Categorical Data Analysis Commons^™

Bayesian Peer Calibration With Application To Alcohol Use, Miles Q. Ott, Joseph W. Hogan, Krista J. Gile, Crystal Linkletter, Nancy P. Barnett

Statistical and Data Sciences: Faculty Publications

Peers are often able to provide important additional information to supplement self-reported behavioral measures. The study motivating this work collected data on alcohol in a social network formed by college students living in a freshman dormitory. By using two imperfect sources of information (self-reported and peer-reported alcohol consumption), rather than solely self-reports or peer-reports, we are able to gain insight into alcohol consumption on both the population and the individual level, as well as information on the discrepancy of individual peer-reports. We develop a novel Bayesian comparative calibration model for continuous, count and binary outcomes that uses covariate information to …

Wartime Construction Project Outcomes As A Function Of Contract Type, Ryan M. Hoff, Gregory D. Hammond, Peter P. Feng, Edward D. White

Faculty Publications

The United States has spent more than $23 billion on construction in Afghanistan since 2001. The dynamic security situation created substantial project uncertainty, and many construction projects used cost-plus-fixed-fee contracts (CPFF) instead of the firm-fixed-price (FFP) norm. Using a dataset of 25 wartime construction projects managed by the Air Force Civil Engineer Center, the authors sought to confirm that both contract types yield project outcomes consistent with the established literature. As expected, they found CPFF contracts had greater cost and schedule growth than FFP. However, they did not find differences regarding as-built quality. Additionally, the authors sought to determine whether …

Does Academic Performance Predict Workplace Productivity?, Jodie-Gaye Hunter

Honors Projects in Economics

This research examines if college GPA affects productivity and compensation in the workplace. It uses data collected from a survey of approximately 23,000 Bryant University graduates in different stages of their career. About 10 percent of the alumni surveyed completed the survey. The econometric model used in this study allows estimating the effect of GPA on income after controlling for various demographic and socioeconomic variables, including education, major, occupation, gender, among others. The empirical work provides evidence that GPA has a positive and statistically significant impact on workplace productivity for females, but GPA seems to be a weaker predictor of …

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 …

Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret

UW Biostatistics Working Paper Series

We have frequently implemented crossover studies to evaluate new therapeutic interventions for genital herpes simplex virus infection. The outcome measured to assess the efficacy of interventions on herpes disease severity is the viral shedding rate, defined as the frequency of detection of HSV on the genital skin and mucosa. We performed a simulation study to ascertain whether our standard model, which we have used previously, was appropriately considering all the necessary features of the shedding data to provide correct inference. We simulated shedding data under our standard, validated assumptions and assessed the ability of 5 different models to reproduce the …

Analysis Of The Precipitation Detection Algorithm For The Geonor T-200b Precipitation Gauge To Improve Accuracy, Megan Lerman, Robert K. Goodrich

STAR Program Research Presentations

In an effort to improve the precipitation detection algorithm for the Geonor All Weather Precipitation Gauge, an automated truth algorithm has been created to detect errors in the original algorithm. The original algorithm detects precipitation in real time and uses the rate of precipitation to indicate an event. The automated truth does not detect in real time, and focuses on precipitation accumulation to indicate an event. Since the automated truth is delayed, it is able to consider the data collected before and after the point it is analyzing. The automated truth is already more accurate than the original algorithm but …

Topics In Logistic Regression Analysis, Zhiheng Xie

Theses and Dissertations--Statistics

Discrete-time Markov chains have been used to analyze the transition of subjects from intact cognition to dementia with mild cognitive impairment and global impairment as intervening transient states, and death as competing risk. A multinomial logistic regression model is used to estimate the probability distribution in each row of the one-step transition matrix that correspond to the transient states. We investigate some goodness of fit tests for a multinomial distribution with covariates to assess the fit of this model to the data. We propose a modified chi-square test statistic and a score test statistic for the multinomial assumption in each …

Unequal Edge Inclusion Probabilities In Link-Tracing Network Sampling With Implications For Respondent-Driven Sampling, Miles Q. Ott, Krista J. Gile

Statistical and Data Sciences: Faculty Publications

Respondent-Driven Sampling (RDS) is a widely adopted linktracing sampling design used to draw valid statistical inference from samples of populations for which there is no available sampling frame. RDS estimators rely upon the assumption that each edge (representing a relationship between two individuals) in the underlying network has an equal probability of being sampled. We show that this assumption is violated in even the simplest cases, and that RDS estimators are sensitive to the violation of this assumption.

