for partner-seeking (hereafter collectively referred to as “apps”) and HIV-related sexual behaviors among 252 young adult MSM residing in small/midsized towns or rural areas in Central Kentucky, a group that has been under-represented in the …

Modeling Multivariate Hopfield-Transformer Hawkes Process: Application To Sovereign Credit Default Swaps, Mohsen Bahremani

Theses and Dissertations (Comprehensive)

Hawkes process was evolved so that the past events contribute to the occurrence time of future events by self-exciting or mutually exciting. However, many real-world data do not follow the Hawkes process's assumptions (i.e., positivity, additivity, and exponential decay) and become more complex to be modeled by the traditional Hawkes processes, so the neural Hawkes process was developed to tackle the challenges. However, Recurrent Neural Networks (RNN) fail to capture long-term dependencies among multiple point processes, and Transformer Hawkes processes only address temporal characteristics of Hawkes processes. In this thesis, we proposed a combination of neural networks and Hawkes processes …

Self-Exciting Point Process For Modelling Terror Attack Data, Siyi Wang

Theses and Dissertations (Comprehensive)

Terrorism becomes more rampant in recent years because of separatism and extreme nationalism, which brings a serious threat to the national security of many countries in the world. The analysis of spatial and temporal patterns of terror data is significant in containing terrorism. This thesis focuses on building and applying a temporal point process called self-exciting point process to fit the terror data from 1970 to 2018 of 10 countries. The data come from the Global Terrorism database. Further, an application in predicting the number of terror events based on the self-exciting model is another main innovative idea, in which …

Parametric, Nonparametric, And Semiparametric Linear Regression In Classical And Bayesian Statistical Quality Control, Chelsea L. Jones

Theses and Dissertations

Statistical process control (SPC) is used in many fields to understand and monitor desired processes, such as manufacturing, public health, and network traffic. SPC is categorized into two phases; in Phase I historical data is used to inform parameter estimates for a statistical model and Phase II implements this statistical model to monitor a live ongoing process. Within both phases, profile monitoring is a method to understand the functional relationship between response and explanatory variables by estimating and tracking its parameters. In profile monitoring, control charts are often used as graphical tools to visually observe process behaviors. We construct a …

Bias Of Rank Correlation Under A Mixture Model, Russell Land

College of Graduate Studies: Theses & Dissertations

This thesis project will analyze the bias in mixture models when contaminated data is present. Specifically, we will analyze the relationship between the bias and the mixing proportion, p, for the rank correlation methods Spearman’s Rho and Kendall’s Tau. We will first look at the history of the two non-parametric rank correlation methods and the sample and population definitions will be introduced. Copulas will be introduced to show a few ways we can define these correlation methods. After that, mixture models will be defined and the main theorem will be stated and proved. As an example, we will apply this …

The Causes And Control Measures Of Extended Spectrum Beta-Lactamase Producing Enterobacteriaceae In Long-Term Care Facilities, Ismaila Olatunji Sule

Walden Dissertations and Doctoral Studies

Due to extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-PE), infections among residents are increasing in long-term care facilities (LTCFs), resulting in high rate of morbidity and healthcare costs. ESBL-PE resists empirical antibiotics and reduces treatment options, and a designated infection control team is unavailable to prevent the prevalence of the disease. Ecological theory guided this study. A systematic review and meta-analysis were conducted to characterize the causes of ESBL-PE and evaluate the infection control strategies within LTCFs. Multiple regression analysis (MRA) was included as supplementary statistical analysis to identify relationships between LTCFs, geographical locations, infection control measures (ICMs), and ESBL-PE. A systematic search …

Automatic Hierarchy Expansion For Improved Structure And Chord Evaluation, Katherine M. Kinnaird, Brian Mcfee

Statistical and Data Sciences: Faculty Publications

No abstract provided.

Predicting The Winning Percentage Of Limited-Overs Cricket Using The Pythagorean Formula, Hasika K. W. Senevirathne, Ananda B.W. Manage

Mathematics & Statistics Faculty Publications

The Pythagorean Win-Loss formula can be effectively used to estimate winning percentages for sporting events. This formula was initially developed by baseball statistician Bill James and later was extended by other researchers to sports such as football, basketball, and ice hockey. Although one can calculate actual winning percentages based on the outcomes of played games, that approach does not take into account the margin of victory. The key benefit of the Pythagorean formula is its utilization of actual average runs scored and actual average runs allowed. This article presents the application of the Pythagorean Win-Loss formula to two different types …

Spatio-Temporal Modelling Of Tick Life-Stage Count Data With Spatially Varying Coefficients, Thabo Lephoto, Henry Mwambi, Oliver Bodhlyera, Holly Gaff

