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Articles 1 - 30 of 246
Full-Text Articles in Statistics and Probability
A Modified Maximum Likelihood Estimation Algorithm For Modeling Threshold Exceedances With The Generalized Pareto Distribution, Jeffrey Harkness
A Modified Maximum Likelihood Estimation Algorithm For Modeling Threshold Exceedances With The Generalized Pareto Distribution, Jeffrey Harkness
UNLV Theses, Dissertations, Professional Papers, and Capstones
A modified maximum likelihood estimation (MLE) algorithm is proposed for modeling threshold exceedances with the generalized Pareto distribution (GPD). The algorithm addresses multiple issues with an approach originally published in the Journal Computational Statistics and Data Analysis (Castillo and Serra, 2015). The modified algorithm is intended to be comparatively simple to understand and implement, accurate in the handling of boundary conditions, relatively fast and reliable for most data sets, and relatively easy to transfer between computer languages by leveraging existing optimization routines.
A reproducibility study of work in recent literature published in the journal Extremes (Belzile, et al., 2023) is …
Digital Literacy And Language Proficiency As Factors Of Accessible Digital Training In The Hospitality Industry: Employee Perspectives Of Training And Working In A Diverse Industry, Gillian Bowden
UNLV Theses, Dissertations, Professional Papers, and Capstones
This explanatory sequential mixed methods study explored how digital literacy and language proficiency impact employees’ access to and engagement with digital training, as well as how these experiences influence their perceptions of training and the organization. In the quantitative phase, survey data were collected from hourly employees at a large foodservice corporation (n=67). Four constructs were assessed: digital literacy, language proficiency, accessibility, and engagement. Results indicated strong, statistically significant relationships with higher levels of digital literacy and language proficiency associated with greater accessibility and increased engagement with digital training materials. The large effect sizes suggest these competencies play a meaningful …
Effect Of The Sava Syndemic On Hiv Viral Suppression Among People Living With Hiv In The United States: A Scoping Review And Meta-Analysis, Jacquelyn Rodriguez
Effect Of The Sava Syndemic On Hiv Viral Suppression Among People Living With Hiv In The United States: A Scoping Review And Meta-Analysis, Jacquelyn Rodriguez
UNLV Theses, Dissertations, Professional Papers, and Capstones
The SAVA syndemic highlights the interconnected and mutually reinforcing nature of substance use, violence victimization, and HIV/AIDS. The synergistic interaction of these conditions creates structural and behavioral barriers that disrupt the HIV care continuum and contribute to significant health inequities. Achieving a suppressed viral load is a critical clinical outcome for people living with HIV, while viral non-suppression can be an indicator of poor health, elevated transmission risk, and disease progression. Still, the association between SAVA factors and viral suppression/non-suppression outcomes within U.S. populations remains inconsistently characterized due to heterogeneous methodologies and variable inclusion of high-risk groups. This mixed-methods study …
Research Remix: Teams, Tech, And Texts, Jaime Carbajal
Research Remix: Teams, Tech, And Texts, Jaime Carbajal
UNLV Best Teaching Practices Expo
The pedagogical innovation that enhanced student learning in the Research Methodologies in Health Sciences course is described as Integrated Digital Collaborative Inquiry-Based Learning (IDCIBL). The IDCIBL approach leveraged digital tools (lecture videos, podcasts, recorded poster presentations, and Artificial Intelligence (AI) platforms), integrated journal article analysis, utilized research-informed active learning, and included team-based learning activities. The combination of multiple innovative strategies into the IDCIBL model intentionally transforms the educational environment and optimizes the student learning experience, relating to the TLC priority area of teaching and assessments in the age of Gen AI.