The Relationship Between Exercise And Depression And Anxiety In College Students, Joshua Frank, Dr. Amy Adkins, Nathan Thomas, Dr. Danielle Dick

Undergraduate Research Posters

The literature shows an inverse association between exercise and mental disorders. The aim of this study is to further elaborate on this association with regards to exercise and its relationship with anxiety and depression in a college sample. The subject group focused on seniors in the Spit for Science data set which incorporated a total of 821 students. Physical activity was assessed using the International Physical Activity Questionnaire (IPAQ) to estimate the overall metabolic equivalents (MET’s) each student spent in walking, moderate, or vigorous activity levels in the previous week. Sum scores were used to measure depression and anxiety. Overall,the …

Data Analytics On Consumer Behavior In Omni-Channel Retail Banking, Card And Payment Services, Geng Dan

Research Collection School Of Computing and Information Systems

Innovations in financial services have created challenges for banks that Information Systems (IS) research can address. My interests involve transaction cost theory, substitution and complementarity theory, and consumer informedness theory to understand consumer behavior and firm performance in the omni-channel world of digital banking. At a high level, my research inquiry asks: How can financial institutions take advantage of the deep insights that data analytics and management science modeling create on consumer behavior and channel management decision-making? And how can changes in payments and services in retail banking be understood in spatial and temporal terms? I am working on three …

Probabilistic Graphical Modeling On Big Data, Ming-Hua Chung

Graduate Theses and Dissertations

The rise of Big Data in recent years brings many challenges to modern statistical analysis and modeling. In toxicogenomics, the advancement of high-throughput screening technologies facilitates the generation of massive amount of biological data, a big data phenomena in biomedical science. Yet, researchers still heavily rely on key word search and/or literature review to navigate the databases and analyses are often done in rather small-scale. As a result, the rich information of a database has not been fully utilized, particularly for the information embedded in the interactive nature between data points that are largely ignored and buried. For the past …

A Localized Approach To The Origins Of Pottery In Upper Mesopotamia, Elizabeth Gibbon

Laurier Undergraduate Journal of the Arts

No abstract provided.

Telecom Data Analysis, Sai Roopak Sarva, Anudeep Masetty, Vinay Reddy Kondam

All Capstone Projects

The telecommunications industry regularly uses data analytics in fields such as customer analysis and network optimization. For financial analysis such as identifying risks, which could negatively impact an entity’s financial performance, communications service providers have traditionally used statistical sampling techniques that cover only short time periods and a limited subset of data.

Given the massive number of transactions processed by telecommunications companies; and the costs and complexity involved in their operations, data analytics offers a valuable opportunity for enhancing the frameworks and procedures they adopt to drive profitability and minimize unnecessary downside risk.

A Nonlinear Filter For Markov Chains And Its Effect On Diffusion Maps, Stefan Steinerberger

Yale Day of Data

Diffusion maps are a modern mathematical tool that helps to find structure in large data sets - we present a new filtering technique that is based on the assumption that errors in the data are intrinsically random to isolate and filter errors and thus boost the efficiency of diffusion maps. Applications include data sets from medicine (the Cleveland Heart Disease Data set and the Wisconsin Breast Cancer Data set) and engineering (the Ionosphere data set).

Model Selection For Gaussian Mixture Models For Uncertainty Qualification, Yiyi Chen, Guang Lin, Xuan Liu

The Summer Undergraduate Research Fellowship (SURF) Symposium

Clustering is task of assigning the objects into different groups so that the objects are more similar to each other than in other groups. Gaussian Mixture model with Expectation Maximization method is the one of the most general ways to do clustering on large data set. However, this method needs the number of Gaussian mode as input(a cluster) so it could approximate the original data set. Developing a method to automatically determine the number of single distribution model will help to apply this method to more larger context. In the original algorithm, there is a variable represent the weight of …

Mapping Open Water Bodeis With Optical Remote Sensing, Mary Ellen O'Donnell, Erika Podest

STAR Program Research Presentations

There is interest in mapping open water bodies using remote sensing data. Coverage and persistence of open water is currently a poorly measured variable due to its spatial and temporal variability across landscapes, especially in remote areas. The presence and persistence of open water is one of the primary indicators of conditions suitable for mosquito breeding habitats. Predicting the risk of mosquito caused disease outbreaks is a required step towards their control and eradication. Satellite observations can provide needed data to support agency decisions for deployment of preventative measures and control resources. This study, which will try to map open …

Data And Analytics In Corporate Real Estate: Do You Have The Right Talent?, Clarence Goh

Research Collection School Of Accountancy

Is the lack of suitable data and analytics talent in your corporate real estate (CRE) team preventing you from contributing to the wider business strategy?

