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Articles 1 - 30 of 41
Full-Text Articles in Categorical Data Analysis
Beyond The Lace Index: Benchmarking Machine Learning Architectures And Explaining 30-Day Hospital Readmission Risk With Shap Analysis, Carl E. Hughes Iii
Beyond The Lace Index: Benchmarking Machine Learning Architectures And Explaining 30-Day Hospital Readmission Risk With Shap Analysis, Carl E. Hughes Iii
Williams Honors College, Honors Research Projects
Unplanned 30-day hospital readmission remains a fundamental challenge in US healthcare, associated with increased risk to patient recovery and representing an estimated $52.4 billion in annual expenses (Beauvais et al., 2022). While the rigorously validated LACE index serves as the clinical standard for readmission modeling, its linear structure and four explanatory variables lack the complexity to capture the high-dimensional and interactive nature of patient risk. This study utilizes an admission granularity level cohort of the MIMIC-IV database to develop and compare machine learning architectures against the baseline LACE index. Due to the imbalanced prevalence of readmission, the penalized logistic regression, …
An Application Of An In-Depth Advanced Statistical Analysis In Exploring The Dynamics Of Depression, Sleep Deprivation, And Self-Esteem, Muslihat Gaffari
An Application Of An In-Depth Advanced Statistical Analysis In Exploring The Dynamics Of Depression, Sleep Deprivation, And Self-Esteem, Muslihat Gaffari
Electronic Theses and Dissertations
Depression, intertwined with sleep deprivation and self-esteem, presents a significant challenge to mental health worldwide. The research shown in this paper employs advanced statistical methodologies to unravel the complex interactions among these factors. Through log-linear homogeneous association, multinomial logistic regression, and generalized linear models, the study scrutinizes large datasets to uncover nuanced patterns and relationships. By elucidating how depression, sleep disturbances, and self-esteem intersect, the research aims to deepen understanding of mental health phenomena. The study clarifies the relationship between these variables and explores reasons for prioritizing depression research. It evaluates how statistical models, such as log-linear, multinomial logistic regression, …
Factors Predictive Of The Development Of Surgical Site Infection In Thyroidectomy, A Replication Study Of Myssiorek (2018), Kaitlyn M. Kenig
Factors Predictive Of The Development Of Surgical Site Infection In Thyroidectomy, A Replication Study Of Myssiorek (2018), Kaitlyn M. Kenig
Capstone Experience: Master of Public Health
The original study aimed to show that thyroidectomy does not result in surgical site infection (SSI) in most cases, and thus routine prescription of antibiotics is not necessary. The study looked to see what risk factors could predict the incidence of SSI. This would highlight those individuals who were at most risk of developing SSI, and then antibiotics would only be prescribed to these individuals instead of all or most individuals who undergo thyroidectomy.
This study used NSQIP data to look at incidence of SSI and look for risk factors that may be predictive of SSI. Only surgeries that were …
Latent Classification Of Multi-Model Non-Homogeneous Continuous-Time Markov Chains, Joonha Chang
Latent Classification Of Multi-Model Non-Homogeneous Continuous-Time Markov Chains, Joonha Chang
Dissertations and Theses (Open Access)
The continuous-time Markov chain (CTMC) model and latent clustering models are commonly used to study longitudinal measures of categorical outcomes. Because of its simple but powerful Markovian property, CTMC models have been widely used in medical and public health researches. Due to limitations in the standard CTMC model, there have been some studies on non-homogeneous continuous-time Markov chain (NH-CTMC) that utilized time-dependent rates, but the progresses have been limited. NH-CTMC can be more powerful than CTMC by its default nature of time-dependent rate that can be fitted to a wider range of applications in medical studies. In this study, we …
Tropical Fish Study In Tahiti, French Polynesia, Miranda Brainard, Caitlyn Swango, Paityn Houglan, Richard Londraville
Tropical Fish Study In Tahiti, French Polynesia, Miranda Brainard, Caitlyn Swango, Paityn Houglan, Richard Londraville
Williams Honors College, Honors Research Projects
In May of 2023, I embarked on an exciting research journey to Moorea, French Polynesia, alongside fellow students and faculty members from the University of Akron and Syracuse University. This expedition was part of the university-sponsored Tropical Vertebrate Biology course, where we delved into the exploration of various tropical species inhabiting the island, including sea urchins, geckos, and my primary focus, the blackspotted rockskipper.
