Multivariate Analysis Commons^™

Predicting Hiv Vaccine-Mediated Protection Level To Identify Immune Correlates Using Positive Unlabeled Learning, Shiwei Xu

Dartmouth College Ph.D Dissertations

The development of a vaccine for Human Immunodeficiency Virus type 1 (HIV-1) is a crucial step in preventing the global spread of AIDS. To ensure the progress and effectiveness of this vaccine, it is essential to establish efficient biotechnology platforms and data mining methods. These methods would help identify immune characteristics that distinguish individuals with varying levels of vaccine-induced protection and determine the underlying factors that contribute to protection against HIV acquisition. While previous studies have focused on identifying immune markers associated with infection outcomes among vaccinated patients, it is important to acknowledge the limitations of traditional case-control analytical protocols …

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 …

Comparing Hierarchical Data Structures And Hierarchical Data Analysis, Halley Jeanne Dante, Robert Rovetti

Honors Thesis

Real world data is inherently noisy and data analysis can be especially complex when noise is compounded in hierarchical and multilevel data structures. Since such data structures can be described using multiple approaches, the way data is collapsed and grouped within these structures can influence its resulting interpretation and analyses. To avoid discrepancies in data collapsing and grouping, multiple statistical approaches have been developed specifically to analyze multilevel data structures. Examples of multilevel statistical models are the two-factor ANOVA and the general linear model with repeated-measures (GLM-RR) which is typically used in the context of looking at change over time. …

A Probabilistic Exploration Of Food Supplementation And Assistance, Logan Mattingly

Honors College Theses

Food insecurity is a stark threat that grips our country and affects households throughout our country. Dietary insufficiency manifests itself in ways that affect health and public safety. According to researchers, individuals who suffer from food insecurity have a higher risk of aggression, anxiety, suicide ideation and depression. These problems tend to occur unequally distributed among those households with lower income. In this work, an exploratory analysis within these data sets will be performed to examine the socio-economic, biographical, nutritional, and geographical principal components of food insecurity among survey participants and how the US Supplemental Nutrition Assistance Program (SNAP) effects …

The Last Drought Frontier: Building A Drought Index For The State Of Alaska, Olivia Campbell

School of Natural Resources: Dissertations, Theses, and Student Research

Drought is characterized by periods of below average precipitation. There are five major types of drought recognized in the literature: meteorological, hydrological, agricultural, socioeconomic, and ecological. A relatively new concept in the drought literature is “snow drought.” A key part of the definition of drought is that it is not always accompanied by extreme heat. This means drought can occur even in cold climates, cold seasons, and higher latitudes and altitudes, like Alaska. Drought is a natural part of climate variability, but Alaska’s climate is changing faster than any other state in the United States. Alaska is no stranger to …

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 …

Fraud Pattern Detection For Nft Markets, Andrew Leppla, Jorge Olmos, Jaideep Lamba

SMU Data Science Review

Non-Fungible Tokens (NFTs) enable ownership and transfer of digital assets using blockchain technology. As a relatively new financial asset class, NFTs lack robust oversight and regulations. These conditions create an environment that is susceptible to fraudulent activity and market manipulation schemes. This study examines the buyer-seller network transactional data from some of the most popular NFT marketplaces (e.g., AtomicHub, OpenSea) to identify and predict fraudulent activity. To accomplish this goal multiple features such as price, volume, and network metrics were extracted from NFT transactional data. These were fed into a Multiple-Scale Convolutional Neural Network that predicts suspected fraudulent activity based …

Application Of Gaussian Mixture Models To Simulated Additive Manufacturing, Jason Hasse, Semhar Michael, Anamika Prasad

SDSU Data Science Symposium

Additive manufacturing (AM) is the process of building components through an iterative process of adding material in specific designs. AM has a wide range of process parameters that influence the quality of the component. This work applies Gaussian mixture models to detect clusters of similar stress values within and across components manufactured with varying process parameters. Further, a mixture of regression models is considered to simultaneously find groups and also fit regression within each group. The results are compared with a previous naive approach.

