Statistics and Probability Commons^™

Engr 597: Special Projects In Engineering Science - Data Analytics, Ali Behnood Ph.D., P.E., M., Asce

GMAS Course Syllabi

No abstract provided.

Smarter Disease Detection From Electronic Health Record Data: An End-To-End Ai-Augmented Pipeline For Computable Phenotyping, Dylan Owens

Statistical Science Theses and Dissertations

Electronic Health Records (EHR) contain a wealth of structured and unstructured patient data that can be leveraged for computable phenotyping, the process of algorithmically identifying patient cohorts with specific diseases or conditions. Traditional rule-based phenotyping approaches, while interpretable, often struggle with scalability, portability across institutions, and effective use of unstructured clinical narratives. Recent advances in large language models (LLMs) present new opportunities for synthesizing complex free-text information into concise, clinically meaningful representations. However, integrating LLMs into phenotyping workflows requires careful design to maintain transparency, interpretability, and measurable uncertainty—features essential for clinical adoption and downstream applications such as decision support.

We …

(Si15-140) Designing Bayesian Double Sampling Plans Based On Zero Inflated Poisson Distribution, Priyadharshini R., Shalini K., Hemalatha R., Sangeetha S.

Applications and Applied Mathematics: An International Journal (AAM)

The implementation of attribute-based sampling inspection serves as a quality control technique used across numerous industries to evaluate items or workflow processes. When the data exhibits a substantial number of zero counts, the zero-inflated Poisson (ZIP) distribution serves as an effective model for accommodating this zero-inflation. Double sampling plan (DSP) is a quality check method where the decision to approve or decline a batch comes after examining two samples, providing more conclusive information compared to a single sample plan (SSP). In practice, effective decision-making regarding submitted lots considers both within-lot and between-lot variations, which can be addressed through the use …

(Si15-142) Selection Of Single Sampling Plans Based On Zero Inflated Binomial Distribution Using Cost Optimization, Sangeetha S., Shalini K., Hemalatha R., Priyadharshini R.

Applications and Applied Mathematics: An International Journal (AAM)

Economic design of sampling plans involves creating sampling plans that minimize the total cost associated with the inspection process while ensuring quality. It aims to address the quality risk concerns of both producer and consumer, ensuring product quality while minimizing inspection costs. This article’s objective is to design single sampling plans by attributes based on Zero-inflated Binomial (ZIB) distribution, using cost optimization principles by developing an economic model aimed at achieving optimal total cost by considering the Average Total Inspection (ATI). Numerical illustration is provided to illustrate the selection of single sampling plans under ZIB distribution that minimizes producer’s total …

The Gender Pay Gap: An Occupational Analysis (2012-2023), Curtis Long

Harriet L Wilkes Honors College Theses

This thesis examines the gender wage gap across thirty major U.S. occupations from 2014 to 2023 using data from the Current Population Survey (CPS), more specifically, the U.S. Bureau of Labor Statistics (BLS). The analysis measures the difference in median weekly earnings between women and men in each occupation and applies two statistical tests: a yearly z-test to evaluate whether the average wage gap is significant, and a ten-year t-test to identify persistent occupational gaps. Results show significant wage differences in every year, with the largest disparities in finance, management, and law, and smaller gaps in education and healthcare. Consistent …

Spatiotemporal Modeling Of Maternal Mortality In South Carolina 2018-2023, Leah Wood, Ray Bai, Emily Mann

Senior Theses

Maternal death serves as a public health indicator due to fact that it is considered preventable with the availability of modern biomedicine, however, it persists broadly throughout the United States. Current literature outlines national trends in maternal mortality with complicating, preexisting conditions, and structural upstream factors often cited as being the largest contributors to increased risk. This study utilizes publicly available, county-level data for maternal death in addition to demographic and descriptive data in order to estimate maternal mortality rates in each of South Carolina’s 46 counties from 2018 to 2023. In order to address sparsity in the outcome variable …

