Statistics and Probability Commons^™

An Adaptive Method For Covariate Balancing In Block Randomized Clinical Trials, Ren Rasnick

Theses and Dissertations

Clinical trials are randomized in part to limit allocation bias, but also to ensure comparability between treatment arms for a baseline variable of concern. Comparable with regard to a baseline variable of concern is necessary for the validity of statistical methods. However, comparability is not guaranteed for trials of any size and is even more likely in trials with < 200 total participants. We propose a new method for adapting the allocation of participants in a sequentially allocated two-armed study with a small sample size to better ensure comparability.

The proposed method calculates the expected final imbalance (lack of comparability) based on the current participant values. Unlike several other methods, our method ensures the final desired sample size for each treatment arm, utilizes the expected final imbalance, increases comparability between …

Climate Migration And Urban Survival: Evidence From Chittagong’S Slums, Mohammad Nur Nobi

Graduate Research Theses & Dissertations

This study examines the impact of climate change on rural-to-urban migration in Chittagong, Bangladesh. Based on a primary survey of 400 respondents across 35 slums in the country's second-largest city, the analysis employs two estimation methods: a multinomial logit model to assess the influence of climate-related factors on migration decisions, and a logit model to evaluate the impact of migration on the living conditions of migrants. The results show that individuals involved in ‘agriculture and daily labor’ are most likely to migrate. Compared to the base category (‘Other Reasons’) for migration, the odds ratios for ‘floods’, ‘droughts’, and ‘better job …

Effect Of Universal Health Coverage On Neonatal Mortality Rate In Sub-Saharan Africa: Addressing Missing Data In Health Indicators, Elizabeth Nalule Arihoona

Graduate Research Theses & Dissertations

This study utilizes two mixed-effects models to examine the effect of Universal Health Coverage on Neonatal Mortality Rate (NMR) in 30 countries of Sub-Saharan Africa from 2000-2019 while addressing the missing data in health indicators. Using natural cubic spline interpolation, I impute the missing values in the health coverage indices to preserve the location- specific trends of the data. Findings indicate that among the health Coverage indices, only Index1, which directly relates to coverage of maternal, newborn and child health services is significantly associated with reduced NMR. While higher Current Health Expenditure is associated with reduced NMR, a higher share …

Unlocking The Secrets Of High-Frequency Financial Data: Innovative Approaches To Modeling And Analysis, Lu Zhang

Graduate Research Theses & Dissertations

High-frequency trading (HFT) has emerged as a pivotal innovation in modern financial markets, characterized by rapid, data-driven decision-making processes that capitalize on granular, time-stamped market data. This dissertation examines the predictability of intraday stock price movements during the final 30 minutes of U.S. trading, employing a Bayesian regression model with Student-t error terms to address the limitations of traditional Gaussian-based methods. The analysis reveals a decline in established predictors and the emergence of new dynamics, such as post-Federal Reserve "tug-of-war" effects. The research further advances high-frequency financial modeling by introducing a comprehensive data engineering pipeline and applying cutting-edge deep learning …

Linking Empirical Data And Numerical Simulation To Characterize Dynamic Fire Behavior Associated With Interacting Firelines, Marta Sergeevna Jerebets

Graduate Student Theses, Dissertations, & Professional Papers

Understanding fuel pattern-fire process relationships is key for predicting fire behavior and effects with follow-on benefits to proactive fire management and model validation. To characterize dynamic fire behavior, this thesis leverages empirical data and numerical simulation through two complementary studies.

In the first study, longwave thermal sensors aboard unmanned aerial systems (UAS) were used to capture fine-scale fire behavior in two experimental grass burns. A novel paired design was used to quantify the effects of fuel arrangement on fire behavior with 3.66 m diameter treatments cut to a height of 0.15 m. The treatments ephemerally reduced fire rate of spread …

Investigating Risk Of Suboptimal Hiv Treatment Outcomes (Treatment Failure And Disengagement) Among Pregnant And Postpartum Women Living With Hiv, Kevin Owuor

All ETDs from UAB

The joint United Nations Programme on HIV/AIDS (UNAIDS) has set targets to end the HIV epidemic by improving HIV diagnosis, treatment, and viral suppression to reduce new infections and improve health outcomes for people living with HIV (PLHIV), including pregnant and postpartum women living with HIV (PPWH). After diagnosis, linking PPWH to antiretroviral (ART) treatment is critical to suppress the virus and prevent mother-to-child transmission (MTCT) of HIV. Continuous engagement in care is essential for achieving and maintaining virologic suppression in the peripartum and postpartum period for PPWH, both for their own health and the health of their family. Disengagement …

Predictive Modeling For Healthcare Data Using Nonlinear Bayesian Methods, Prince Kofi Asare

Theses and Dissertations

Unplanned hospital readmissions represent a significant challenge for healthcare systems, contributing to substantial financial burdens and highlighting gaps in patient care coordination. In the U.S., approximately 20% of Medicare beneficiaries are readmitted within 30 days, costing billions annually. Social determinants of health, such as income, housing stability, and social support, account for up to 80% of health outcomes, yet their integration into predictive models remains underexplored. This study introduces a novel Bayesian framework for predicting 30-day readmission risk, combining Gaussian Process models with spike-and-slab priors and Bayesian Lasso regression with Laplace priors. Utilizing Markov Chain Monte Carlo methods, the approach …

