Statistics and Probability Commons^™

Simulation Study On Count Data Based On Double Poisson Distribution, Chao Ma

Theses and Dissertations

This thesis delves into the double Poisson distribution. Regression based on the double Poisson distribution, as proposed by Efron in 1986, offers an alternative approach that allows for more accurate regression models when dealing with discrete data that exhibit either over- or under-dispersion compared to the Poisson distribution. In this thesis, two methods of calculating the exact double Poisson density are compared: one utilizes the exact probability with the normalizing constant c(mu, theta) by definition or the “finite sum” method, while the other employs an approximation of the normalizing constant c(mu, theta). Furthermore, a simulation was …

Cluster Effect For Snp-Snp Interaction Pairs For Predicting Complex Traits, Hui Yi Lin, Harun Mazumder, Indrani Sarkar, Po Yu Huang, Rosalind A. Eeles, Zsofia Kote-Jarai, Kenneth R. Muir, Johanna Schleutker, Nora Pashayan, Jyotsna Batra, David E. Neal, Sune F. Nielsen, Børge G. Nordestgaard, Henrik Grönberg, Fredrik Wiklund, Robert J. Macinnis, Christopher A. Haiman, Ruth C. Travis, Janet L. Stanford, Adam S. Kibel, Cezary Cybulski, Kay Tee Khaw, Christiane Maier, Stephen N. Thibodeau, Manuel R. Teixeira, Lisa Cannon-Albright, Hermann Brenner, Radka Kaneva, Hardev Pandha, Et Al

School of Public Health Faculty Publications

Single nucleotide polymorphism (SNP) interactions are the key to improving polygenic risk scores. Previous studies reported several significant SNP-SNP interaction pairs that shared a common SNP to form a cluster, but some identified pairs might be false positives. This study aims to identify factors associated with the cluster effect of false positivity and develop strategies to enhance the accuracy of SNP-SNP interactions. The results showed the cluster effect is a major cause of false-positive findings of SNP-SNP interactions. This cluster effect is due to high correlations between a causal pair and null pairs in a cluster. The clusters with a …

The Impact Of “Multiple Looks” When Performing Survival Analysis, Quentin Eloise

Electronic Theses and Dissertations

Survival analysis is a critical statistical method in healthcare to assess patient treatment effects and disease progression. Another critical area of statistical methodology in health care is the practice of adaptive designs. Adaptive designs allow for interim analyses to take place during a study and various decisions and actions can take place more ethically. This is beneficial for studies that take multiple years to complete and allows administrators and healthcare providers to make sound decisions as early as possible. A challenging aspect of adaptive designs is that the number of interim analyses is known in advance which is applicable in …

Public Mass Shootings In Texas And California: Routine Activity Theory Comparisons, Mason R. Feinartz

Doctoral Dissertations and Projects

Public mass shootings are a distinct and unique phenomenon that receives vast media and public attention due to the location, weapons used, and amount of people killed or injured. These mass shootings occur in places where people frequent daily in their routine activities and are unexpected, seemingly random, or symbolic events. This study used a casual-comparative quantitative research design using routine activity theory as the foundation to investigate public mass shootings in Texas and California from 1966 to 2023. This study used public open-source data collection and analysis to identify and substantiate all mass shootings that satisfy the research inclusion/exclusion …

Green Synthesis Of Carbonized Chitosan-Fe3o4-Sio2 Nano-Composite For Adsorption Of Heavy Metals From Aqueous Solutions, Dalia A. Ali Eng, Rinad Galal Ali Eng.