My research team, composed of my co-authors and me, was particularly intrigued by the unique refuge-seeking behavior displayed by blackspotted rockskippers. These amphibious fish are renowned for their remarkable ability to inhabit tide pools and rocky …
Multiscale Modelling Of Brain Networks And The Analysis Of Dynamic Processes In Neurodegenerative Disorders, Hina Shaheen
Multiscale Modelling Of Brain Networks And The Analysis Of Dynamic Processes In Neurodegenerative Disorders, Hina Shaheen
Theses and Dissertations (Comprehensive)
The complex nature of the human brain, with its intricate organic structure and multiscale spatio-temporal characteristics ranging from synapses to the entire brain, presents a major obstacle in brain modelling. Capturing this complexity poses a significant challenge for researchers. The complex interplay of coupled multiphysics and biochemical activities within this intricate system shapes the brain's capacity, functioning within a structure-function relationship that necessitates a specific mathematical framework. Advanced mathematical modelling approaches that incorporate the coupling of brain networks and the analysis of dynamic processes are essential for advancing therapeutic strategies aimed at treating neurodegenerative diseases (NDDs), which afflict millions of …
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Journal of Nonprofit Innovation
Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.
Imagine Doris, who is …
Utilizing New Technologies To Measure Therapy Effectiveness For Mental And Physical Health, Jonathan Ossie
Utilizing New Technologies To Measure Therapy Effectiveness For Mental And Physical Health, Jonathan Ossie
Dissertations
Mental health is quickly becoming a major policy concern, with recent data reporting increasing and disproportionately worse mental health outcomes, including anxiety, depression, increased substance abuse, and elevated suicidal ideation. One specific population that is especially high risk for these issues is the military community because military conflict, deployment stressors, and combat exposure contribute to the risk of mental health problems.
Although several pharmacological approaches have been employed to combat this epidemic, their efficacy is mixed at best, which has led to novel nonpharmacological approaches. One such approach is Operation Surf, a nonprofit that provides nature-based programs advocating the restorative …
Employee Attrition: Analyzing Factors Influencing Job Satisfaction Of Ibm Data Scientists, Graham Nash
Employee Attrition: Analyzing Factors Influencing Job Satisfaction Of Ibm Data Scientists, Graham Nash
Symposium of Student Scholars
Employee attrition is a relevant issue that every business employer must consider when gauging the effectiveness of their employees. Whether or not an employee chooses to leave their job can come from a multitude of factors. As a result, employers need to develop methods in which they can measure attrition by calculating the several qualities of their employees. Factors like their age, years with the company, which department they work in, their level of education, their job role, and even their marital status are all considered by employers to assist in predicting employee attrition. This project will be analyzing a …
Prevalence Of Sars-Cov-2 Antibodies In Liberty University Student Population, Emily Bonus
Prevalence Of Sars-Cov-2 Antibodies In Liberty University Student Population, Emily Bonus
Senior Honors Theses
In 2020, the virus SARS-CoV-2 gained attention as it spread around the world. Its antibodies are poorly understood, and little research focuses on those with few COVID-19 complications yet large numbers of close contacts: university students. This longitudinal study recorded SARS-CoV-2 antibody presence in 107 undergraduate Liberty University students twice during early 2021. After extensive data cleaning and the application of various statistical tests and ANOVAs, the data seems to show that in the case of COVID-19 infections, SARS-CoV-2 IgM antibodies are immediately produced, and then IgG antibodies follow later. However, the COVID-19 vaccine causes the production of both IgM …
Knowledge Discovery On The Integrative Analysis Of Electrical And Mechanical Dyssynchrony To Improve Cardiac Resynchronization Therapy, Zhuo He
Dissertations, Master's Theses and Master's Reports
Cardiac resynchronization therapy (CRT) is a standard method of treating heart failure by coordinating the function of the left and right ventricles. However, up to 40% of CRT recipients do not experience clinical symptoms or cardiac function improvements. The main reasons for CRT non-response include: (1) suboptimal patient selection based on electrical dyssynchrony measured by electrocardiogram (ECG) in current guidelines; (2) mechanical dyssynchrony has been shown to be effective but has not been fully explored; and (3) inappropriate placement of the CRT left ventricular (LV) lead in a significant number of patients.
