Statistics and Probability Commons^™

Social Ecological Factors Affecting Substance Abuse In Ghana (West Africa) Using Photovoice, Ahmed Kabore, Evans Afriyie-Gyawu, James Awuah, Andrew R. Hansen, Ashley Walker, Melissa Hester, Moussa Aziz Wonadé Sié, Dhruv Medarametla, Nicolas Meda

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

Introduction: substance abuse is an important public health issue affecting West Africa; however, there is currently a dearth of literature on the actions needed to address it. The aim of this study was to assess the risks and protective factors of substance abuse in Ghana, West Africa, using the photovoice method.

Methods: this study recruited and trained 10 participants in recovery from substance abuse and undergoing treatment in the greater Accra region of Ghana on the photovoice methodology. Each participant received a disposable camera to take pictures that represented the risk and protective factors pertinent to substance abuse …

Generalized Matrix Decomposition Regression: Estimation And Inference For Two-Way Structured Data, Yue Wang, Ali Shojaie, Tim Randolph, Jing Ma

UW Biostatistics Working Paper Series

Analysis of two-way structured data, i.e., data with structures among both variables and samples, is becoming increasingly common in ecology, biology and neuro-science. Classical dimension-reduction tools, such as the singular value decomposition (SVD), may perform poorly for two-way structured data. The generalized matrix decomposition (GMD, Allen et al., 2014) extends the SVD to two-way structured data and thus constructs singular vectors that account for both structures. While the GMD is a useful dimension-reduction tool for exploratory analysis of two-way structured data, it is unsupervised and cannot be used to assess the association between such data and an outcome of interest. …

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 …

Statistical Inference For Networks Of High-Dimensional Point Processes, Xu Wang, Mladen Kolar, Ali Shojaie

UW Biostatistics Working Paper Series

Fueled in part by recent applications in neuroscience, high-dimensional Hawkes process have become a popular tool for modeling the network of interactions among multivariate point process data. While evaluating the uncertainty of the network estimates is critical in scientific applications, existing methodological and theoretical work have only focused on estimation. To bridge this gap, this paper proposes a high-dimensional statistical inference procedure with theoretical guarantees for multivariate Hawkes process. Key to this inference procedure is a new concentration inequality on the first- and second-order statistics for integrated stochastic processes, which summarizes the entire history of the process. We apply this …

Impact Of Motor Therapy With Dynamic Body-Weight Support On Functional Independence Measures In Traumatic Brain Injury: An Exploratory Study, Emily F. Anggelis, Elizabeth Salmon Powell, Philip M. Westgate, Amanda C. Glueck, Lumy Sawaki

Physical Medicine and Rehabilitation Faculty Publications

BACKGROUND: Contemporary goals of rehabilitation after traumatic brain injury (TBI) aim to improve cognitive and motor function by applying concepts of neuroplasticity. This can be challenging to carry out in TBI patients with motor, balance, and cognitive impairments.

OBJECTIVE: To determine whether use of dynamic body-weight support (DBWS) would allow safe administration of intensive motor therapy during inpatient rehabilitation and whether its use would yield greater improvement in functional recovery than standard-of-care (SOC) therapy in adults with TBI.

METHODS: Data in this retrospective cohort study was collected from patients with TBI who receive inpatient rehabilitation incorporating DBWS (n = …

Identifying Customer Churn In After-Market Operations Using Machine Learning Algorithms, Vitaly Briker, Richard Farrow, William Trevino, Brent Allen

SMU Data Science Review

This paper presents a comparative study on machine learning methods as they are applied to product associations, future purchase predictions, and predictions of customer churn in aftermarket operations. Association rules are used help to identify patterns across products and find correlations in customer purchase behaviour. Studying customer behaviour as it pertains to Recency, Frequency, and Monetary Value (RFM) helps inform customer segmentation and identifies customers with propensity to churn. Lastly, Flowserve’s customer purchase history enables the establishment of churn thresholds for each customer group and assists in constructing a model to predict future churners. The aim of this model is …