A Mechanistic Model Of The Wash Shuffle And Monte Carlo Exploration Of Its Impact On Card Shuffling In Texas Hold’Em, Michael A. Alexeev, Peter B. Chi
A Mechanistic Model Of The Wash Shuffle And Monte Carlo Exploration Of Its Impact On Card Shuffling In Texas Hold’Em, Michael A. Alexeev, Peter B. Chi
UNLV Gaming Research & Review Journal
In casino games using a standard deck of cards, a wash shuffle is sometimes performed prior to the rest of the card shuffling procedure. Unlike other methods of shuffling, the wash shuffle has not yet been well studied. To this end, we first develop a mechanistic model of the wash shuffle based on our observation of how cards tend to move when a wash shuffle is being performed. Then, we use this model to simulate the card shuffling procedure used in casino poker rooms, and explore the resulting impact on where the cards are dealt in the context of Texas …
Cash Or Crash: Return To Player Percentages And Expected Value Of Crash Games, Robert H. Scott Iii, Mikhail M. Sher, Jonathan Daigle
Cash Or Crash: Return To Player Percentages And Expected Value Of Crash Games, Robert H. Scott Iii, Mikhail M. Sher, Jonathan Daigle
UNLV Gaming Research & Review Journal
Crash games are a new type of casino game offered on some online gambling sites. The first crash game was created by the online cryptocurrency casino Bustabit. Other cryptocurrency casinos started offering their own versions of crash games. Now mainstream online casinos have developed their own crash games—notably Rocket by DraftKings. Crash games are easy to learn and play. They offer the opportunity to increase your bet by many hundreds of multiples—though, as we show when deriving expected values, these outcomes are rare. In this paper, we study the history of crash games and calculate theoretical values of crash game …
Testing For Dice Control At Craps, Stewart N. Ethier
Testing For Dice Control At Craps, Stewart N. Ethier
UNLV Gaming Research & Review Journal
Dice control involves “setting” the dice and then throwing them carefully, in the hope of influencing the outcomes and gaining an advantage at craps. How does one test for this ability? To specify the alternative hypothesis, we need a statistical model of dice control. Two have been suggested in the gambling literature, namely the Smith–Scott model and the Wong–Shackleford model. Both models are parameterized by θ ∈ [0, 1], which measures the shooter’s level of control. We propose and compare four test statistics: (a) the sample proportion of 7s; (b) the sample proportion of pass-line wins; (c) the sample mean …
The Dual Impact Of Moral Injury: Links To Ptsd Symptoms And Disinhibited Externalizing In U.S. Combat Veterans, Bianca S. Islas
The Dual Impact Of Moral Injury: Links To Ptsd Symptoms And Disinhibited Externalizing In U.S. Combat Veterans, Bianca S. Islas
UNLV Theses, Dissertations, Professional Papers, and Capstones
Moral injury is an experience of psychological distress that occurs when a person’s morals are violated by themselves or others, including institutions and organizations. Such violations of morality can be impairing and have high rates of comorbidity with internalizing disorders (posttraumatic stress, depression, anxiety, suicidality), which may indicate that moral injury is a transdiagnostic construct. This study had four aims, which were accomplished using from a nationally representative, probability-based sample of 1,353 US military veterans. In the first aim, we created structural models of moral injury using the Moral Injury Events Scale (for which a bifactor structure with a specific …
Rna’S Symphony: Harmonizing Splice Junctions And Exon Counts For A Novel Approach To Differential Splicing Analysis, Jelard Aquino
Rna’S Symphony: Harmonizing Splice Junctions And Exon Counts For A Novel Approach To Differential Splicing Analysis, Jelard Aquino
UNLV Theses, Dissertations, Professional Papers, and Capstones