Biological Sciences Faculty Publications

There is a vast amount of geo-referenced data in many fields of study including ecological studies. Geo-referencing is usually by point referencing; that is, latitudes and longitudes or by areal referencing, which includes districts, counties, states, provinces and other administrative units. The availability of large geo-referenced datasets for modelling has necessitated the development and application of spatial statistical methods. However, spatial varying coefficients models exploring the abundance of tick counts remain limited. In this study we used data that was collected and prepared by researchers in the Department of Biological Sciences from the Old Dominion University, Virginia, USA. We modelled …

Neither “Post-War” Nor Post-Pregnancy Paranoia: How America’S War On Drugs Continues To Perpetuate Disparate Incarceration Outcomes For Pregnant, Substance-Involved Offenders, Becca S. Zimmerman

Pitzer Senior Theses

This thesis investigates the unique interactions between pregnancy, substance involvement, and race as they relate to the War on Drugs and the hyper-incarceration of women. Using ordinary least square regression analyses and data from the Bureau of Justice Statistics’ 2016 Survey of Prison Inmates, I examine if (and how) pregnancy status, drug use, race, and their interactions influence two length of incarceration outcomes: sentence length and amount of time spent in jail between arrest and imprisonment. The results collectively indicate that pregnancy decreases length of incarceration outcomes for those offenders who are not substance-involved but not evenhandedly -- benefitting white …

A Deep Learning Model To Predict Traumatic Brain Injury Severity And Outcome From Mr Images, Dacosta Yeboah, Hung Nguyen, Daniel B. Hier, Gayla R. Olbricht, Tayo Obafemi-Ajayi

Chemistry Faculty Research & Creative Works

For Many Neurological Disorders, Including Traumatic Brain Injury (TBI), Neuroimaging Information Plays a Crucial Role Determining Diagnosis and Prognosis. TBI is a Heterogeneous Disorder that Can Result in Lasting Physical, Emotional and Cognitive Impairments. Magnetic Resonance Imaging (MRI) is a Non-Invasive Technique that Uses Radio Waves to Reveal Fine Details of Brain Anatomy and Pathology. Although MRIs Are Interpreted by Radiologists, Advances Are Being Made in the Use of Deep Learning for MRI Interpretation. This Work Evaluates a Deep Learning Model based on a Residual Learning Convolutional Neural Network that Predicts TBI Severity from MR Images. the Model Achieved a …

Dimension Reduction Techniques In Regression, Pei Wang

Theses and Dissertations--Statistics

Because of the advances of modern technology, the size of the collected data nowadays is larger and the structure is more complex. To deal with such kinds of data, sufficient dimension reduction (SDR) and reduced rank (RR) regression are two powerful tools. This dissertation focuses on these two tools and it is composed of three projects. In the first project, we introduce a new SDR method through a novel approach of feature filter to recover the central mean subspace exhaustively along with a method to determine the dimension, two variable selection methods, and extensions to multivariate response and large p …

Novel Nonparametric Testing Approaches For Multivariate Growth Curve Data: Finite-Sample, Resampling And Rank-Based Methods, Ting Zeng

Theses and Dissertations--Statistics

Multivariate growth curve data naturally arise in various fields, for example, biomedical science, public health, agriculture, social science and so on. For data of this type, the classical approach is to conduct multivariate analysis of variance (MANOVA) based on Wilks' Lambda and other multivariate statistics, which require the assumptions of multivariate normality and homogeneity of within-cell covariance matrices. However, data being analyzed nowadays show marked departure from multivariate normal distribution and homoscedasticity. In this dissertation, we investigate nonparametric testing approaches for multivariate growth curve data from three aspects, i.e., finite-sample, resampling and rank-based methods.

The first project proposes an approximate …

Novel Methods For Characterizing Conditional Quantiles In Zero-Inflated Count Regression Models, Xuan Shi

Theses and Dissertations--Statistics

Despite its popularity in diverse disciplines, quantile regression methods are primarily designed for the continuous response setting and cannot be directly applied to the discrete (or count) response setting. There can also be challenges when modeling count responses, such as the presence of excess zero counts, formally known as zero-inflation. To address the aforementioned challenges, we propose a comprehensive model-aware strategy that synthesizes quantile regression methods with estimation of zero-inflated count regression models. Various competing computational routines are examined, while residual analysis and model selection procedures are included to validate our method. The performance of these methods is characterized through …

Estimating And Testing Treatment Effects With Misclassified Multivariate Data, Zi Ye

Theses and Dissertations--Statistics

Clinical trials are often used to assess drug efficacy and safety. Participants are sometimes pre-stratified into different groups by diagnostic tools. However, these diagnostic tools are fallible. The traditional method ignores this problem and assumes the diagnostic devices are perfect. This assumption will lead to inefficient and biased estimators. In this era of personalized medicine and measurement-based care, the issues of bias and efficiency are of paramount importance. Despite the prominence, only few researches evaluated the treatment effect in the presence of misclassifications in some special cases and most others focus on assessing the accuracy of the diagnostic devices. In …