Personalized Detection Of Anxiety Provoking News Events Using Semantic Network Analysis, Jacquelyn Cheun Phd, Luay Dajani, Quentin B. Thomas

SMU Data Science Review

In the age of hyper-connectivity, 24/7 news cycles, and instant news alerts via social media, mental health researchers don't have a way to automatically detect news content which is associated with triggering anxiety or depression in mental health patients. Using the Associated Press news wire, a semantic network was built with 1,056 news articles containing over 500,000 connections across multiple topics to provide a personalized algorithm which detects problematic news content for a given reader. We make use of Semantic Network Analysis to surface the relationship between news article text and anxiety in readers who struggle with mental health disorders. …

Statistical Analysis Of Social Network Change, Teresa Danielle Schmidt

Dissertations and Theses

This project explores two statistical methods that infer social network structures and statistically test those structures for change over time: regression-based differential network analysis (R-DNA) and information theory-based differential analysis (I-DNA). R-DNA is adapted from bioinformatics and I-DNA employs reconstructability analysis.

This project applies both R-DNA and I-DNA to analyze Medicaid claims data from one-year periods before (May 2011- Apr 2012) and after (Jan 2013-Dec 2013) the formation of the Health Share of Oregon Coordinated Care Organization (CCO). The formation of CCOs was legislated by the state of Oregon in 2012 with the triple aim of improving health outcomes, reducing …

Achieving Optimal Horizontal Drill Operations, Daniel J. Serna, James Vasquez, Donald Markley

SMU Data Science Review

In this paper, we present a novel method of predicting the onset of a slide event in horizontal drilling operations. Horizontal drilling operations attempt to create a well through a subsurface as quickly as possible by rotating a drill through the subsurface. A slide event occurs when the drill begins to inefficiently rotate through the subsurface, resulting in a significantly reduced rate of penetration. Slide events can be prevented, or significantly reduced in their impact, when their onset is accurately predicted. We present a method of accurately predicting the onset of slide events with a time-series based predictive model that …

Ordinal Hyperplane Loss, Bob Vanderheyden

Doctor of Data Science and Analytics Dissertations

This research presents the development of a new framework for analyzing ordered class data, commonly called “ordinal class” data. The focus of the work is the development of classifiers (predictive models) that predict classes from available data. Ratings scales, medical classification scales, socio-economic scales, meaningful groupings of continuous data, facial emotional intensity and facial age estimation are examples of ordinal data for which data scientists may be asked to develop predictive classifiers. It is possible to treat ordinal classification like any other classification problem that has more than two classes. Specifying a model with this strategy does not fully utilize …

On Improving Performance Of The Binary Logistic Regression Classifier, Michael Chang

UNLV Theses, Dissertations, Professional Papers, and Capstones

Logistic Regression, being both a predictive and an explanatory method, is one of the most commonly used statistical and machine learning method in almost all disciplines. There are many situations, however, when the accuracies of the fitted model are low for predicting either the success event or the failure event. Several statistical and machine learning approaches exist in the literature to handle these situations. This thesis presents several new approaches to improve the performance of the fitted model, and the proposed methods have been applied to real datasets.

Transformations of predictors is a common approach in fitting multiple linear and …

Evaluating Parents Sociodemographic Factors And Childhood Vaccine Decisions, Mehret Girmay

UNLV Theses, Dissertations, Professional Papers, and Capstones

Vaccination is considered one of the most successful public health achievements of the 20th century. However, with increasing vaccine skepticism emerging over the past decades, there is a threat to the ongoing sustainment of vaccine coverage within all US communities. This study evaluated and compared parents’ sociodemographic factors associated with childhood vaccine decisions. This study is a secondary analysis of 893 parents/guardians, age 18-55 years with child(ren) < 7 years living in the U.S.

