Categorical Data Analysis Commons^™

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 …

Joint Displays For Mixed Methods Research In Psychology, Matthew T. Mccrudden, Gwen Marchand, Paul A. Schutz

Research & Economic Development Faculty Research

Mixed methods researchers use joint displays for integration at different phases of the research process in psychological research. Joint displays are visual displays that are used to integrate quantitative and qualitative data during data collection, analysis, and interpretation. We discuss different mixing purposes and how joint displays may help researchers integrate the quantitative and qualitative strands of a study. We provide examples of joint displays for data collection and for data analysis, including newer innovations. Finally, we discuss considerations, including benefits and challenges, of using joint displays during data collection and analysis.

An Exploratory Assessment Of Callings: The Importance Of Specialization, Christopher Paul Cain, Lisa Nicole Cain, James A. Busser, Hee Jung Kang

Hospitality Faculty Research

Purpose This study sought to understand how having a calling influenced engagement, work–life balance and career satisfaction for Professional Golfers Association of America (PGA) and Golf Course Superintendent of America (GCSA) professionals. Design/methodology/approach A conceptual model was used to examine callings among golf course supervisors and its impact on their engagement, work–life balance and career satisfaction. This study also explored the moderation effect of employees’ generalized or specialized role on the calling–engagement relationship. Surveys were collected from a single golf management company and partial least squares structural equation modeling (PLS-SEM) was used for data analysis. Findings The results revealed significant …

Privacy-Preserving Cloud-Assisted Data Analytics, Wei Bao

Graduate Theses and Dissertations

Nowadays industries are collecting a massive and exponentially growing amount of data that can be utilized to extract useful insights for improving various aspects of our life. Data analytics (e.g., via the use of machine learning) has been extensively applied to make important decisions in various real world applications. However, it is challenging for resource-limited clients to analyze their data in an efficient way when its scale is large. Additionally, the data resources are increasingly distributed among different owners. Nonetheless, users' data may contain private information that needs to be protected.

Cloud computing has become more and more popular in …

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 …

Knowledge Discovery From Complex Event Time Data With Covariates, Samira Karimi

Graduate Theses and Dissertations

In particular engineering applications, such as reliability engineering, complex types of data are encountered which require novel methods of statistical analysis. Handling covariates properly while managing the missing values is a challenging task. These type of issues happen frequently in reliability data analysis. Specifically, accelerated life testing (ALT) data are usually conducted by exposing test units of a product to severer-than-normal conditions to expedite the failure process. The resulting lifetime and/or censoring data are often modeled by a probability distribution along with a life-stress relationship. However, if the probability distribution and life-stress relationship selected cannot adequately describe the underlying failure …

Grizzly Bears Mortalities And The Survival Of The Species, Courtney Swanson

Senior Seminars and Capstones

In this paper we aim to understand what is happening in the grizzly bear population mortalities from the year 2010 to 2020. We are performing Classical and Regression Tree (CART) methods and Correspondence Analysis on data provided by the U.S. Geological Survey (USGS). We found certain variables in the data set to be important through CART methods. Correspondence Analysis then allowed us to compare these variables to determine their relationships and association to one another. Most of the grizzly bear deaths are human caused and mainly over land and resources such as food and habitat. This aligns with some of …

Data Analysis And Visualization To Dismantle Gender Discrimination In The Field Of Technology, Quinn Bolewicki

Dissertations, Theses, and Capstone Projects

In the United States, a significant population is facing an uphill battle trying to thrive in an industry that has seen exponential growth in recent years. Women, who account for approximately 50.8% of the U.S. population are statistically underpaid and underrepresented in science, technology, engineering, and mathematics (STEM). Despite women-led technology teams establishing a 21% greater return on investment than teams who don’t, and young women largely outperforming men in math according to a 2015 study, there are only three fortune 500 companies led by women, and they comprise only 10% of internet entrepreneurs. Research generates hundreds of articles, infographics, …

Why Does An Ex-Offender Reoffend?, Jacob Rybak

Symposium of Student Scholars

What leads an offender to go back to prison? This researcher has lived in the Georgia State prison system for 3.5 years. Using personal insights as well as analytics, this researcher analyzes Iowa state’s six-year data set tracking recidivism of released offenders and recommends changes to the prison system to address the analytical findings.

The Iowa recidivism data set includes the following information for all offenders: age group, type of release (parole vs different discharges), release year, original offense, and whether they recidivated. For the recidivating offenders, the data set includes the days to return to prison, the type of …

Access To Higher Education: Do Schools “Grant” Success?, Nathaniel Jones

Symposium of Student Scholars

University education can lead to upward income mobility for low-income students. Being exposed to other student’s life experiences that are different from their own may highlight activities and actions that they may want to consider aiding their success. According to the U.S. Bureau of Labor Statistics, the median weekly earnings in 2019 for all workers in the U.S. was $969. Of those, U.S. workers who held bachelor’s degrees earned $1,248. In 2016, the Brookings Institute found that Pell Grant recipients and first-generation student loan borrowers attended universities that had lower graduation rates and higher loan default rates in comparison to …

Use Of Linear Discriminant Analysis In Song Classification: Modeling Based On Wilco Albums, Caroline Pollard