Check Your Data Before You Wreck Your Model: The Impact Of Careless Responding On Substance Use Data Quality, Abby L. Braitman, Anna M. Petrey, Jennifer L. Shipley, Rachel Ayala Guzman, Emily Renzoni, Alison Looby, Adrian J. Bravo

Psychology Faculty Publications

Background: The accuracy of survey responses is a concern in research data quality, especially in college student samples. However, examination of the impact of removing participants from analyses who respond inaccurately or carelessly is warranted given the potential for loss of information or sample diversity. This study aimed to understand if careless responding varies across a number of demographic indices, substance use behaviors, and the timing of survey completion.

Method: College students (N = 5809; 70.7% female; 75.7% White, non-Hispanic) enrolled in psychology classes from six universities completed an online survey assessing a variety of demographic and substance use-related information, …

Group Antenatal Care Positively Transforms The Care Experience: Results Of An Effectiveness Trial In Malawi, Crystal L. Patil, Kathleen F. Noor, Esnath Kapito, Li C. Liu, Xiaohan Mei, Elizabeth Chodzaza, Genesis Chorwe-Sungani, Ursula Kafuulafula, Elizabeth T. Abrams, Allissa Desloge, Ashley Gresh, Rohan D. Jeremiah, Dhruvi R. Patel, Anne Batchelder, Heidy Wang, Jocelyn Faydenko, Sharon S. Rising, Ellen Chirwa

Department of Medicine Faculty Publications

Background

We developed and tested a Centering-based group antenatal (ANC) model in Malawi, integrating health promotion for HIV prevention and mental health. We present effectiveness data and examine congruence with only the Group ANC theory of change model, which identifies key processes as supportive relationships, empowered partners in learning and care, and meaningful services, leading to better ANC experiences and outcomes.

Methods

We conducted a hybrid effectiveness-implementation trial at seven clinics in Blantyre District, Malawi, comparing outcomes for 1887 pregnant women randomly assigned to Group ANC or Individual ANC. Group effects on outcomes were summarized and evaluated using t-tests, Mann-Whitney, …

A New G Family: Properties, Characterizations, Different Estimation Methods And Port-Var Analysis For U.K. Insurance Claims And U.S. House Prices Data Sets, Ahmad M. Aboalkhair, Gholamhossein Hamedani, Nazar Ali Ahmed, Mohamed Ibrahim, Mohammad A. Zayed, Haitham M. Yousof

Mathematical and Statistical Science Faculty Research and Publications

This paper introduces a new class of probability distributions, termed the generated log exponentiated polynomial (GLEP) family, designed to enhance flexibility in modeling complex real financial data. The proposed family is constructed through a novel cumulative distribution function that combines logarithmic and exponentiated polynomial structures, allowing for rich distributional shapes and tail behaviors. We present comprehensive mathematical properties, including useful series expansions for the density, cumulative, and quantile functions, which facilitate the derivation of moments, generating functions, and order statistics. Characterization results based on the reverse hazard function and conditional expectations are established. The model parameters are estimated using various …

Early Entering Research And Writing (Eerw) In College-Level Statistics, Rebecca Fang

2025 Faculty Bibliography

With the high demand for data-driven knowledge, students today need to comprehend skills in problem-solving, critical thinking, communication, and collaboration. However, in traditional statistics lectures, students learn descriptive algorithms, hypothesis, and linear regression at their early stage of college. Unfortunately, they often analyze numbers without considering the context, purpose, audience, and the meaning of the numbers. Therefore, providing students the early opportunity to research and write with data in college will allow them to deepen their understanding of the subjects, to think critically about the data and the results, to communicate effectively with diverse audience, and to prepare for their …

Group And State-Specific Estimation In Animal Movement Models Using A Bayesian Approach, Anita Bhandari Sharma

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This research study investigates statistical approaches for modeling the movement patterns of white-tailed deer in Louisiana using GPS tracking data. We start by classifying the latent behavioral states using a hidden Markov model (HMM) and then integrate those inferred states into a state-dependent step selection framework to evaluate the land cover preferences. Standard HMMs, however, assume the same movement patterns for all animals, overlooking the differences due to characteristics such as sex, age, breeding season, etc.

To address this limitation, we extend the modeling framework to incorporate the group-level structure defined by similar characteristics or conditions to assess whether such …

Capital Structure Models And Contingent Convertible Securities, Di Meng

Theses and Dissertations (Comprehensive)

The 2007-09 financial crisis showed financial institutions are vulnerable during distressed times. As an alternative resolution to a government bail-out, contingent convertible securities (contingent capital or CoCos) were proposed by various researchers. CoCo is a hybrid capital security that converts from a bond to common equity when a pre-determined event occurs. The loss absorption mechanism of CoCo is essential to the financial health of a bank during a crisis as it provides an instant capital infusion when public capital is difficult to access.