Predictive analysis was conducted using multinomial logistic regression modeling was used to examine vaccine decisions (accept, hesitant, and refuse) in relation to parents’ sociodemographic factors. Overall, (66.6%) of parents accepted recommended vaccines, while …

A Pedagogic Analysis Of Linear Algebra Courses, Andrew Taylor

Mathematics & Statistics ETDs

This project is concerned with investigating the question, "Do our applied linear algebra courses (at the University of New Mexico) adequately prepare STEM students for future work in their respective fields?" In order to explore this, surveys were issued to three groups (sections) of students (among two different instructors) at the conclusion of their applied linear algebra course, as well as STEM professors/instructors from a variety of STEM fields. Students were surveyed regarding their perceived mastery of given topics/ideas from the course and professors/instructors were surveyed about the level of mastery they felt was necessary (referred to as ``desired mastery") …

Efficient Smooth Non-Convex Stochastic Compositional Optimization Via Stochastic Recursive Gradient Descent, Wenqing Hu, Chris Junchi Li, Xiangru Lian, Ji Liu, Huizhuo Yuan

Mathematics and Statistics Faculty Research & Creative Works

Stochastic compositional optimization arises in many important machine learning applications. The objective function is the composition of two expectations of stochastic functions, and is more challenging to optimize than vanilla stochastic optimization problems. In this paper, we investigate the stochastic compositional optimization in the general smooth non-convex setting. We employ a recently developed idea of Stochastic Recursive Gradient Descent to design a novel algorithm named SARAH-Compositional, and prove a sharp Incremental First-order Oracle (IFO) complexity upper bound for stochastic compositional optimization: 𝒪((n + m)^1/2ε^-2) in the finite-sum case and 𝒪(ε^-3) in the online case. …

Implications Of The Modifiable Areal Unit Problem For Wildfire Analyses, Timothy P. Nagle-Mcnaughton, Xi Gong, Jose A. Constantine

Geography and Environmental Studies Faculty Publications

Wildfires pose a danger to both ecologies and communities. To this end, many large-scale analyses of wildfire patterns and behavior rely on the aggregation of point data to polygons, typically those based on distinct disparate ecological areas. However, the sizes, shapes, andorientations of the polygons to which data are aggregated are not neutral factors in the resulting analysis. The influence of the aggregation polygons on calculated results is known as the modifiable areal unit problem (MAUP), which is well-documented in the spatial statistics literature. Despite the documentation of the MAUP, relatively few wildfire studies consider the effects of the MAUP …

Determinism Of Stochastic Processes Through The Relationship Between The Heat Equation And Random Walks, Gurmehar Singh Makker

Publications and Research

We study the deterministic characteristics of stochastic processes through investigation of random walks and the heat equation. The relationship is confirmed by discretizing the heat equation in time and space and determining the probability distribution function for random walks in dimension d = 1, 2. The existence of the relationship is presented both through theoretical analysis and numerical computation.

Chronic Muscle Weakness And Mitochondrial Dysfunction In The Absence Of Sustained Atrophy In A Preclinical Sepsis Model, Allison M. Owen, Samir P. Patel, Jeffrey D. Smith, Beverly K. Balasuriya, Stephanie F. Mori, Gregory S. Hawk, Arnold J. Stromberg, Naohide Kuriyama, Masao Kaneki, Alexander G. Rabchevsky, Timothy A. Butterfield, Karyn A. Esser, Charlotte A. Peterson, Marlene E. Starr, Hiroshi Saito

Physiology Faculty Publications

Chronic critical illness is a global clinical issue affecting millions of sepsis survivors annually. Survivors report chronic skeletal muscle weakness and development of new functional limitations that persist for years. To delineate mechanisms of sepsis-induced chronic weakness, we first surpassed a critical barrier by establishing a murine model of sepsis with ICU-like interventions that allows for the study of survivors. We show that sepsis survivors have profound weakness for at least 1 month, even after recovery of muscle mass. Abnormal mitochondrial ultrastructure, impaired respiration and electron transport chain activities, and persistent protein oxidative damage were evident in the muscle of …

The Negotiator's Role In A Buyer-Seller Game, Joseph Gaudy

Graduate Theses and Capstone Projects (excluding DNP)