Alternative Splicing (AS) plays a critical role in transcriptome complexity and cell-type-specific gene regulation, yet its analysis remains methodologically fragmented, especially in the context of noisy and sparse single-cell RNA sequencing (scRNA-seq) data. This dissertation addresses key computational challenges in AS detection by evaluating existing tools, developing integrative frameworks, and proposing new strategies for improving analysis accuracy in both bulk and single-cell contexts. In chapter 1, I present a comprehensive literature review of computational tools designed for detecting and quantifying AS from bulk and scRNA-seq data. This review outlines major methodological paradigms, including exon-based and splice junction-based approaches, and evaluates …
Empowering Science With The World's First High Accuracy And High Throughput Functional Assay, Christopher Giacoletto
Empowering Science With The World's First High Accuracy And High Throughput Functional Assay, Christopher Giacoletto
UNLV Theses, Dissertations, Professional Papers, and Capstones
Understanding the functional consequences of genetic mutations remains a central challenge in modern biology, with far-reaching implications for human health and disease. While early systematic methods like alanine scanning and phage display provided foundational insights into protein structure and function, the emergence of high-throughput approaches—such as Multiplexed Assays of Variant Effect (MAVEs)—and predictive tools powered by artificial intelligence have vastly expanded our ability to profile mutational landscapes. However, these methods are often constrained by trade-offs between accuracy, scalability, and biological relevance.This dissertation presents the development and application of the GigaAssay, the world’s first high-throughput functional assay capable of delivering both …
“Do You Even Lift, Bro?”: Correlates Of Muscle Dysmorphia Symptomatology In Filipino Male University Students, Pamela Paula C. Pioquinto
“Do You Even Lift, Bro?”: Correlates Of Muscle Dysmorphia Symptomatology In Filipino Male University Students, Pamela Paula C. Pioquinto
UNLV Theses, Dissertations, Professional Papers, and Capstones
Muscle Dysmorphia (MD) is a subtype of Body Dysmorphic Disorder (BDD) and is marked by the desire to increase muscularity and reduce body fat. MD is typically more prevalent among younger male populations, and it often drives comorbid disorders, including substance abuse, eating disorders, and social anxiety. Despite the growing literature on MD, it remains understudied in certain racial/ethnic populations, such as Filipinos. Acculturation, defined as the process in which an individual adopts, acquires, and adapts to a new cultural environment as a result of immigration, influences body image by reshaping an individual’s perceptions of beauty and muscularity standards. Guided …
Associations Of The Medicaid Expansion Policy With Racial/Ethnic Disparities In Breast Cancer Screening And Treatment, James Howard Smith Ii
Associations Of The Medicaid Expansion Policy With Racial/Ethnic Disparities In Breast Cancer Screening And Treatment, James Howard Smith Ii
UNLV Theses, Dissertations, Professional Papers, and Capstones
Background and Aim. This dissertation examines Medicaid expansion’s effect on breast cancer (BC) screening and treatment disparities in two Medicaid-expanding states (MES) that passed Medicaid expansion (New Jersey and Vermont) relative to two non-expansion states (NES) (Georgia and Wisconsin). It then compares the association of Medicaid expansion to other states that did not undertake this policy on various subgroups, such as minorities by race and ethnicity, income, and age groups. Black women still bear significant BC disparities due to untimely screenings, treatments, and deaths. Therefore, it is critical to investigate how socioeconomic status influences racial/ethnic disparity gaps, given that BC …
Contribution Of Various Factors On The Rate Of Traffic Accidents In The Us, Martin Mnatsakanyan
Contribution Of Various Factors On The Rate Of Traffic Accidents In The Us, Martin Mnatsakanyan
Undergraduate Research Symposium Lightning Talks
Background:
Until 2020, the number of traffic accidents has been steadily decreasing. After 2020, the number started increasing until 2022, then started s lowly decreasing again. Most drivers aren’t fully aware of the reason behind all of these accidents.