Chemical Engineering

Water pollution with heavy metals owing to industrial and agricultural activities have become a critical dilemma to humans, plants as well as the marine environment. Therefore, it is of great importance that the carcinogenic heavy metals present in wastewater to be eliminated through designing treatment technologies that can remove multiple pollutants. A novel green magnetic nano-composite called (Carbonized Chitosan-Fe3O4-SiO2) was synthesized using Co-precipitation method to adsorb a mixture of heavy metal ions included; cobalt (Co2+), nickel (Ni2+) and copper (Cu2+) ions from aqueous solutions. The novelty of this study was the synthesis of a new

nano-composite which was green with …

Estimation Of Integrated Volatility Functionals & Behavior Of The Bandwidth Selector With Kernel Spot Volatility Estimators, Jincheng Pang

Arts & Sciences Graduate Student Theses and Dissertations

In financial economics, semimartingales hold great importance among all the stochastic processes, and the Itô framework, driven by Brownian motion and Poisson random measure, provides a robust way to model a wide range of phenomena, particularly in finance, and therefore, Itô semimartingales are almost universally preferred in practical applications. Based on high-frequency return data, the accurate estimation of the spot volatility of Itô semimartingales is crucial for addressing numerous issues such as hedging, option pricing, risk analysis and portfolio management. In this dissertation, we investigate kernel type estimators and examine two issues concerning the estimation of spot volatility. Firstly, for …

Disparities And Protective Factors In Pandemic-Related Mental Health Outcomes: A Louisiana-Based Study, Ariane L. Rung, Evrim Oral, Tyler Prusisz, Edward S. Peters

School of Public Health Faculty Publications

Introduction: The COVID-19 pandemic has had a wide-ranging impact on mental health. Diverse populations experienced the pandemic differently, highlighting pre-existing inequalities and creating new challenges in recovery. Understanding the effects across diverse populations and identifying protective factors is crucial for guiding future pandemic preparedness. The objectives of this study were to (1) describe the specific COVID-19-related impacts associated with general well-being, (2) identify protective factors associated with better mental health outcomes, and (3) assess racial disparities in pandemic impact and protective factors. Methods: A cross-sectional survey of Louisiana residents was conducted in summer 2020, yielding a sample of 986 Black …

A Machine Learning Based Approach For The Identification Of Fake Bills, Tianyang Lu, Hongyang Pang

Rose-Hulman Undergraduate Mathematics Journal

Fake or counterfeiting currency, which has been around as long as money has existed, is a major economic problem. Since the US dollar is the most popular form of currency globally, it is the most popular currency to counterfeit. The United States Department of Treasury estimates that between $70 million and $200 million in fake bills are in circulation. The Federal Reserve Bank uses special banknote processing systems to count each bill deposited by the bank and examine them for the possibility of counterfeits. These machines have sensors designed to detect general quality of the bills, including paper type, quality …

Uncertainty Quantification In Machine Learning Models Via Gaussian Process Regression: A Comparative Study, Ayorinde E. Olatunde, Weiqi Yue, Pawan K. Tripathi, Roger H. French, Anirban Mondal

Faculty Scholarship

As the use of Machine learning models in science and engineering continues to increase, there is an increasing need for quantifying the uncertainties inherent in the predictions of these models. The more complex a model is, the more the uncertainties in its predictions increase. Amongst the plethora of methodologies used in quantifying uncertainties lies Gaussian Process Regression (GPR). GPR surmounts some of the popular shortfalls of other state-of-the-art methodologies. Although GPR has some quick wins in its application for uncertainty quantification, it is plagued with some shortfalls, such as scalability issues when the feature space increases as well as an …

Bayesian And Deep Generative Modeling In Immunology, Yuqiu Yang

Statistical Science Theses and Dissertations

Due to the accumulation of a large volume of data of different natures such as sequencing data, proteomics data, and clinical data, statistical methods and deep learning algorithms have become increasingly important in the field of immunology. By leveraging the diverse datasets as well as interdisciplinary knowledge from areas like biology and public health, these quantitative methods have revolutionized this field by providing powerful tools for data analysis, modeling, and prediction. This has led to a deeper understanding of the immune system, accelerated the development of novel therapies, and paved the way for personalized and precision medicine approaches in immunology. …

Bayesian Variational Inference In Keyword Identification And Multiple Instance Classification, Yaofang Hu

Statistical Science Theses and Dissertations

This dissertation investigates (1) Variational Bayesian Semi-supervised Keyword Extraction and (2) Variational Bayesian Multimodal Multiple Instance Classification.