Glucodensity Functional Profiles Outperform Traditional Continuous Glucose Monitoring Metrics, Marcos Matabuena, Rahul Ghosal Ph.D., Javier Enrique Aguilar, Ayya Keshet, Robert Wagner, Carmen Fernández Merino, Juan Sánchez Castro, Vadim Zipunnikov, Jukka-Pekka Onnela, Francisco Gude

Faculty Publications

Continuous glucose monitoring (CGM) data have revolutionized the management of type 1 diabetes, particularly when integrated with insulin pumps to mitigate clinical events such as hypoglycemia. Recently, there has been growing interest in utilizing CGM devices in clinical studies involving healthy and diabetic populations. However, efficiently exploiting the high temporal resolution of CGM profiles remains a significant challenge. Numerous indices—such as time–in–range metrics and glucose variability measures–have been proposed, but evidence suggests these metrics overlook critical aspects of dynamic glucose homeostasis. As an alternative method, this paper explores the clinical value of glucodensity metrics in capturing glucose dynamics—specifically the speed …

Association Of Estimated Plasma Volume Status With Invasive Hemodynamics And Adverse Clinical Outcomes In Patients With Pulmonary Hypertension And Chronic Kidney Disease, Andrew Geller, Jose Manuel Martinez Manzano, Esteban Kosak Lopez, Phuuwadith Wattanachayakul, John Malin, Raul Leguizamon, Tara John, Rasha Khan, Ian Mclaren, Alexander Prendergast, Simone Jarrett, Kevin Bryan Lo, Christian Witzke

Einstein Health Papers

Identifying noninvasive measures to assess intravascular volume status and risk stratify patients with pulmonary hypertension (PH) and chronic kidney disease (CKD) is needed. We assessed the predictive value of estimated plasma volume status (ePVS) using the Strauss-derived Duarte formula in PH-CKD patients. This single-center retrospective cohort analysis included patients with PH and CKD Stage 3b (CKD3b), Stage 4 (CKD4), or Stage 5 (CKD5) who underwent right heart catheterization from 2018 to 2023. Patients were categorized into low ePVS (< 6.2) and high ePVS (≥ 6.2) using Youden's J statistics. We used the Cox-proportional hazards model, adjusting for age, sex, and body mass index, to investigate the association between …

Reduced Order Approach For Peening Stress Field Variability, Langdon Feltner, Paul Mort

15th International Conference on Shot Peening

A common goal in shot peening research is to connect operational parameters to resultant residual stress fields, providing a means to control and optimize the effectiveness of surface treatment. In practice, experimental measurements of residual stresses are often averaged values over regions that are large in comparison to an impact dimple. In fact, the stochastic nature of impact locations leads to residual stress fields that are distributed. Finite element peening simulations confirm this observation. The goal of this report is to connect operational parameters to localized fluctuations in residual stress through probabilistic reasoning (Figure 1). In particular, the development of …

Heuristic Weight Initialization For Transfer Learning In Classification Problems, Musulmon Lolaev, Anand Paul, Jeonghong Kim

School of Public Health Faculty Publications

Transfer learning is the predominant method for adapting pre-trained models on another task to new domains while preserving their internal architectures and augmenting them with requisite layers in Deep Neural Network models. Training intricate pre-trained models on a sizable dataset requires significant resources to fine-tune hyperparameters carefully. Most existing initialization methods mainly focus on gradient flow-related problems, such as gradient vanishing or exploding, or other existing approaches that require extra models that do not consider our setting, which is more practical. To address these problems, we suggest employing gradient-free heuristic methods to initialize the weights of the final new-added fully …

From P-Values To Practical Relevance: An Introduction To Effect Sizes Through A Legal Psychological Example, Paul Riesthuis, Henry Otgaar, Tery Setiawan, Nathanael Sumampouw, Charlotte Bücken