In this thesis, we first implement a methodology to calibrate capital structure models for large Canadian banks. …

Using Landscape Ecology And Spatial Statistics To Examine The Impacts Of Proposed Removals To Natural Heritage System And The Agricultural System Of Ontario’S Greenbelt, Brianna Downey

Theses and Dissertations (Comprehensive)

The 2022 proposed removals from the Greater Toronto Area (GTA), Southern Ontario’s Greenbelt would have resulted in negative impacts including, reductions to the size and functionality of the Agricultural System and Natural Heritage System, which are components of protected Greenbelt area. Several removal sites were located either on or in close proximity to corridor areas of the NHS, reducing connectivity and negatively impacting the surrounding ecological area. The removal of Agricultural land primarily consisted of corn and soybeans, as well as large removals of woodland, wetland, and shrubland class areas. The removal sites on local Agricultural composition and configuration were …

Analysis Of Cytokine Data In A Case-Control Study Of Me/Cfs, Navya Amaratunga

Electronic Theses & Dissertations (2024 - present)

This study investigated the role of cytokines in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), a debilitating multi-system disease with unknown etiology. Using data from a case-control study (60 cases, 61 controls) previously collected by Dr. Roxana Moslehi’s lab, serum levels of 48 cytokines were analyzed. Statistical analyses, including T-tests, Wilcoxon Rank Sum tests, and logistic regression (unadjusted and adjusted for medication use), were performed to identify differences between cases and controls.

Results revealed a statistically significant difference in mean Fractalkine levels between cases and controls (p=0.031). Borderline significant differences were also observed for IL-6 (p=0.046) and MIP-1α (p=0.046). Unadjusted logistic regression …

Complex Missing Data Problems In Education Surveys, Thomas Wesley Robertson

Electronic Theses & Dissertations (2024 - present)

Missing data are a nearly universal problem in human subjects research, including in education. However, reporting and addressing missing data is an issue, despite guidelines from the APA style guide and the What Works Clearinghouse, as well as guidance from prominent statisticians on the best methods to use. Prior research conducted in 2004 and 2014 found that in the field of education, most studies do not report or address missing data. In addition, no study has looked specifically at how missing data are reported and addressed in complex surveys. The current study has two main objectives: first, to determine if …

Safeguard Cyberspace In Ransomware Era: Risk Analysis & Cyber Insurance, Li Huang

Electronic Theses & Dissertations (2024 - present)

The increasing frequency and severity of ransomware attacks pose significant challenges for organizational cybersecurity. Fragmentation across disciplines in cyber defense has created practical gaps in the development of the necessary capabilities needed to address rapidly evolving cyber threats. This study explores the impact of ransomware attacks and the evolving role of cyber insurance as a proactive cybersecurity partner. Bridging the gap between actuarial science and cyber risk management, it proposes an interdisciplinary framework that quantifies the impact of ransomware and integrates cyber insurance into cybersecurity strategies.

The primary contribution of this study is methodology. We present a framework that remains …

A Two-Stage Design For Choosing Among Several Normal Treatments In Comparison With A Control: The Case Of Common, Known Variance, Samarasuriyage Sayura Sankalpa Senaratne

UNF Graduate Theses and Dissertations

A two-stage design is developed for comparing the means of multiple normally distributed treatment groups under a known common variance, with the aim of identifying the treatment with the highest mean while minimizing the expected sample size, a crucial consideration in clinical trials. The proposed methodology integrates elements of both hypothesis testing and selection procedures to achieve greater efficiency and decision-making power. In the initial stage, if no treatment exhibits a mean surpassing a predefined efficacy threshold, the trial is terminated early, conserving resources. If one or more treatments exceed the threshold, the procedure advances to a second stage, where …

Crime Modeling Using An Integrated Cnn–Lstm Architecture With Embedded Self-Excitation, Pawandeep Kaur

Theses and Dissertations (Comprehensive)

It is often assumed that natural phenomena occur randomly over time. However, careful analysis reveals that these events typically form some series or sequences and exhibit distinctive temporal patterns. These patterns are not exclusive to nature. They also appear in human activities, often studied under the concept of bursty human dynamics. The statistical methods analyzing bursty human dynamics not only capture overall trends or seasonality but also explore how past events influence future ones. It makes the analysis more realistic and the results more closely aligned with reality. Bursty human dynamics can be studied at two levels: the individual level …

The Matryoshka Doll Prior – Principled Multiplicity Correction In Bayesian Model Comparison, Andrew Womack, Daniel Taylor-Rodríguez, Claudio Fuentes

Mathematics and Statistics Faculty Publications and Presentations

This paper introduces a general and principled construction of model space priors with a focus on regression problems. The proposed formulation regards each model as a “local” null hypothesis whose alternatives are the set of models that nest it. Assuming constant ratio of prior probabilities for any “local” null and its alternatives provides a natural isomorphism of model spaces (like a matryoshka doll), constituting an intuitive way to correct for multiplicity in Bayesian model selection and averaging problems. This isomorphism yields the Poisson distribution as the unique limiting distribution over model dimension under mild assumptions. We compare this model space …