The expansion of textual data, stemming from various sources such as online product reviews and scholarly publications on scientific discoveries, has created a demand for the extraction of succinct yet comprehensive information. As a result, in recent years, efforts have been spent in developing novel methodologies for keyword extraction. Although many methods have been proposed to automatically extract keywords in the contexts of both unsupervised and fully supervised learning, how to effectively use partially observed keywords, such as author-specified keywords, remains an under-explored …

Non-Receptor Tyrosine Kinases: Their Structure And Mechanistic Role In Tumor Progression And Resistance, Abdulaziz M. Eshaq, Thomas W. Flanagan, Sofie Yasmin Hassan, Sara A. Al Asheikh, Waleed A. Al-Amoudi, Simeon Santourlidis, Sarah Lilly Hassan, Maryam O. Alamodi, Marcelo L. Bendhack, Mohammed O. Alamodi, Youssef Haikel, Mossad Megahed, Mohamed Hassan

School of Graduate Studies Faculty Publications

Protein tyrosine kinases (PTKs) function as key molecules in the signaling pathways in addition to their impact as a therapeutic target for the treatment of many human diseases, including cancer. PTKs are characterized by their ability to phosphorylate serine, threonine, or tyrosine residues and can thereby rapidly and reversibly alter the function of their protein substrates in the form of significant changes in protein confirmation and affinity for their interaction with protein partners to drive cellular functions under normal and pathological conditions. PTKs are classified into two groups: one of which represents tyrosine kinases, while the other one includes the …

Mesenchymal Stem Cells In Autoimmune Disease: A Systematic Review And Meta-Analysis Of Pre-Clinical Studies, Hailey N. Swain, Parker D. Boyce, Bradley A. Bromet, Kaiden Barozinksy, Lacy Hance, Dakota Shields, Gayla R. Olbricht, Julie A. Semon

Mathematics and Statistics Faculty Research & Creative Works

Mesenchymal Stem Cells (MSCs) Are of Interest in the Clinic Because of their Immunomodulation Capabilities, Capacity to Act Upstream of Inflammation, and Ability to Sense Metabolic Environments. in Standard Physiologic Conditions, They Play a Role in Maintaining the Homeostasis of Tissues and Organs; However, there is Evidence that They Can Contribute to Some Autoimmune Diseases. Gaining a Deeper Understanding of the Factors that Transition MSCs from their Physiological Function to a Pathological Role in their Native Environment, and Elucidating Mechanisms that Reduce their Therapeutic Relevance in Regenerative Medicine, is Essential. We Conducted a Systematic Review and Meta-Analysis of Human MSCs …

Lactoferrin And Lysozyme To Promote Nutritional, Clinical And Enteric Recovery: A Protocol For A Factorial, Blinded, Placebo-Controlled Randomised Trial Among Children With Diarrhoea And Malnutrition (The Boresha Afya Trial), Ruchi Tiwari, Kirkby Tickell, Emily Yoshioka, Joyce Otieno, Adeel Shah, Barbra Richardson, Lucia Keter, Maureen Okello, Churchil Nyabinda, Indi Trehan

Paediatrics and Child Health, East Africa

Introduction: Children with moderate or severe wasting are at particularly high risk of recurrent or persistent diarrhoea, nutritional deterioration and death following a diarrhoeal episode. Lactoferrin and lysozyme are nutritional supplements that may reduce the risk of recurrent diarrhoeal episodes and accelerate nutritional recovery by treating or preventing underlying enteric infections and/or improving enteric function.