Using Neighborhood Information To Improve Fiber Direction Estimation From Neuroimaging Data, Anjan Mandal
Using Neighborhood Information To Improve Fiber Direction Estimation From Neuroimaging Data, Anjan Mandal
UNLV Theses, Dissertations, Professional Papers, and Capstones
Accurately estimating neuronal fiber directions is crucial in neuroimaging analysis. The Ball-and-Stick Model (BSM), introduced by Behrens et al. (2003), and widely used in software tools like FSL, remains one of the most popular models for this purpose. BSM analyzes each voxel individually, based solely on its signal information.In this dissertation, we propose modifications to BSM, that incorporate signal information from neighboring voxels in the estimation process, potentially improving the accuracy of the estimates. Additionally, within the estimation process, we introduce two novel proposal distributions to enhance the efficiency of the Markov chain Monte Carlo sampling procedure on the simplex …
Application Of Machine Learning Algorithms In Healthcare, Dwaipayan Mukhopadhyay
Application Of Machine Learning Algorithms In Healthcare, Dwaipayan Mukhopadhyay
UNLV Theses, Dissertations, Professional Papers, and Capstones
Machine Learning (ML) is a subset of artificial intelligence that has made substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, amongst a few fields of healthcare. Here we provide a brief overview of machine learning-based approaches and learning algorithms. Second, we discuss a general procedure of ML and review some studies presented in ML application for several healthcare fields. We also briefly discuss the risks and challenges of ML application to healthcare.This dissertation also consists of four different cases in healthcare where we have applied ML techniques on real life data sets. …
Development And Pilot Testing Of A Surface Discrimination Test For People With Lower Limb Amputation, Colin Kruger, Kyle Mcknight, Sharlene Lim, Samuel Straus
Development And Pilot Testing Of A Surface Discrimination Test For People With Lower Limb Amputation, Colin Kruger, Kyle Mcknight, Sharlene Lim, Samuel Straus
UNLV Theses, Dissertations, Professional Papers, and Capstones
Introduction: There is a lack of understanding as to how sensory loss and sensory deficits impact those with LLA. The purpose of this research is to determine the extent to which people with LLA can discriminate between surfaces underfoot, in order to better understand the relationship between people with LLA and their perception of the ground they are walking on. We developed a test to determine which qualities of surfaces may be easier to distinguish.
Methods: 10 unimpaired adults and 2 adults with LLA participated. Participants compared surfaces underfoot that consisted of ceramic, rough tile, gravel, sand, and sandpaper to …
Statistical Classification Using Selection And Ranking Methodologies With Statistical Learning, Jeong Jun Lee
Statistical Classification Using Selection And Ranking Methodologies With Statistical Learning, Jeong Jun Lee
UNLV Theses, Dissertations, Professional Papers, and Capstones
The subject of Statistical Classification is concerned with identifying and allocating future observations into one of the pre-categorized classes based on the characteristics of the objects. Typically, these decisions to classify and categorize the objects have been dependent on identifying a system of classification, and from there, determining attributes for sorting.
In past decades, from discriminant analysis, various methods have been developed for classification. In particular, the rise of artificial intelligence (AI), machine learning, and statistical learning theory has made it possible to consider improving the existing methods along with new developments and more comprehensive schemes in conjunction with data-driven …
Identifying Disease-Related Gene-Environment Interactions Based On Method Of Moments, Linchuan Shen
Identifying Disease-Related Gene-Environment Interactions Based On Method Of Moments, Linchuan Shen
UNLV Theses, Dissertations, Professional Papers, and Capstones
Human diseases are often caused by a complex interplay of multiple factors, including genetics and environmental factors. These factors can play critical roles in the development and progression of diseases. Although genome-wide association studies (GWAS) have successfully identified many genetic variants associated with human diseases, the estimated effects of these variants are small and can explain only a relatively small portion of the heritability of the underlying diseases.
Detecting gene-environment interactions (G × E) can shed light on the biological mechanisms of diseases. However, most existing methods that investigate G × E only look at how one environmental …
Effect Of Asynchronous Virtual Interviews On Ethnic Minority Matriculation Into A Doctor Of Physical Therapy Program, Conner Clark, Nanea Lagasca, Gladys Miller, Jasmine Puspos
Effect Of Asynchronous Virtual Interviews On Ethnic Minority Matriculation Into A Doctor Of Physical Therapy Program, Conner Clark, Nanea Lagasca, Gladys Miller, Jasmine Puspos
UNLV Theses, Dissertations, Professional Papers, and Capstones
Purpose/Methods: This study examines the impact of the use of asynchronous virtual interviews (AVIs) in the admissions process of the Doctor of Physical Therapy (DPT) program at the University of Nevada, Las Vegas (UNLV). This research aims to examine racial and ethnic subgroup differences in AVI scores, evaluate the influence of AVIs on applicant scores in the admissions process, and assess the AVI inter-rater reliability among faculty evaluators using data from the 2019-2022 admissions cycles.