Psychological Research on Urban Society

Null-hypothesis significance testing and p-values are frequently criticized for their focus on detecting non-zero differences and their inability to provide evidence for the null hypothesis. In this article, we highlight how effect sizes, when meaningfully interpreted, can address these issues. Specifically, we argue that researchers should consider the smallest effect size of interest (SESOI) - the smallest effect size that yields practical or theoretical relevance. We propose several methods for estimating the SESOI and present a consensus study among Indonesian professionals which can be used to estimate the SESOI for child eyewitness testimony research. Results suggest that most Indonesian professionals …

Effect Of Vitamin D Supplementation During Pregnancy And Lactation On The Development Of Infants Born To Tanzanian Women Living With Hiv: A Secondary Analysis Of A Randomised Controlled Trial, Temiwunmi Shobanke, Alfa Muhihi, Nandita Perumal Phd, Nzovu Ulenga, Fadhlun M. Alwy Al-Beity, Christopher P. Duggan, Wafaie W. Fawzi, Karim P. Manji, Christopher R. Sudfeld

Faculty Publications

Background Infants born to pregnant women living with HIV (WLHIV) are at greater risk for morbidity and mortality and may also have poorer developmental outcomes as compared with infants who are not exposed to HIV. Nutrition interventions in pregnancy may affect developmental outcomes.

Objectives This study evaluated the effect of maternal vitamin D supplementation on infant development outcomes.

Design We conducted a secondary analysis of a randomised, triple-blind, placebo-controlled trial of maternal vitamin D supplementation from June 2015 to October 2019.

Setting Antenatal care clinics in Dar es Salaam, Tanzania.

Participants Pregnant WLHIV and their offspring.

Interventions Daily 3000 IU …

Long-Term Behavior Of Subordinated Branching Processes With Prevailing Emigration, George Yanev

School of Mathematical & Statistical Sciences Faculty Publications

This paper deals into the long-term behavior of subordinated critical branching processes with migration. We focus on scenarios where emi­gration is the dominant factor and introduce additional randomness in timing through a subordination mechanism, involving renewal processes. The key findings highlight how the initial population size and the interar­rival mean time influence both asymptotic behavior of the non-extinction probability and corresponding Yaglom type limit theorems. We also study an alternating regenerative process, when the population cycles between zero and positive states. This research complements previous studies for processes when immigration prevails over emigration.

Comparative Evaluation Of Estimation Techniques For Purchasing Power Parity In African Countries Using The Country-Product-Dummy Regression Framework, Rokibat Adeola Tijani, Taiwo Abideen Lasisi, Dahud Kehinde Shangodoyin, Olasunkanmi James Oladapo

Al-Bahir

Purchasing Power Parity (PPP) is a popular macroeconomic analysis metric used to compare economic productivity and standards of living between countries. This study examines the estimation of PPP within the International Comparison Program (ICP) at Basic Heading (BH) level stage and leverages on the data from the 2011 ICP round. Focusing on five BHs out of 12 BHs across 50 Africa countries, to empirically evaluate the validity of the classical Ordinary Least Square (OLS) assumptions in the estimation of Country Product Dummy (CPD) regressions. Given the widespread use of OLS for BH level PPP computation, a rigorous examination of these …

Bayesian Survival Analysis For High-Dimensional Compositional Data, Zhenying Ding

All ETDs from UAB

Survival analysis integrating microbiome and clinical data offers powerful insights into human health. The microbiome influences immunity, inflammation, and cancer outcomes. Combining microbial profiles with clinical factors like tumor stage, treatment, and demographics enhances understanding of how host-microbe interactions affect survival. To analyze these complex datasets, advanced statistical methods, including Bayesian models, penalized Cox proportional hazards models, and machine learning techniques are employed. These approaches can uncover novel biomarkers and therapeutic targets, leading to personalized treatment strategies that optimize patient survival. However, challenges arise due to the compositionality, high-dimensionality, and phylogenetic relation between taxa in microbiome data. In this dissertation, …