In terms of mechanical dyssynchrony, we utilize an …
Smoking, Alcohol Consumption, And Depression In Association With Incidence Of Type 2 Diabetes Among Mexican Americans In Starr County, Texas, Gabriela Rubannelsonkumar
Smoking, Alcohol Consumption, And Depression In Association With Incidence Of Type 2 Diabetes Among Mexican Americans In Starr County, Texas, Gabriela Rubannelsonkumar
Honors Program Theses and Research Projects
Previous studies on conditions like obesity, hypertension, and type 2 diabetes mellitus (T2DM) have explored the correlations between them and various other human conditions, including aortic stiffness, left ventricular hypertrophy and sleep apnea, as they predict possibilities of developing certain diseases in Mexican Americans. This study aims to observe the correlation between lifestyle decisions that could relate to the onset of the depression in normal, prediabetic, and diabetic individuals. These include smoking habits and alcohol consumption. Many papers have previously conducted research on these lifestyle habits as they relate to obesity, hypertension, diabetes, however, have done so in a singular …
Bayesian Variable Selection Strategies In Longitudinal Mixture Models And Categorical Regression Problems., Md Nazir Uddin
Bayesian Variable Selection Strategies In Longitudinal Mixture Models And Categorical Regression Problems., Md Nazir Uddin
Electronic Theses and Dissertations
In this work, we seek to develop a variable screening and selection method for Bayesian mixture models with longitudinal data. To develop this method, we consider data from the Health and Retirement Survey (HRS) conducted by University of Michigan. Considering yearly out-of-pocket expenditures as the longitudinal response variable, we consider a Bayesian mixture model with $K$ components. The data consist of a large collection of demographic, financial, and health-related baseline characteristics, and we wish to find a subset of these that impact cluster membership. An initial mixture model without any cluster-level predictors is fit to the data through an MCMC …
Statistical Modeling For High-Dimensional Compositional Data With Applications To The Human Microbiome, Thy Dao
Graduate Theses and Dissertations
Compositional data refer to the data that lie on a simplex, which are common in many scientific domains such as genomics, geology, and economics. As the components in a composition must sum to one, traditional tests based on unconstrained data become inappropriate, and new statistical methods are needed to analyze this special type of data. This dissertation is motivated by some statistical problems arising in the analysis of compositional data. In particular, we focus on the high-dimensional and over-dispersed setting, where the dimensionality of compositions is greater than the sample size and the dispersion parameter is moderate or large. In …
Maternal Proximity To Mountaintop Removal Mining And Birth Defects In Appalachian Kentucky, 1997-2003, Daniel B. Cooper
Maternal Proximity To Mountaintop Removal Mining And Birth Defects In Appalachian Kentucky, 1997-2003, Daniel B. Cooper
Theses and Dissertations--Public Health (M.P.H. & Dr.P.H.)
Background: Extraction of coal through mountaintop removal mining (MTR) alters many dimensions of the landscape, and explosive blasts, exposed rock, and coal washing have the potential to pollute air and water with substances known to increase risk of developmental and birth anomalies. Previous research suggests that infants born to mothers living in MTR coal mining counties have higher prevalence of most types of birth defects.
Objectives: This study seeks to examine further the relationship between MTR activity and birth defects by employing individual level exposure estimation through precise satellite data of MTR activity in the Appalachian region and maternal residence …
Statistical Approaches For Estimation And Comparison Of Brain Functional Connectivity, Jifang Zhao
Statistical Approaches For Estimation And Comparison Of Brain Functional Connectivity, Jifang Zhao
Theses and Dissertations
Drug addiction can lead to many health-related problems and social concerns. Functional connectivity obtained from functional magnetic resonance imaging (fMRI) data promotes a variety of fundamental understandings in such association. Due to its complex correlation structure and large dimensionality, the modeling and analysis of the functional connectivity from neuroimage are challenging. By proposing a spatio-temporal model for multi-subject neuroimage data, we incorporate voxel-level spatio-temporal dependencies of whole-brain measurements to improve the accuracy of statistical inference. To tackle large-scale spatio-temporal neuroimage data, we develop a computationally efficient algorithm to estimate the parameters. Our method is used to identify functional connectivity and …
Direct Questioning Of Sensitive Topics In Public Health Studies: A Simulation Study, Jessica K. Fox, Evrim Oral
Direct Questioning Of Sensitive Topics In Public Health Studies: A Simulation Study, Jessica K. Fox, Evrim Oral
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Improving The Quality And Design Of Retrospective Clinical Outcome Studies That Utilize Electronic Health Records, Oliwier Dziadkowiec, Jeffery Durbin, Vignesh Jayaraman Muralidharan, Megan Novak, Brendon Cornett
Improving The Quality And Design Of Retrospective Clinical Outcome Studies That Utilize Electronic Health Records, Oliwier Dziadkowiec, Jeffery Durbin, Vignesh Jayaraman Muralidharan, Megan Novak, Brendon Cornett
HCA Healthcare Journal of Medicine
Electronic health records (EHRs) are an excellent source for secondary data analysis. Studies based on EHR-derived data, if designed properly, can answer previously unanswerable clinical research questions. In this paper we will highlight the benefits of large retrospective studies from secondary sources such as EHRs, examine retrospective cohort and case-control study design challenges, as well as methodological and statistical adjustment that can be made to overcome some of the inherent design limitations, in order to increase the generalizability, validity and reliability of the results obtained from these studies.