In game theory, buyer-seller games rarely utilize a negotiating third party. Any negotiations are typically conducted by the buyer and seller. This study, motivated by the real estate market, uses sequentially and simultaneously played game models to explore the influence a self-interested, negotiating, third party has on player payoffs. For the sequential model, a game tree is utilized to demonstrate player actions, preferences, and outcomes. The weak sequential equilibrium is calculated using Gambit[1] and shows optimality in player payoffs to exist when the seller’s and realtor’s strategies align according to the current market. For the simultaneous model, expected payoff functions …

A Simulation Study On The Size And Power Properties Of Some Ridge Regression Tests, B. M. Golam Kibria, Shipra Banik

Applications and Applied Mathematics: An International Journal (AAM)

Ridge regression techniques have been extensively used to solve the multicollinearity problem for both linear and non-linear regression models since its inception. This paper studied different ridge regression t-type tests of the individual coefficients of a linear regression model. A simulation study has been conducted to evaluate the performance of the proposed tests with respect to their sizes and powers under different settings of the linear regression model. Our simulation results demonstrated that most of the proposed tests have sizes close to the 5% nominal level and all tests except tAKS, tkM2 and tkM9 have considerable gain in powers over …

Alpha-Skew Generalized Normal Distribution And Its Applications, Eisa Mahmoudi, Hamideh Jafari, Rahmat S. Meshkat

Applications and Applied Mathematics: An International Journal (AAM)

The main object of this paper is to introduce a new family of distributions, which is quite flexible to fit both unimodal and bimodal shapes. This new family is entitled alpha-skew generalized normal (ASGN), that skews the symmetric distributions, especially generalized normal distribution through this paper. Here, some properties of this new distribution including cumulative distribution function, survival function, hazard rate function and moments are derived. To estimate the model parameters, the maximum likelihood estimators and the asymptotic distribution of the estimators are discussed. The observed information matrix is derived. Finally, the flexibility of the new distribution, as well as …

Evaluation Of Modern Missing Data Handling Methods For Coefficient Alpha, Katerina Matysova

College of Education and Human Sciences: Dissertations, Theses, and Student Research

When assessing a certain characteristic or trait using a multiple item measure, quality of that measure can be assessed by examining the reliability. To avoid multiple time points, reliability can be represented by internal consistency, which is most commonly calculated using Cronbach’s coefficient alpha. Almost every time human participants are involved in research, there is missing data involved. Missing data means that even though complete data were expected to be collected, some data are missing. Missing data can follow different patterns as well as be the result of different mechanisms. One traditional way to deal with missing data is listwise …

A Comparison Of Academic Performance Measures Of Hsta Participants With Non-Hsta Participants: Is It Possible To Narrow The African American-White Achievement Gap?, Sherron Mckendall, Alan Mckendall, Ann Chester

Faculty & Staff Scholarship

Historically, African American and other underserved students encounter academic challenges in pursuit of a college degree—one of which is their performance on standardized tests. This paper analyzes College Grade Point Averages (CGPAs), ACT Composite (ACTC), and SAT Total (SATT) scores of students who participated in the Health Sciences and Technology Academy (HSTA), an out-of-school-time (OST) program, and Non-HSTA (NHSTA) students attending West Virginia University. Traditionally, OST programs provide academic enrichment to underserved youth to increase their chances for post-secondary entry and success. Two-Way Factorial ANOVA determined if HSTA participants performed better on academic measures than their NHSTA counterparts. The ANOVAs …

An (S - 1; S) Inventory System With Negative Arrivals And Multiple Vacations, Kathiresan Jothivel, Anbazhagan Neelamegam

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we consider a continuous review one-to-one ordering policy inventory system with multiple vacations and negative customers. The maximum storage capacity is S. The customers arrive according to a Poisson process with finite waiting hall. There are two types of customers: ordinary and negative. An ordinary customer, on arrival, joins the queue and the negative customer does not join the queue and takes away any one of the waiting customers. When the waiting hall is full, the arriving primary customer is considered to be lost. The service time and lead time are assumed to have independent exponential distribution. …

A Further Result On The Aging Properties Of An Extended Additive Hazard Model, Morteza Raeisi, Gholamhossein Yari

Applications and Applied Mathematics: An International Journal (AAM)

The passing of time is an important factor for covariates in the additive and proportional hazard models. According to this idea, the extended additive hazard model (EAHM) is introduced by considering the time-varying effects of covariates and is investigated several properties of this model related to reliability analysis. In this paper, we obtain a further result for the EAHM with respect to the aging properties.