Modeling And Fitting Two-Way Tables Containing Outliers, David L. Farnsworth

Articles

A model is proposed for two-way tables of measurement data containing outliers. The two independent variables are categorical and error free. Neither missing values nor replication are present. The model consists of the sum of a customary additive part that can be fit using least squares and a part that is composed of outliers. Recommendations are made for methods for identifying cells containing outliers and for fitting the model. A graph of the observations is used to determine the outliers’ locations. For all cells containing an outlier, replacement values are determined simultaneously using a classical missing-data tool. The result is …

Analyzing Relationships With Machine Learning, Oscar Ko

Dissertations, Theses, and Capstone Projects

Procedurally, this project aims to take a dataset, analyze it, and offer insights to the audience in an easy-to-digest format. Conceptually, this project will seek to explore questions like: “Do couples that meet through online dating or dating apps have higher or lower quality relationships?”, “Can any features in this dataset help predict how a subject would rate their relationship quality?”, and “What other insights can I derive from using machine learning for exploratory analysis?” The intended audience for this project is anyone interested in romantic relationships or machine learning.

The dataset is from a Stanford University survey, “How Couples …

Copula-Based Models For Bivariate And Multivariate Zero-Inflated Count Time Series Data, Dimuthu Fernando, Norou Diawara

College of Sciences Posters

Count time series data have multiple applications. The applications can be found in areas of finance, climate, public health and crime data analyses. In some scenarios, count time series come as multivariate vectors that exhibit not only serial dependence within each time series but also with cross correlation among the series. When considering these observed counts, analysis presents crucial challenges when a value, say zero, occurs more often than usual. There is presence of zero-inflation in the data.

In this presentation, we mainly focus on modeling bivariate zero-inflated count time series model based on a joint distribution of the two …

Enforcement Penalties At The Itc, Andrea R. Hugill, John C. Jarosz, Katherine D. Cappaert

Northwestern Journal of International Law & Business

The U.S. International Trade Commission (“ITC” or “Commission”) has grown in importance as a venue for U.S. companies to pursue intellectual property (“IP”) violators and to block the sale or importation of goods from overseas that infringe U.S. IP rights. Once a violation of the Section 337 of the Tariff Act of 1930 is found, an order halting further infringement, including importation, is almost always entered. In theory, potentially sizeable penalties may be imposed on entities that do not comply with the terms of an import restriction. In practice, the terms of an import restriction are almost always honored, but …

Modeling Growth And Stress Factors For Converted Silvopasture Systems In The Missouri Ozarks, Bailee N. Suedmeyer

Graduate Theses/Dissertations

Silvopasture systems are becoming increasingly popular among sustainable agriculture ranchers, due to the increase in knowledge of benefits to the cattle and ability to grow cool season grasses beneath the canopy. This project focuses on the forest crop aspect of silvopasture systems from monitoring of the health of the trees over time to recommendations for thinning management to keep it functioning as viable silvopasture. The study site consists of five acres of upland hardwood forest area in Southern Missouri with 18 monumented fixed area plots. Arial and ground data was collected at each plot throughout the growing season, along with …

The Vertical Evolution And Horizontal Correlation Of Information Science Education Research In China, Siyu Chen, Xiaofeng Zhu, Xumu Jiang

Journal of Scientific Information Research

[Purpose/significance]The comprehensive and accurate visualization of the information science education research in our country will help clarify the research context and inspire future research.[Method/process] Based on the relevant literature on "information education" in the CNKI database from 1980 to 2022, from the high-frequency keywords of the literature, the evolutionary context and development direction of our country's information science education research hotspots were longitudinally studied; from the three levels of system including our county's information science reseanch subject and research authar, our country's information science research research subject and research auther, horizontally explored and analyzed the mutual influence and mutual connection …

Disciplines Different Of Fine-Grained Acknowledged Entity：A Case Of Doctoral Dissertations In Chinese Humanities And Social Sciences, Jiaxin He, Shijin Zhang, Jiayu Zheng, Xinlong Chu, Chengzhi Zhang