Image Segmentation Using Fuzzy-Spatial Taxon Cut, Lauren Barghout

MODVIS Workshop

Images convey multiple meanings that depend on the context in which the viewer perceptually organizes the scene. This presents a problem for automated image segmentation, because it adds uncertainty to the process of selecting which objects to include or not include within a segment. I’ll discuss the implementation of a fuzzy-logic-natural-vision-processing engine that solves this problem by assuming the scene architecture prior to processing. The scene architecture, a standardized natural-scene-perception-taxonomy comprised of a hierarchy of nested spatial-taxons. Spatial-taxons are regions (pixel-sets) that are figure-like, in that they are perceived as having a contour, are either `thing-like', or a `group of …

Scientific Awareness At Ursinus College, Frank G. Devone

Mathematics Honors Papers

Ursinus College prides itself on creating well-rounded students, and recent initiatives, such as the Fellowships in the Ursinus Transition to the Undergraduate Research Experience Program and the Center for Science and the Common Good suggest that science is a vital part of the Ursinus liberal arts mission. A scientific awareness pilot survey was administered to a sample of Ursinus students drawn from the Class of 2014 and students residing at Ursinus during summer 2014. Experience and data collected from this pilot were used to create a final survey which was made available to all students at Ursinus College. The survey …

A Simulation-Based Task Analysis Using Agent-Based, Discrete Event And System Dynamics Simulation, Anastasia Angelopoulou

Electronic Theses and Dissertations

Recent advances in technology have increased the need for using simulation models to analyze tasks and obtain human performance data. A variety of task analysis approaches and tools have been proposed and developed over the years. Over 100 task analysis methods have been reported in the literature. However, most of the developed methods and tools allow for representation of the static aspects of the tasks performed by expert system-driven human operators, neglecting aspects of the work environment, i.e. physical layout, and dynamic aspects of the task. The use of simulation can help face the new challenges in the field of …

Ensemble Prediction And Data Assimilation For Operational Hydrology, Dong-Jun Seo, Yuqiong Liu, Hamid Moradkhani, Albrecht Weerts

Civil and Environmental Engineering Faculty Publications and Presentations

This special section in the Journal of Hydrology will discuss the need for advancing hydrologic ensemble prediction and DA.

Stratified Meta-Analysis To Examine Data Biases In Lung Cancer Studies Of Refinery Workers, Sherman Selix

Yale Day of Data

Petroleum refineries employ a variety of workers who historically experienced different potentials for asbestos exposure depending on job tasks. Associations between petroleum refinery work and lung cancer related to occupational asbestos exposure have been quantified among various locations, corporations, and time periods. To combine the data from several individual refinery studies and examine an overall effect, a systematic review and stratified meta-analysis was employed. Using set search terms among four databases, 112 potential publications were identified, of which 29 qualified for meta-analysis. Risk estimates and confidence intervals were extracted from these publications to construct four separate datasets. Inverse variance weighting …

Computational Methods For Historical Research On Wikipedia’S Archives, Jonathan Cohen

e-Research: A Journal of Undergraduate Work

This paper presents a novel study of geographic information implicit in the English Wikipedia archive. This project demonstrates a method to extract data from the archive with data mining, map the global distribution of Wikipedia editors through geocoding in GIS, and proceed with a spatial analysis of Wikipedia use in metropolitan cities.