Novel Inference Methods For Generalized Linear Models Using Shrinkage Priors And Data Augmentation., Arinjita Bhattacharyya
Novel Inference Methods For Generalized Linear Models Using Shrinkage Priors And Data Augmentation., Arinjita Bhattacharyya
Electronic Theses and Dissertations
Generalized linear models have broad applications in biostatistics and sociology. In a regression setup, the main target is to find a relevant set of predictors out of a large collection of covariates. Sparsity is the assumption that only a few of these covariates in a regression setup have a meaningful correlation with an outcome variate of interest. Sparsity is incorporated by regularizing the irrelevant slopes towards zero without changing the relevant predictors and keeping the resulting inferences intact. Frequentist variable selection and sparsity are addressed by popular techniques like Lasso, Elastic Net. Bayesian penalized regression can tackle the curse of …
Inference Of Heterogeneity In Meta-Analysis Of Rare Binary Events And Rss-Structured Cluster Randomized Studies, Chiyu Zhang
Inference Of Heterogeneity In Meta-Analysis Of Rare Binary Events And Rss-Structured Cluster Randomized Studies, Chiyu Zhang
Statistical Science Theses and Dissertations
This dissertation contains two topics: (1) A Comparative Study of Statistical Methods for Quantifying and Testing Between-study Heterogeneity in Meta-analysis with Focus on Rare Binary Events; (2) Estimation of Variances in Cluster Randomized Designs Using Ranked Set Sampling.
Meta-analysis, the statistical procedure for combining results from multiple studies, has been widely used in medical research to evaluate intervention efficacy and safety. In many practical situations, the variation of treatment effects among the collected studies, often measured by the heterogeneity parameter, may exist and can greatly affect the inference about effect sizes. Comparative studies have been done for only one or …
Association Of Copy Number Variations With Chronic Hepatitis B In Chinese Population, Fang Niu
Association Of Copy Number Variations With Chronic Hepatitis B In Chinese Population, Fang Niu
Capstone Experience: Master of Public Health
With one third of the Hepatitis B virus (HBV) infection population of the world, chronic Hepatitis B (CHB) has become a top burden in China. CHB is a lifelong infection with HBV which can cause serious health problems, like cirrhosis, liver cancer or even death. HBV infection is known to result in various clinical conditions, including asymptomatic HBV carriers to chronic hepatitis and primary hepatocellular carcinoma. Several studies have shown that host genetic susceptibility could be an important factor that determines these various outcomes of HBV infection. Many Single Nucleotide Polymorphisms (SNPs) and Copy Number Variations (CNVs) have been associated …
Statin Prescription For Patients With Atherosclerotic Cardiovascular Disease From National Survey Data, Kristina Vatcheva, Vicente Aparicio, Ayesha Araya, Eduardo Gonzalez, Susan T. Laing
Statin Prescription For Patients With Atherosclerotic Cardiovascular Disease From National Survey Data, Kristina Vatcheva, Vicente Aparicio, Ayesha Araya, Eduardo Gonzalez, Susan T. Laing
School of Mathematical & Statistical Sciences Faculty Publications
Despite strong evidence for the use of statins for patients with atherosclerotic cardiovascular disease (ASCVD), statin prescription is still suboptimal. We aimed to determine the rates and factors that influence statin prescription using national survey data. This is a cross-sectional retrospective study on 8,468 patients with clinical ASCVD who were drawn from the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey from years 2011 to 2015. Survey-weighted analysis was conducted to estimate weighted prevalence and odds ratios for statin prescription. There was a significant increase in statin prescription from the years 2011 to 2015. Nevertheless, …
Data Analytics Pipeline For Rna Structure Analysis Via Shape, Quinn Nelson
Data Analytics Pipeline For Rna Structure Analysis Via Shape, Quinn Nelson
UNO Student Research and Creative Activity Fair
Coxsackievirus B3 (CVB3) is a cardiovirulent enterovirus from the family Picornaviridae. The RNA genome houses an internal ribosome entry site (IRES) in the 5’ untranslated region (5’UTR) that enables cap-independent translation. Ample evidence suggests that the structure of the 5’UTR is a critical element for virulence. We probe RNA structure in solution using base-specific modifying agents such as dimethyl sulfate as well as backbone targeting agents such as N-methylisatoic anhydride used in Selective 2’-Hydroxyl Acylation Analyzed by Primer Extension (SHAPE). We have developed a pipeline that merges and evaluates base-specific and SHAPE data together with statistical analyses that provides confidence …
Instances Of Influenza In The United States Visualized, Parth Patel
Instances Of Influenza In The United States Visualized, Parth Patel
Publications and Research
The Tycho Project collects large data sets related to healthcare and in particular, instances and geographical information of diseases. We look at the instance counts and locations of Influenza from 1919-1951 across the United States. We hope to find seasonal and geographical insight to the spread of the disease.