Results: Significant differences were found in AVI scores among racial and ethnic groups, with Black applicants scoring highest and Asian applicants scoring lowest. Additionally, inclusion …
Examining Covid-19 Vaccine Hesitancy Among The Nevada African American Population Using The Social-Ecological Model, Katelyn Faulk
Examining Covid-19 Vaccine Hesitancy Among The Nevada African American Population Using The Social-Ecological Model, Katelyn Faulk
UNLV Theses, Dissertations, Professional Papers, and Capstones
In Nevada, COVID-19 vaccines have been widely available to the general population since March 2021; however, even with the wide availability of these vaccines only 40% of the African American population in Nevada has been fully vaccinated against COVID-19 as of May 2023. This is problematic as it has been shown that the African American population is disproportionately affected by COVID-19 with higher rates of cases, hospitalizations, and deaths when compared to other races or ethnicities. Through the literature, it has also been well documented that African Americans may experience hesitancy toward these vaccinations for a multitude of reasons including …
Development Of A Metapgs For Accurate Prediction Of Osteoporotic Fracture, Xiangxue Xiao
Development Of A Metapgs For Accurate Prediction Of Osteoporotic Fracture, Xiangxue Xiao
UNLV Theses, Dissertations, Professional Papers, and Capstones
Introduction: Early identification of individuals at high-risk for osteoporotic fractures who may benefit from preventive intervention is essential. However, the predictive accuracy of the currently used fracture risk assessment tool remains suboptimal. The first aim of this research is to construct genome-wide polygenic scores for the femoral neck (PGS_FNBMDidpred) and total body BMD (PGS_TBBMDidpred) and to estimate their potential in identifying individuals with a high risk of osteoporotic fractures. The second aim is to validate the predictive performance of two previously established PGSs (PGS_FNBMDidpred and PGS_TBBMDidpred) in an external cohort …
Synergy And Antagonism In Log-Linear Models, Md Nahid Hasan
Synergy And Antagonism In Log-Linear Models, Md Nahid Hasan
UNLV Theses, Dissertations, Professional Papers, and Capstones
Synergy and antagonism have been extensively studied in the context of the statistical analysis of drug combinations given to treat a disease. “Synergy” (“antagonism”, resp.) in a drug combination occurs when the desirable effect of two drugs given together for treating a disease is greater than (less than, resp.) the effect of each drug given separately.
In this dissertation, however, we study “synergy” and “antagonism” in log-linear models. We also give a thorough review and extend several epidemiological definitions of synergy and antagonism for categorical data, and we connect these definitions to the definitions of synergy and antagonism in log-linear …
Benchmarking And Practical Evaluation Of Machine And Statistical Learning Methods In Credit Scoring: A Method Selection Perspective, Gwen Verbeck
UNLV Theses, Dissertations, Professional Papers, and Capstones
Predictive models are important tools used in all scientific fields. Machine learning (ML) algorithms and statistical models are widely used for decision-making because of their capability to tackle intricate and unique problems. In domains where data are high-dimensional and contain irrelevant and redundant features, ML algorithms are known to have superior performance over traditional (statistical) learning methods. However, researchers and analysts are often faced with a myriad of techniques to choose from, with no clear consensus on which will perform best for their specific task. Considering resource limitations, exhaustive exploration of all available methods is impractical and often fails to …
Polygenic Risk Score Development And Validation For Early Detection And Risk Stratification Of Rheumatoid Arthritis And Osteoarthritis In Postmenopausal Women, Yingke Xu
UNLV Theses, Dissertations, Professional Papers, and Capstones
Introduction: Around one in four adults worldwide suffer from arthritis. There are more than one hundred different forms of arthritis; the two most common forms of arthritis are rheumatoid arthritis (RA) and osteoarthritis (OA). RA is an autoimmune disease that can cause joint inflammation. Around 1.3 million adults in the US suffer from RA, representing 0.6%–1% of the population. The RA diagnosis in its early stages is difficult since its signs and symptoms are similar to other arthritis. OA is the most common form of arthritis. In the US, around 30.8 million people are affected by this disease. However, OA …