Honors Theses

The study of music recommender algorithms is a relatively new area of study. Although these algorithms serve a variety of functions, they primarily help advertise and suggest music to users on music streaming services. This thesis explores the use of linear discriminant analysis in music categorization for the purpose of serving as a cheaper and simpler content-based recommender algorithm. The use of linear discriminant analysis was tested by creating lineardiscriminant functions that classify Wilco’s songs into their respective albums, specifically A.M., Yankee Hotel Foxtrot, and Sky Blue Sky. 4 sample songs were chosen from each album, and song data was …

A Comparison Of The Localized Aviation Mos Program (Lamp) And Terminal Aerodrome Forecast (Taf) Accuracy For General Aviation, Douglas D. Boyd, Thomas A. Guinn

Journal of Aviation Technology and Engineering

Background. For general aviation (GA) pilots, operations in instrument meteorological conditions (IMC) carry an elevated risk of a fatal accident. As to whether a general aviation flight can be safely undertaken, aerodrome-specific forecasts (TAF, LAMP) provide guidance. Although LAMP forecasts are more common for GA-frequented aerodromes, nevertheless, the FAA recommends that for such aerodromes (and for which a TAF is not issued) the airman uses the TAF generated for the geographically closest airport for pre-flight weather evaluation. Herein, for non-TAF-issuing airports, the LAMP (sLAMP) predictive accuracy for visual (VFR) and instrument (IFR) flight rules flight category was determined.

Method. sLAMP …

How Risk-Related Statistics, As Reported In News And Social Media, Are Linked To The Use Of The Public Transit System, Prashiddhi Pokhrel

Thinking Matters Symposium

Due to the pandemic, people have started relying more on televisions, news, social media, and other news outlets for guidance. Moreover, with the increasing amount of news, data, and information there is also an increase in the amount of misleading statistics. People’s opinions and decisions significantly depend on the data, statistics, and information that they are exposed to, as well as their sources. For this project, we want to look at how information and its sources are affecting the decision made by the general public for the usage of the Portland Transit System. It is very important to know why …

Application Of Cycle-By-Cycle Analysis To Eeg Data From Individuals With Phelan-Mcdermid Syndrome, Naomi Miller

ENGS 88 Honors Thesis (AB Students)

This study aimed to analyze a novel method of processing data from electroencephalography (EEG) recordings, which implements time-domain cycle-by-cycle analysis. This "bycycle" method, developed by the Cole & Voytek laboratory, was implemented on a EEG dataset of children with and without Phelan-McDermid Syndrome in the hopes of uncovering network-level explanations for the genetic disorder. A supplemental Python pipeline was developed to organize and visualize the data. This led to the discovery of group-level differences in measures of cycle symmetry in alpha band waves over the sensorimotor electrodes. Through the same pipeline, the bycycle tool was validated as a sound EEG …

Node Classification On Relational Graphs Using Deep-Rgcns, Nagasai Chandra

Master's Theses

Knowledge Graphs are fascinating concepts in machine learning as they can hold usefully structured information in the form of entities and their relations. Despite the valuable applications of such graphs, most knowledge bases remain incomplete. This missing information harms downstream applications such as information retrieval and opens a window for research in statistical relational learning tasks such as node classification and link prediction. This work proposes a deep learning framework based on existing relational convolutional (R-GCN) layers to learn on highly multi-relational data characteristic of realistic knowledge graphs for node property classification tasks. We propose a deep and improved variant, …

Behavior Of Lightning In Developing Storms, Erick A. Tello

Theses and Dissertations

Air Force weather squadrons issue a warning when lightning activity is observed within 5 nautical miles (NM) of protected areas. Upon receiving this warning, personnel outdoors are expected to pause work and move inside. Studies sponsored by the 45th Weather Squadron (45 WS) have concluded that the 5 NM warning radius can be safely reduced for well-developed storms. This thesis investigates whether radii for storms in early development can also be reduced. Our research develops algorithms to partition lightning sensor data into storms. Next, storms are filtered to their earliest lightning events, and the study calculates distances between successive early …

Analyzing Student Experience On Group Work With The Application Of Different Group Allocation Approaches, An Yee Tan

Management and HR

Working as a group can be as challenging as working by oneself. Common issues like ineffective group work, unequal work contribution, and poor communication are believed to be the reasons why many students preferred to work individually. The purpose of this study is to understand if there is a disparity in student experience on group work by implementing different methods of group formation, which are, intentional group formation and random assignment. Topics around team well-being, team communication, and team effectiveness are the main focus of this study. The second emphasis of this study is students’ opinions on whether or not …

Carbon Dioxide And Particulate Matter Concentration On Hampton Roads Air Quality, Gregory Hubbard

OUR Journal: ODU Undergraduate Research Journal

Hampton Roads has been a maritime crossroads for the last 400 years. Industrialization has impacted the coastal region for the last 250 years. The expansion of the Port of Virginia in 2019 has created dense traffic in the region resulting in impacts to air quality. Two waste products that affect humans are particulate matter and carbon dioxide. Both respective emissions can cause adverse effects on humans, such as asthma, some lung cancers, and other respiratory distress. Scientists and health practitioners are studying the effects of particulate matter on human health. Hampton Roads, in particular, because of its unique location on …

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

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 …