The Structure Of Child And Adolescent Aggression: Confirmatory Factor Analysis Of A Brief Peer Conflict Scale, Justin Russell

LSU New Orleans Theses and Dissertations

The importance of simultaneous consideration of forms and functions in youth measures of aggressive behavior is well established. Competing models have presented these highly interrelated constructs as either independent (e.g., reactive or overt) or paired factors (e.g., reactive and overt). The current study examines these models in the context of assessing the viability of a new self-report measure, the Peer Conflict Scale – 20 Item Version. Confirmatory factor analyses were conducted on PCS 20 responses from 1,048 school-age youth living in the Gulf Coast region. Both models significantly improved upon one or two-factor alternatives, and demonstrated partial invariance across gender …

Using Remote Sensing Data To Predict The Spread Of Mosquito Borne Disease, Mary Ellen O'Donnell, Erika Podest

STAR Program Research Presentations

There is interest in how environmental variables derived from satellite data such as temperature, vegetation cover, and precipitation correlate to vector borne disease occurrence such as malaria and dengue fever. This study will be carried out using a decision tree based open source software called Random Forests to find correlations between the remote sensing variables and mosquito abundance. Software will be written in C# to take large amounts of data from the NASA satellite database and automatically format it for the Random Forest Software input. Correlations found, using Random Forests, between disease incidence and the variables can be used as …

An Eigenvector-Based Test For Local Stationarity Applied To Array Processing, Jorge Quijano, Lisa M. Zurk

Electrical and Computer Engineering Faculty Publications and Presentations

In sonar array processing, a challenging problem is the estimation of the data covariance matrix in the presence of moving targets in the water column, since the time interval of data local stationarity is limited. This work describes an eigenvector-based method for proper data segmentation into intervals that exhibit local stationarity, providing data-driven higher bounds for the number of snapshots available for computation of time-varying sample covariance matrices. Application of the test is illustrated with simulated data in a horizontal array for the detection of a quiet source in the presence of a loud interferer.

A Comparison Of Prenatal Alcohol, Tobacco, And Other Drug Use Between San Luis Obispo County And Ventura County, Dana M. Williamson

Statistics

Prenatal substance abuse is a growing issue in America. It can lead to fetal alcohol spectrum disorder, long term growth, behavior, and executive functioning problems, and creates a predisposition for drug use for the child.

This project summarizes the statistical analyses comparing alcohol, tobacco, and other drug use by pregnant women between San Luis Obispo County and Ventura County. The main goal of these analyses is to determine if there is a difference between San Luis Obispo County and Ventura County. This is an interesting comparison because these counties are neighboring counties, and past data have shown that the rate …

Identification Of Slums In Mumbai, India: Unsupervised Classification Techniques, Frankie St. Amand

Thinking Matters Symposium Archive

Slums are contiguous settlements. Inhabitants lack access to safe water, sanitation and sewage infrastructure, secure housing tenure, uncrowded living space, and permanent, durable housing. Addressing these problematic trends begins with identifying contiguous settlements within Mumbai’s urban fabric. Classifications can be performed using satellite images and remote sensing techniques to yield accurate results. Through literature reviews, socio-cultural analysis, and examination of high resolution satellite imagery, this project aims to develop a systematic, accessible, and reproducible method of classifying Mumbai’s slums.

Building Footprint Extraction: A Land Use Classification Comparison Of Satellite Imagery Vs. Orthoimagery, Elisa Trepanier

Thinking Matters Symposium Archive

The Town of Windham, Maine Proposed Municipal Budget FY 2012-2013 called for $12,750 for professional services to develop a building footprint database. There are several municipal applications for building footprints including, but not limited to: Taxation/valuation of properties; setbacks for code enforcement; public safety planning; historical analysis of building patterns; general planning, where to encourage growth and redevelopment; zoning analysis and recreational planning. Due to the town’s in-house GIS (Geographic Information Systems) capabilities, the project will be developed within the Assessor’s Office and based on the 2012 Maine Office of GIS 6 Orthoimagery for Windham. The following is an effort …

Identifying High Crime Areas Using Spatial Analysis, Elisa Trepanier

Thinking Matters Symposium Archive

Crime incident locations and trends are examined spatially using GIS to produce maps that pinpoint high crime areas or Hot Spots Crime mapping aids police departments by identifying areas to allocate limited resources where and when they are most needed. This project introduces the availability of GIS technology to smaller police departments as a tool to assist in the development of crime prevention strategies. In this model crime incident reports for Windham, Maine are geocoded and patterns of motor vehicle and structure burglaries analyzed for date, time and location of incident. An addressing protocol is followed to protect victim privacy …