Bayesian Mediation Analyses For Zero-Inflated Data, Jinhong Cui

All ETDs from UAB

Mediation analysis is a fundamental tool in causal inference, enabling researchers to disentangle the pathways through which an exposure affects an outcome via intermediate variables (mediators). It has been widely applied in social sciences, psychology, and healthcare-related studies. Traditionally, mediation analysis has been conducted within the linear structural equation modeling (LSEM) framework. However, recent advances have shifted attention toward the counterfactual framework due to its flexibility in defining causal effects and its capacity to accommodate non-linear relationships, parametric and non-parametric models. Building on this foundation, methodological developments in mediation analysis have expanded to address more complex data structures, such as …

Modeling Musculoskeletal Combat Casualty Care: Nato Trauma System Performance In Large Scale Combat Operations, Mark P. Cote, Kaitlyn E. Holly, Roman J. Schoenfeld, Matthew R. Bryan, Malina O. Hatton, Mitchel B. Harris, Tracey P. Koehlmoos, Andrew J. Schoenfeld

Department of Orthopaedic Surgery Faculty Papers

BACKGROUND: It is unclear whether the current North Atlantic Treaty Organization (NATO) trauma system will be effective in the setting of Large-Scale Combat Operations (LSCO). We sought to model the efficacy of the NATO trauma system in the setting of LSCO. We also intended to model novel scenarios that could better adapt the current system to LSCO.

METHODS: We developed a discrete-event simulation model for patients with combat musculoskeletal injuries treated within the standard NATO system. The primary outcome of the model was survival. The model's health states were characterized as stable, hypovolemia, sepsis, shock, or death. The model simulated …

Emerging Clinical Role Of Tavapadon, A Novel Dopamine Partial Agonist, In The Treatment Of Parkinson’S Disease, Alan D. Kaye, Bennett M. Ford, Brennan M. Abbott, Kalob M. Broocks, Sofia Novacic, Sahar Shekoohi

School of Medicine Faculty Publications

Tavapadon, a novel oral dopamine-D1R/D5R partial agonist, has been studied in recent years for the treatment of late-stage development Parkinson’s disease (PD). Levodopa, a dopamine precursor that currently remains the gold-standard first-line therapy for PD motor symptoms, serves as a benchmark against emerging dopaminergic agents. By selectively activating D1-family receptors on direct-pathway medium neurons, Tavapadon differs in that it delivers levodopa-level motor benefit while avoiding its many D2R/D3R-mediated adverse effects. In placebo-controlled trials, Tavapadon produced clear, clinically meaningful gains in motor function and day-to-day activities, as captured by the Unified Parkinson’s Disease Rating Scale (UPDRS). Recent late-stage results have revealed …

Generalized Transversality Conditions For Fuzzy Quantum-Symmetric Variational Problems Via Granular Approach, Martin Bohner, Ewa Girejko, Agnieszka B. Malinowska, Linh Nguyen, Baruch Schneider, Tri Truong

Mathematics and Statistics Faculty Research & Creative Works

This paper investigates fuzzy q-symmetric variational problems with natural boundary conditions. Based on the relative distance measure fuzzy arithmetic and horizontal membership functions (HMFs), we propose novel concepts of differentiability and integrability for fuzzy functions on quantum geometric subsets of real numbers. Then, fundamental foundations of q-symmetric calculus of variations based on HMFs are provided. With the help of HMFs and granular q-symmetric differentiability, we derive necessary optimality conditions for fuzzy q-symmetric variational problems that depend on free endpoints. Moreover, sufficient conditions for minimizers of q-symmetric variational problems are obtained. Some numerical examples illustrating the proposed approach are presented.