Bubble Stream Production By Belugas (Delphinapterus Leucas), Megan Slack
Bubble Stream Production By Belugas (Delphinapterus Leucas), Megan Slack
Theses
Bubble stream production in belugas has been poorly characterized and its function is not well understood. I examined behavioral states when producing bubble streams (“bubbling”), and when bubbling calls, to determine whether bubbling was significantly associated with a particular call category or behavioral state. Using 19 hours of video and audio recordings collected over a two-day period, I quantified bubble streams of a 4-month old calf and an unrelated adult female housed together. Based on the overall activity budgets and pool of vocalizations for both animals, I calculated the expected counts of bubble streams with and without vocalizations, assuming that …
Penalized Mixed-Effects Ordinal Response Models For High-Dimensional Genomic Data In Twins And Families, Amanda E. Gentry
Penalized Mixed-Effects Ordinal Response Models For High-Dimensional Genomic Data In Twins And Families, Amanda E. Gentry
Theses and Dissertations
The Brisbane Longitudinal Twin Study (BLTS) was being conducted in Australia and was funded by the US National Institute on Drug Abuse (NIDA). Adolescent twins were sampled as a part of this study and surveyed about their substance use as part of the Pathways to Cannabis Use, Abuse and Dependence project. The methods developed in this dissertation were designed for the purpose of analyzing a subset of the Pathways data that includes demographics, cannabis use metrics, personality measures, and imputed genotypes (SNPs) for 493 complete twin pairs (986 subjects.) The primary goal was to determine what combination of SNPs and …
Visualizing Lab And Phenotype Associations Using Phewas And Electronic Health Records, Brenda Emerson, Miriam Goldman, Sahiti Kolli
Visualizing Lab And Phenotype Associations Using Phewas And Electronic Health Records, Brenda Emerson, Miriam Goldman, Sahiti Kolli
Honors Projects
As the digitization of patient health records is becoming more common, we are given a great opportunity to analyze these records and hopefully make discoveries about diseases or medicines. Being given large datasets of Electronic Health Records, I and two other students decided to look for novel phenotype associations with mean lab values, look to see whether the presence of a lab had associations with a phenotype, and create an interactive application to visual the associations between labs and phenotypes.
Burden Of Atopic Dermatitis In The United States: Analysis Of Healthcare Claims Data In The Commercial, Medicare, And Medi-Cal Databases, Sulena Shrestha, Raymond Miao, Li Wang, Jingdong Chao, Huseyin Yuce, Wenhui Wei
Burden Of Atopic Dermatitis In The United States: Analysis Of Healthcare Claims Data In The Commercial, Medicare, And Medi-Cal Databases, Sulena Shrestha, Raymond Miao, Li Wang, Jingdong Chao, Huseyin Yuce, Wenhui Wei
Publications and Research
Comparative data on the burden of atopic dermatitis (AD) in adults relative to the general population are limited. We performed a large-scale evaluation of the burden of disease among US adults with AD relative to matched non-AD controls, encompassing comorbidities, healthcare resource utilization (HCRU), and costs, using healthcare claims data. The impact of AD disease severity on these outcomes was also evaluated.
On The Three Dimensional Interaction Between Flexible Fibers And Fluid Flow, Bogdan Nita, Ryan Allaire
On The Three Dimensional Interaction Between Flexible Fibers And Fluid Flow, Bogdan Nita, Ryan Allaire
Department of Mathematics Faculty Scholarship and Creative Works
In this paper we discuss the deformation of a flexible fiber clamped to a spherical body and immersed in a flow of fluid moving with a speed ranging between 0 and 50 cm/s by means of three dimensional numerical simulation developed in COMSOL . The effects of flow speed and initial configuration angle of the fiber relative to the flow are analyzed. A rigorous analysis of the numerical procedure is performed and our code is benchmarked against well established cases. The flow velocity and pressure are used to compute drag forces upon the fiber. Of particular interest is the behavior …
Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang
Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang
COBRA Preprint Series
Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …