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Utilizing New Technologies To Measure Therapy Effectiveness For Mental And Physical Health, Jonathan Ossie 2023 University of San Diego

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 …


A Novel Family Of Chain Binomial Models To Investigate Correlated Vaccination And Infection Rates In Sveirs Epidemic Dynamics, Divine Wanduku 2023 Virginia Commonwealth University

A Novel Family Of Chain Binomial Models To Investigate Correlated Vaccination And Infection Rates In Sveirs Epidemic Dynamics, Divine Wanduku

Biology and Medicine Through Mathematics Conference

No abstract provided.


Optimizing Tumor Xenograft Experiments Using Bayesian Linear And Nonlinear Mixed Modelling And Reinforcement Learning, Mary Lena Bleile 2023 Southern Methodist University

Optimizing Tumor Xenograft Experiments Using Bayesian Linear And Nonlinear Mixed Modelling And Reinforcement Learning, Mary Lena Bleile

Statistical Science Theses and Dissertations

Tumor xenograft experiments are a popular tool of cancer biology research. In a typical such experiment, one implants a set of animals with an aliquot of the human tumor of interest, applies various treatments of interest, and observes the subsequent response. Efficient analysis of the data from these experiments is therefore of utmost importance. This dissertation proposes three methods for optimizing cancer treatment and data analysis in the tumor xenograft context. The first of these is applicable to tumor xenograft experiments in general, and the second two seek to optimize the combination of radiotherapy with immunotherapy in the tumor xenograft …


Drug Ideologies Of The United States, Macy Montgomery 2023 Liberty University

Drug Ideologies Of The United States, Macy Montgomery

Helm's School of Government Conference

The United States has been increasingly creating lenient drug policies. Seventeen states and Washington, the District of Columbia, legalized marijuana, and Oregon decriminalized certain drugs, including methamphetamine, heroin, and cocaine. The medical community has proven that drugs, including marijuana, have myriad adverse health side effects. This leads to two questions: Why does the United States government continue to create lenient drug policies, and what reasons do citizens give for legalizing drugs when the medical community has proven them harmful? The paper hypothesizes that the disadvantages of drug legalization outweigh its benefits because of the numerous harms it causes, such as …


Inter-Rater Reliability Of Statistics Based On Reconstructed Individual Patient Data From Published Kaplan-Meier Curves, Megan E. Smith 2023 University of Nebraska Medical Center

Inter-Rater Reliability Of Statistics Based On Reconstructed Individual Patient Data From Published Kaplan-Meier Curves, Megan E. Smith

Theses & Dissertations

Introduction: Time-to-event outcomes include two elements: an indicator variable for whether the event has taken place, and the length of time from some origin point to the occurrence of the event of interest. Due to the complexity of these data, secondary analysis methods, such as indirect comparisons and meta-analysis, are easier to perform when individual-level patient data (IPD) is available.

Objectives: In 2021, an R package IPDfromKM was published, which contains an algorithm for reconstructing IPD from a Kaplan-Meier graph. The current research aimed to investigate the reproducibility of the IPDfromKM algorithm.

Methods: Three statisticians (MS, LS, …


On Cox Proportional Hazards Model Performance Under Different Sampling Schemes, Hani Samawi, Lili Yu, Jingjing Yin 2023 Georgia Southern University, Jiann-Ping Hsu College of Public Health

On Cox Proportional Hazards Model Performance Under Different Sampling Schemes, Hani Samawi, Lili Yu, Jingjing Yin

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

Cox’s proportional hazards model (PH) is an acceptable model for survival data analysis. This work investigates PH models’ performance under different efficient sampling schemes for analyzing time to event data (survival data). We will compare a modified Extreme, and Double Extreme Ranked Set Sampling (ERSS, and DERSS) schemes with a simple random sampling scheme. Observations are assumed to be selected based on an easy-to-evaluate baseline available variable associated with the survival time. Through intensive simulations, we show that these modified approaches (ERSS and DERSS) provide more powerful testing procedures and more efficient estimates of hazard ratio than those based on …


Employee Attrition: Analyzing Factors Influencing Job Satisfaction Of Ibm Data Scientists, Graham Nash 2023 Kennesaw State University

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 …


Statistical Analysis Of The Relationship Between Protected Bird Species And National Parks, Katherine Harmon 2023 Kennesaw State University

Statistical Analysis Of The Relationship Between Protected Bird Species And National Parks, Katherine Harmon

Symposium of Student Scholars

The ecological diversity of Earth is majorly threatened by habitat loss due to the destruction by human intervention. The conservation status of all identified species are classified into nine categories of varying vulnerability as described by the International Union for Conservation of Nature’s Red List. By understanding the vulnerability of specific species, scientists can work to maintain a viable and healthy ecosystem globally by instilling rules and regulations of observed habitats for threatened species. These habitats are identified by surveying potential locations for threatened species and determining the population size at each site. An example of one of these surveys …


Multiple Endpoints In Randomized Controlled Trials: A Review And An Illustration Of The Global Test, Lindsay Cameron 2023 Western University

Multiple Endpoints In Randomized Controlled Trials: A Review And An Illustration Of The Global Test, Lindsay Cameron

Electronic Thesis and Dissertation Repository

A randomized controlled trial is often used to provide high quality evidence regarding treatment interventions. Due to the complex nature of many diseases, trials usually select multiple primary outcomes to capture the efficacy of the interventions. In this thesis, we conducted a literature search to determine the prevalence of the different types of multiple outcomes that have been used in randomized controlled trials. We also reviewed the corresponding statistical methods used to deal with such outcomes. In addition, we described the benefits of using global tests as a statistical method when there are multiple primary outcomes in order to answer …


Prevalence Of Sars-Cov-2 Antibodies In Liberty University Student Population, Emily Bonus 2023 Liberty University

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 …


Forecasting Remission Time Of A Treatment Method For Leukemia As An Application To Statistical Inference Approach, Mahmoud Mansour, Rashad EL-Sagheer, Ahmed Galal Attia, Beha S. El-Desouky Prof. 2023 Al-Azhar University - Egypt

Forecasting Remission Time Of A Treatment Method For Leukemia As An Application To Statistical Inference Approach, Mahmoud Mansour, Rashad El-Sagheer, Ahmed Galal Attia, Beha S. El-Desouky Prof.

Basic Science Engineering

In this paper, Weibull-Linear Exponential distribution (WLED) has been investigated whether being it is a well-fit distribution to a clinical real data. These data represent the duration of remission achieved by a certain drug used in the treatment of leukemia for a group of patients. The statistical inference approach is used to estimate the parameters of the WLED through the set of the fitted data. The estimated parameters are utilized to evaluate the survival and hazard functions and hence assessing the treatment method through forecasting the duration of remission times of patients. A two-sample prediction approach has been applied to …


Statistical Methods For Gene Selection And Genetic Association Studies, Xuewei Cao 2023 Michigan Technological University

Statistical Methods For Gene Selection And Genetic Association Studies, Xuewei Cao

Dissertations, Master's Theses and Master's Reports

This dissertation includes five Chapters. A brief description of each chapter is organized as follows.

In Chapter One, we propose a signed bipartite genotype and phenotype network (GPN) by linking phenotypes and genotypes based on the statistical associations. It provides a new insight to investigate the genetic architecture among multiple correlated phenotypes and explore where phenotypes might be related at a higher level of cellular and organismal organization. We show that multiple phenotypes association studies by considering the proposed network are improved by incorporating the genetic information into the phenotype clustering.

In Chapter Two, we first illustrate the proposed GPN …


Striving For Appropriate Antibiotic Use: A Biomarker Initiative, And Outcomes Associated With Azithromycin Exposure, Amanda Gusovsky 2023 University of Kentucky

Striving For Appropriate Antibiotic Use: A Biomarker Initiative, And Outcomes Associated With Azithromycin Exposure, Amanda Gusovsky

Theses and Dissertations--Pharmacy

The introduction of antibiotics into clinical practice is considered the greatest medical breakthrough of the 20thcentury. However, the use of antibiotics can contribute to the development of resistance. In the United States (U.S.), approximately 2.8 million people are infected with antibiotic-resistant bacteria each year, and more than 35,000 people die as a result. Moreover, some antibiotics are known to cause cardiac side effects including QT prolongation, hypotension, and ventricular arrythmias. The U.S. Centers for Disease Control and Prevention (CDC) defines appropriate antibiotic use as the effort to use “the right antibiotic, at the right dose, for the right …


Utilizing Markov Chains To Estimate Allele Progression Through Generations, Ronit Gandhi 2023 University of Nebraska - Lincoln

Utilizing Markov Chains To Estimate Allele Progression Through Generations, Ronit Gandhi

Honors Theses, University of Nebraska-Lincoln

All populations display patterns in allele frequencies over time. Some alleles cease to exist, while some grow to become the norm. These frequencies can shift or stay constant based on the conditions the population lives in. If in Hardy-Weinberg equilibrium, the allele frequencies stay constant. Most populations, however, have bias from environmental factors, sexual preferences, other organisms, etc. We propose a stochastic Markov chain model to study allele progression across generations. In such a model, the allele frequencies in the next generation depend only on the frequencies in the current one.

We use this model to track a recessive allele …


Deep Learning-Based Technique For The Perception Of The Cervical Cancer, Aya Haraz, Hossam El-Din Moustafa, Abeer Twakol Khaleel, Ahmed H. Eltanboly 2023 Biomedical Engineering Program, Faculty of Engineering, Mansoura University, Egypt

Deep Learning-Based Technique For The Perception Of The Cervical Cancer, Aya Haraz, Hossam El-Din Moustafa, Abeer Twakol Khaleel, Ahmed H. Eltanboly

Mansoura Engineering Journal

In third-world countries, cervical cancer is the most prevalent and leading cause of death. It is affected by a variety of factors, including smoking, poor nutritional status, immunological inadequacy, and prolonged use of contraception. The Pap smear test, which is intended to prevent cervical cancer, finds preneoplastic changes in cervical epithelial cells. This study framework classified cervical cancer cells from Pap smears into five specified cell types using machine learning-based classification algorithms. The SIPaKMeD database is used in this investigation. This public dataset, which was manually cropped from 966 cluster cell images taken from Pap smear slides, has 4045 isolated …


Turnover, Covid-19, And Reasons For Leaving And Staying Within Governmental Public Health, Jonathan P. Leider, Gulzar H. Shah, Valerie A. Yeager, Jingjing Yin, Kusuma Madamala 2023 University of Minnesota - Twin Cities

Turnover, Covid-19, And Reasons For Leaving And Staying Within Governmental Public Health, Jonathan P. Leider, Gulzar H. Shah, Valerie A. Yeager, Jingjing Yin, Kusuma Madamala

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

Background and Objectives:

Public health workforce recruitment and retention continue to challenge public health agencies. This study aims to describe the trends in intention to leave and retire and analyze factors associated with intentions to leave and intentions to stay.

Design:

Using national-level data from the 2017 and 2021 Public Health Workforce Interests and Needs Surveys, bivariate analyses of intent to leave were conducted using a Rao-Scott adjusted chi-square and multivariate analysis using logistic regression models.

Results:

In 2021, 20% of employees planned to retire and 30% were considering leaving. In contrast, 23% of employees planned to retire and 28% …


Variability In Causal Effects On A Binary Outcome And Noncompliance In A Multisite Randomized Trial, Xinxin Sun 2023 Virginia Commonwealth University

Variability In Causal Effects On A Binary Outcome And Noncompliance In A Multisite Randomized Trial, Xinxin Sun

Theses and Dissertations

Noncompliance to treatment assignment is widespread in randomized trials and presents challenges in causal inference. In the presence of noncompliance, the most commonly estimated effect of treatment assignment, also known as intent-to-treat (ITT) effect, is biased. Of interest in this setting is the complier average causal effect (CACE), the ITT effect among compliers. Further complication arises when the outcome variable is partially observed.

My research focuses on estimating the distribution of a site-specific CACE in a multisite randomized controlled trial (MRCT) by maximum likelihood (ML). Assuming compliance missing at random (MAR). We express the likelihood as an integral with respect …


On Kernel-Based Estimator Of Odds Ratio Using Different Stratified Sampling Schemes, Abbas Eftekharian, Hani Samawi, Haresh Rochani 2022 University of Hormozgan

On Kernel-Based Estimator Of Odds Ratio Using Different Stratified Sampling Schemes, Abbas Eftekharian, Hani Samawi, Haresh Rochani

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

No abstract provided.


Regression Modeling Of Complex Survival Data Based On Pseudo-Observations, Rong Rong 2022 Southern Methodist University

Regression Modeling Of Complex Survival Data Based On Pseudo-Observations, Rong Rong

Statistical Science Theses and Dissertations

The restricted mean survival time (RMST) is a clinically meaningful summary measure in studies with survival outcomes. Statistical methods have been developed for regression analysis of RMST to investigate impacts of covariates on RMST, which is a useful alternative to the Cox regression analysis. However, existing methods for regression modeling of RMST are not applicable to left-truncated right-censored data that arise frequently in prevalent cohort studies, for which the sampling bias due to left truncation and informative censoring induced by the prevalent sampling scheme must be properly addressed. Meanwhile, statistical methods have been developed for regression modeling of the cumulative …


Bayesian Methods For Graphical Models With Neighborhood Selection., Sagnik Bhadury 2022 University of Louisville

Bayesian Methods For Graphical Models With Neighborhood Selection., Sagnik Bhadury

Electronic Theses and Dissertations

Graphical models determine associations between variables through the notion of conditional independence. Gaussian graphical models are a widely used class of such models, where the relationships are formalized by non-null entries of the precision matrix. However, in high-dimensional cases, covariance estimates are typically unstable. Moreover, it is natural to expect only a few significant associations to be present in many realistic applications. This necessitates the injection of sparsity techniques into the estimation method. Classical frequentist methods, like GLASSO, use penalization techniques for this purpose. Fully Bayesian methods, on the contrary, are slow because they require iteratively sampling over a quadratic …


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