Statistical Methods To Generate Artificial Slot Floor Data For The Advancement Of Casino Related Research, Courtney Bonner, Anastasia (Stasi) D. Baran, Jason D. Fiege, Saman Muthukumarana
Statistical Methods To Generate Artificial Slot Floor Data For The Advancement Of Casino Related Research, Courtney Bonner, Anastasia (Stasi) D. Baran, Jason D. Fiege, Saman Muthukumarana
International Conference on Gambling & Risk Taking
Abstract:
A common difficulty when researching gambling topics is the availability of high-quality data sets for development and testing. Due to the high level of secrecy within the gambling industry, if data is obtained for research purposes it is often prohibitively obfuscated, incomplete, or aggregated. Although these data have allowed for advancement in academic work, it leaves both the researchers and readers left wondering about what would be possible if more detailed data sets were available. To mitigate the paucity of data available to researchers, we present a Markov chain-based statistical process for producing artificial event data for a simulated …
Payments Data In Gambling Research, Kasra Ghaharian, Mana Azizsoltani
Payments Data In Gambling Research, Kasra Ghaharian, Mana Azizsoltani
International Conference on Gambling & Risk Taking
A considerable body of gambling-related research has leveraged gamblers' behavioral tracking data to address a broad set of research questions. These data have typically comprised of gamblers' betting-related behaviors including, for example, the frequency and volume of betting. The analysis of gamblers' payment-related behavioral data is far less common, but provides a fruitful avenue gambling-related research.
In this presentation we discuss a selection of potential research opportunities that payments transaction data presents. We supplement this discussion with specific analyses that have been performed by our research group. We also discuss knowledge gaps and areas for future research.
A Game-Theoretic Analysis Of Baccara Chemin De Fer, Ii, Stewart N. Ethier, Jiyeon Lee
A Game-Theoretic Analysis Of Baccara Chemin De Fer, Ii, Stewart N. Ethier, Jiyeon Lee
International Conference on Gambling & Risk Taking
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The Rocket: Analyzing Rtp (Return To Player), Payoff Distribution And Player Behavior In Crash Games, Mikhail M. Sher, Robert Haywood Scott Iii, Jonathan A. Daigle
The Rocket: Analyzing Rtp (Return To Player), Payoff Distribution And Player Behavior In Crash Games, Mikhail M. Sher, Robert Haywood Scott Iii, Jonathan A. Daigle
International Conference on Gambling & Risk Taking
Abstract
Rocket is a crash game developed by DraftKings, an American publicly traded online casino, sports betting and fantasy sports company. DraftKings Rocket is a game played with a rising rocket. Players must exit the rocket at any point before the rocket crashes. In that case they receive the payoff in accordance to the multiplier of their exit point. If the rocket crashes before the player bails, player’s payoff is 0 (and they lose their bet).
The game boasts an unprecedented 97% RTP (Return to Player). For comparison, Atlantic City casino slots typically have a 91-92% RTP, while Vegas casino …
Testing For Dice Control Based On Observations Of The Length Of The Shooter's Hand, Stewart N. Ethier, Hokwon Cho
Testing For Dice Control Based On Observations Of The Length Of The Shooter's Hand, Stewart N. Ethier, Hokwon Cho
International Conference on Gambling & Risk Taking
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Stake Size And Wagering In A Professional Betting Environment – When Data Affects Decision Making, Anthony Bedford, Tristan Barnett
Stake Size And Wagering In A Professional Betting Environment – When Data Affects Decision Making, Anthony Bedford, Tristan Barnett
International Conference on Gambling & Risk Taking
In this work, we discuss the structure of a number of professional wagering organisations, and how they attempt to deal with the “Ender’s Game” effect – when knowledge of the true nature of the ‘war being wagered’ may have affected the process and choice of betting. We analyse the responses from professional wagering and betting organisations, whom operate predominately in Horseracing and sportsbetting, and they identify the importance of separation of decisions around choices to make and the stakes and size of wagers that are linked to the decisions. The proposed model, practically carried out by one company, is an …