Novel Statistical And Topological Data Analyses Of 2d Electronic Images, Robert L. Paige, Vic Patrangenaru

Mathematics and Statistics Faculty Research & Creative Works

In this paper, novel statistical and topological data analyses of 2D images are developed. One considers methodologies based on the Region Covariance Descriptor (RCD) and Topological Data Analysis (TDA) rooted in the simplicial as well as cubical persistent homologies. These methods provide statistical methods for data from populations of complex data objects that are elements of non-Euclidean spaces. The 2D image data considered consist of pictures of two leaves—A and B—from the same tree, twenty of each leaf, from different perspectives. The novel statistical procedures developed are used for correctly determining that leaf A images and leaf B images are …

Deep Learning Framework For Option Pricing, Kyle Rytand Bistrain

Master's Theses

Accurately pricing American options with market data presents a significant challenge, as foundational models like the Black-Scholes-Merton (BSM) model rely on assumptions that deviate from real-world financial data -- such as log-normal returns, constant volatility, and no dividends -- and fail to account for the key early exercise feature of American options. While parametric models can adjust for these features, the complexity of the resulting models renders them prohibitively difficult to apply in practice for nonspecialists. In response, modern machine learning (ML) techniques provide a set of flexible and powerful alternatives, and recent research has explored the application of ML …

Designing The Protocol For An Experimental Flight Simulation Study Encouraging Fuel Efficient Behavior, Thomas S. Reardon

Theses and Dissertations

This study designed and tested an experimental instrument to examine how pilots respond to fuel efficiency feedback in a flight simulator. A standardized flight plan, script, and hardware setup were created using X-Plane 12 software and physical flight simulator hardware. The chosen sortie guided participants from Monterey Regional Airport to Moffett Federal Airfield using instrument flight rules (IFR). The flight script provided step-by-step guidance to ensure consistent behavior across participants. The simulator was mapped to match real cockpit controls and allowed for precise data collection including flight time, altitude, heading, and fuel use. The goal was to support a larger …

Ibi-Dt: A Novel Approach Combining Individualized Bayesian Inference And Decision Tree For Identifying Cancer Drivers And Their Interactions, Md Asad Rahman, Gregory F. Cooper, Jinying Zhao, Xinghua Lu, Jinling Liu

Engineering Management and Systems Engineering Faculty Research & Creative Works

Cancer is mainly caused by a relatively small portion of somatic genome alterations (SGAs), called cancer drivers. Despite success in identifying a good number of cancer drivers, many more remain to be discovered to explain various cancers. Moreover, limited tools are available to identify potential interactions among cancer drivers for a better understanding of oncogenesis. To tackle these challenges, we have developed a novel approach called individualized Bayesian inference using a decision tree (IBI-DT). IBI-DT recognizes the genetic heterogeneity among cancer patients, where different individuals or patient subgroups of distinct genomic makeup may have different drivers. IBI-DT works by constructing …

Effect Of Workplace Design On Collaboration And Satisfaction In Space System Command, Joshua A. Hagood

Theses and Dissertations

This study addresses a significant knowledge gap regarding the influence of physical workplace design on employee collaboration and satisfaction with the physical environment within U.S. Space Force technical military organizations.  While seminal industry research consistently demonstrates that physical design and indoor environmental quality influence employee satisfaction and collaboration (e.g., Candido et al., 2015; Sailer et al., 2021), the understanding of these impacts within military contexts remains limited.  Using a quantitative post-occupancy evaluation survey, adapted from the Sustainable Post Occupancy Evaluation Survey (SPOES), multiple regression analyses revealed that physical elements collectively predict both satisfaction and collaboration.  The final simplified model showed …

Designing An Experiment To Create And Evaluate Behavioral Changes In Air Force Pilots' Fuel Efficiency, Jackson Macias

Theses and Dissertations

Fuel represents over 70% of the logistical resupply demand within the Department of Defense, with the United States Air Force accounting for most of that consumption. While prior fuel efficiency efforts have primarily focused on technical upgrades, this research explores how behavioral interventions can influence pilot decision-making and operational energy outcomes. Using the Theory of Planned Behavior (TPB) as a guiding framework, this study investigates the effects of targeted behavioral strategies on pilots’ attitudes, subjective norms, perceived behavioral control, intentions, and actual fuel-efficient behaviors. A quasi-experimental design was applied through a controlled pilot study using simulator flights. Six participants were …

Trends And Predictive Modeling Of Real Estate Prices In Major Saudi Arabia Cities, Meshal S. Aldahas

Theses and Dissertations

his research examines historical trends and explanatory modeling of real estate prices in major Saudi cities, with a focus on Riyadh, Jeddah, and Dammam. Using a mixed-methods approach, the study integrates quantitative data from 2010–2023, including housing and macroeconomic indicators, with qualitative insights drawn from over 320 survey responses that captured consumer sentiment on affordability, job security, and housing policies. A combination of descriptive statistics, ARIMA and Exponential Smoothing techniques was applied to detect long-term patterns, seasonal variations, and market shocks. Predictive modeling was conducted using Linear Regression, Decision Trees, and Neural Networks, with results showing that job security consistently …

Access To Information On Toddler Family Development Program And Family Participation In Child Growth And Development, Dita Dhammayanti, Demsa Simbolon, Lissa Ervina, Yusran Fauzi

Kesmas

The comprehension of the Toddler Family Development (TFD) Program among families in Indonesia remains limited, likely due to insufficient access to information and low participation rates. Limited participation can negatively affect a family’s ability to support optimal child growth and development. This study examined the relationship between access to information on the TFD Program and family participation in child growth and development. Using secondary data from the 2019 Program Performance and Accountability Survey in Indonesia, the cross-sectional analysis included 21,497 respondents. The results revealed an association between access to information on the TFD Program and family participation in child growth …

Exploring Stunting In South Kalimantan Province Using R Programming-Based Data Visualization, Muhammad Hudaya, Wahyudin Nor, Mellani Yuliastina, Muhammad Nordiansyah

Kesmas

South Kalimantan Province continues to face the challenge of relatively high stunting prevalence despite being endowed with abundant coal resources that could serve as a source of funding for public health. Therefore, this study aimed to examine differences in stunting prevalence among cities, mining districts, and non-mining districts in South Kalimantan to raise stakeholder awareness of disparities across these regional types. This study was conducted between April and December 2024, using secondary data obtained from the Indonesian Ministry of Health and the South Kalimantan Provincial Government. R programming was used to process the data, generate visualizations, and perform analysis of …

Understanding User Needs In Health Crisis Risk Monitoring Information System Development: A Lesson From Tasikmalaya District, Indonesia, Arief Tarmansyah Iman, Hari Kusnanto, Ariani Arista Putri Pertiwi

Kesmas

A health crisis risk monitoring information system needs to be developed, especially during the pre-disaster phase; therefore, understanding the needs of prospective users is crucial. This study aimed to investigate the needs of potential users regarding the development of this system. This study employed a qualitative, exploratory approach to gather user needs from stakeholders through interviews (n = 7) and one focus group discussion (n = 12). The data were audio-recorded, transcribed verbatim, and then thematically analyzed using qualitative content analysis. The need for information was related to disaster preparedness and its preferred format. The system should be targeted, multiplatform, …

Low Economic Level And The Risk Of Overweight Among Indonesian Junior And Senior High School Students, Ariyanto Nugroho, Purwo Setiyo Nugroho, Amarin Yudhana, Sri Sunarti

Kesmas

Overweight and obesity among Indonesian adolescents have emerged as a pressing public health issue, reflecting global trends. This study examines the relationship between economic status and overweight prevalence among junior and senior high school students in Indonesia, using secondary data from the Global School-based Health Survey (GSHS). This study analyzed data from 9,977 students aged 11–18 years through a cross-sectional design and binary logistic regression, adjusting for dietary habits, physical activity, and sedentary behavior. Overall, 14.7% of students were overweight; the prevalence was notably higher among low-income students (27.4%) compared to high-income groups (14.2%). Students from lower economic backgrounds were …