Series Of Divergence Measures Of Type K, Information Inequalities And Particular Cases, R. N. Saraswat, Ajay Tak

Applications and Applied Mathematics: An International Journal (AAM)

Information and Divergence measures deals with the study of problems concerning information processing, information storage, information retrieval and decision making. The purpose of this paper is to find a new series of divergence measures and their applications, discuss the mathematical tools for finding convexity of the functions. Applications of convex functions in information theory, relationship between new and well-known divergence measures are discussed. Also some new bounds have been established for divergence measures using new f divergence measures and its properties.

Analysis Of Batch Arrival Single And Bulk Service Queue With Multiple Vacation Closedown And Repair, T. Deepa, A. Azhagappan

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we analyze batch arrival single and bulk service queueing model with multiple vacation, closedown and repair. The single server provides single service if the queue size is ‘< a’ and bulk service if the queue size is ‘ ≥ a’. After completing the service (single or bulk), the server may breakdown with probability ξ and then it will be sent for repair. When the system becomes empty or the server is ready to serve after the repair but no one is waiting, the server resumes closedown and then goes for a multiple vacation of random length. Using supplementary variable technique, the steady-state probability generating function (PGF) of …

Analysis Of Two Stage M[X1],M[X2]/G1,G2/1 Retrial G-Queue With Discretionary Priority Services, Working Breakdown, Bernoulli Vacation, Preferred And Impatient Units, G. Ayyappan, B. Somasundaram

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we study M^[X₁] , M^[X2] /G₁ ,G₂ /1 retrial queueing system with discretionary priority services. There are two stages of service for the ordinary units. During the first stage of service of the ordinary unit, arriving priority units can have an option to interrupt the service, but, in the second stage of service it cannot interrupt. When ordinary units enter the system, they may get the service even if the server is busy with the first stage of service of an ordinary unit or may enter into the orbit or leave …

Evaluation Of Relationship Between Lead-Dust Loading, Lead-Dust Concentration, And Total Dust Loading Metrics Across Multiple Data Sets, Charles Bevington

Capstone Experience

Lead-dust monitoring studies report values as either lead-dust loadings µg/ft² or as lead-dust concentrations µg/g. It is rare for studies to report both metrics. When only lead-dust loading values are present, professionals require an approach to estimate lead-dust concentration values. A literature search identified five studies that contained raw data for both lead-dust loading and lead-dust concentration. An additional thirty-two studies had summary-statistics available for both lead-dust loading and lead-dust concentration. Studies with raw-data were used to develop an empirically-based loading to concentration statistical relationship. Raw data sets were critically evaluated to determine whether elimination or …

Production Of Physician Services Under Fee-For-Service And Blended Fee-For-Service: Evidence From Ontario, Canada., Nibene H Somé, Rose Anne Devlin, Nirav Mehta, Greg Zaric, Lihua Li, Salimah Shariff, Bachir Belhadji, Amardeep Thind, Amit Garg, Sisira Sarma

Epidemiology and Biostatistics Publications

We examine family physicians' responses to financial incentives for medical services in Ontario, Canada. We use administrative data covering 2003-2008, a period during which family physicians could choose between the traditional fee for service (FFS) and blended FFS known as the Family Health Group (FHG) model. Under FHG, FFS physicians are incentivized to provide comprehensive care and after-hours services. A two-stage estimation strategy teases out the impact of switching from FFS to FHG on service production. We account for the selection into FHG using a propensity score matching model, and then we use panel-data regression models to account for observed …

Statistical Methods For Estimating And Testing Treatment Effect For Multiple Treatment Groups In Observational Studies., Xiaofang Yan

Electronic Theses and Dissertations

Note: Abstract would not save due to an issue with some of the characters.