Journal of Scientific Information Research

[Purpose/significance]Thesis acknowledgment is a public text in which the authors express their gratitude to individuals and institutions those support their research. It is helpful to understand the individuals and institutions that play a role in the cultivation of doctoral candidate in different disciplines by extracting the entities of acknowledgment and comparing the distribution of the objects of acknowledgment in the dissertations of different disciplines.[Method/process]In this paper, we gained more than 60 000 Chinese doctoral dissertations acknowledgment of 21 humanities and social sciences disciplines, extracted acknowledged entities from acknowledgment, and constructed a fine-grained classification system of acknowledgment entities. The classification system …

Comparison Of Policies Text On Information Technology Of China And The United States, Bolin Hua, Shihui Wu

Journal of Scientific Information Research

[Purpose/significance]Information technology plays an important role in the comprehensive national power, whose development is closely associated with the government's guidance and support. It's under this background that China and the United States launched a series of policies to promote the development of information technology. Discovering the differences between China and the US's policies is of great significance for us to improve our strategic planning for future development.[Method/process]This study presents China and the US's most important policies on information technology in chronological order, and mines the policies' text via the co-word networks and the LDA model.[Result/conclusion]Reveal common concerns and different focuses …

Clustering Hospital Performance Using Group-Based Multi-Trajectory Modeling With Singular Bayesian Information Criterion, Gaixin Du

Theses and Dissertations--Epidemiology and Biostatistics

Hospital performance is complex and patient-experience oriented. Currently, the Centers for Medicare and Medicaid Services (CMS) evaluate hospitals yearly with a single score of one to five ("Star Rating") using composite measures from five domains. However, a single composite score cannot fully describe it, and alternative measures should be considered. Healthcare quality improvement needs long-term data to validate effectiveness. Group-based multi-trajectory modeling (GBMTM) estimates probabilities of latent group membership based on longitudinal profiles from multiple outcomes. We use GBMTM to identify groups of hospitals with similar performance in SAS PROC TRAJ.

We downloaded Medicare-eligible hospitals (N=5,111) that provided patient care …

System For Scanning And Monitoring Science And Technology Policy Texts Of Us And Eu, Dahai Yu, Aofei Chang, Bolin Hua, Hongguang Wang, Wenjiao Zheng

Journal of Scientific Information Research

[Purpose/significance]Science and technology policy plays a guiding role in the development of science and technology. Whether science and technology policies are efficient and reasonable has an important impact on the rapid development of science and technology. In order to help decision-makers grasp the latest international scientific and technological layout, planning and policy guidance more quickly, especially to track and analyze the scientific, and technological policies of major developed countries in Europe and the United States, grab analyze and mine the corresponding scientific and technological policy texts in real time, has of great significance in the current international environment.[Method/process]This research designed …

The Impact Of Subjective Risk Analysis On Real Estate Prices In The Nisqually Region Following The 2001 Nisqually Earthquake, Ryan Espedal

All Master's Theses

Earthquakes are an environmental hazard that pose great risks to communities almost every day. With earthquakes, the main cause of concern is physical destruction of property, however, there are also psychological effects that are researched and discussed much less. In 2001, the Nisqually area of western Washington experienced a substantial earthquake that produced minimal physical damage but caused a significant decrease in real estate prices. Studying single-family homes from 1986-2012, this research utilizes hedonic property models to measure the change in consumer’s subjective risk calculations with reference to real estate purchases after the Nisqually earthquake, measure the relationship between earthquake …

Impacts Of Covid-19 On Industrial Growth In The United States, Emily G. Warthman, Charles J. Landis

Williams Honors College, Honors Research Projects

COVID-19 has caused massive ramifications on all parts of life in the world and industry growth/decline is not immune to it. This report will analyze nine different industries’ profit and revenue from quarterly data during the years 2009-2022. Forecast models will be generated using various methods and different techniques of validating to predict the values from Q2 2020- Q4 2022 based on historical data. After which, a comparison will be conducted between those predicted values to the actual average revenue and profit generated by order of greatest error percentage made. Thorough research will then be completed to determine if there …