Methods and analysis: In this factorial, blinded, placebo-controlled randomised trial, we aim to determine the efficacy of lactoferrin and lysozyme supplementation in decreasing diarrhoea incidence and improving nutritional recovery in Kenyan children convalescing from comorbid diarrhoea and wasting. Six hundred children aged 6–24 months with …

Assessing Gtfs Accuracy, Gregory L. Newmark

Mineta Transportation Institute

The promised benefits of the General Transit Feed Specification (GTFS) Schedule and Realtime standards are dependent on the underlying quality of the data. Despite this fundamental reliance, there has been relatively little research on techniques and strategies to assess GTFS accuracy. The need for such assessment is growing as federal and state governments increasingly require transit agencies to make these data available to the public. This research fills this gap by presenting a suite of methods and metrics to assess the temporal accuracy of GTFS Realtime and the spatial accuracy of GTFS Schedule feeds. The temporal assessment demonstrates an approach …

Two New Baseball Performance Statistics, Charles H. Smith

Faculty/Staff Personal Papers

Ever since I was a small child I have been interested in both statistics and baseball, so I guess it was inevitable I would eventually find a way to put the two together. In this short note I'd like to suggest a pair of measures that I feel might be useful in interpreting quality of play: one focusing more on hitting, the other on pitching. Let's start with the one concerning hitting.

Using Digitized Building And Weather Records To Improve The Accuracy Of Ground To Roof Snow Load Ratio Estimations, Gideon Parry

All Graduate Theses and Dissertations, Fall 2023 to Present

Reliability target loads refer to the amount of accumulated snow a roof needs to be able to support to ensure that the probability of collapse is sufficiently low. Since ground snow weight, or load, is much easier to measure than roof snow load, models for roof snow loads rely on ground snow load measurements along with a statistical model that estimates roof snow retention as a ratio of the measured ground snow load. This thesis focuses on improving the roof snow retention model using data from Canadian case studies that include information about building geometry and local wind speeds. This …

Exploring Healthcare Chatbot Information Presentation: Applying Hierarchical Bayesian Regression And Inductive Thematic Analysis In A Mixed Methods Study, Samuel Nelson Koscelny

All Theses

High blood pressure, also known as hypertension, significantly increases the risk of heart disease and stroke, which are leading causes of death in the United States. While contributing to over 691,000 deaths in 2021 alone in the United States (U.S.), it also imposes immense economic burden on the healthcare system, costing approximately $131 billion annually. One way to address this issue is for increased self-care behaviors and medication adherence, both of which require sufficient health literacy. Despite the importance of health literacy, 90% of U.S. adults struggle with health-related subjects. Overcoming the issues associated with health literacy requires addressing the …

Effects Of Measurement Error In Student Pre-Post Test Score On The Recovery Of The Estimates Of Teachers Value-Added Scores, Merlin J. Kamgue

Graduate Theses and Dissertations

Abstract Background: Value-added models (VAMs) are statistical tools used to gauge a teacher’s impact on student performance by analyzing standardized test scores. These models project students’ future performance based on past scores and compare the projection to actual outcomes, accounting for differences in student backgrounds. However, the standard error of measurement (SEM) inherent in all measurement tools is often overlooked in VAMs. Aims and Objectives: This study aims to investigate the impact of test reliability on teacher and school score estimates within a Bayesian framework. We will precisely manipulate the reliability of standardized tests by adjusting the standard error of …

Dynamic Prediction Of Disease Progression With Longitudinal Data, Wenhao Li

Dissertations and Theses (Open Access)

Dynamic prediction plays a pivotal role in clinical research, especially when forecasting time-to-event outcomes based on evolving longitudinal data. This process often leverages the integration of longitudinal and time-to-event data through joint modeling, a prevalent technique. Alongside joint modeling, landmark modeling stands as another key approach in the realm of longitudinal studies. These methodologies are instrumental in dynamically predicting clinical events by utilizing predictor variables measured over time, up until the moment predictions are made. Within this framework, Chapter 2 addresses the challenge of comparing joint modeling and landmark modeling for dynamic prediction in longitudinal studies, introducing a novel algorithm …