Applied Statistics Commons^™

Use Of Tezepelumab For Chronic Rhinosinusitis With Nasal Polyps By Eosinophilic Endotype: Waypoint Post-Hoc Analysis, Shigeharu Fujieda, Nobuyoshi Otori, Joseph K. Han, Tadataka Yabuta, Claudia Chen, Claudio Marchese, Andrews Foster, Sandhia S. Ponnarambil, Yun Chan, Brian J. Lipworth

Department of Otolaryngology (ENT) Faculty Publications

Background

The phase 3 WAYPOINT study (NCT04851964) reported that tezepelumab improved outcomes in patients with chronic rhinosinusitis with nasal polyps (CRSwNP), including nasal polyp size, nasal congestion, and sinonasal symptoms, and reduced the need for surgery and systemic corticosteroids (SCS).

Objective

To evaluate the efficacy and safety of tezepelumab across Japanese Epidemiological Survey of Refractory Eosinophilic Chronic Rhinosinusitis-defined eosinophilic chronic rhinosinusitis (ECRS) subgroups.

Methods

Adults with severe CRSwNP were randomized to tezepelumab 210 mg or placebo every 4 weeks. Coprimary end points were the change from baseline to week 52 in total Nasal Polyp Score and the biweekly mean Nasal …

Changepoint Analyses Confirms Global Tropical Cyclone Frequency Decline, Michael Wehner, Thomas Fisher, Norou Diawara, Robert Lund

Mathematics & Statistics Faculty Publications

Changes in tropical cyclone frequencies as the climate warms is a topic of significant current debate [1, 2]. There is no accepted theory of how tropical cyclogenesis might respond to a warmer ocean-atmosphere system as multiple controlling factors exist [3–7]. Anthropogenic warming of surface ocean temperatures due to increased greenhouse gas concentrations [8] increases the potential for tropical cyclogenesis [9–11]; however, realized cyclogenesis also requires an initial local disturbance [12–16] to develop. Most multi-decadal tropical cyclone permitting climate models (i.e. resolutions of 15-50km) exhibit frequency decreases in warmer climates, despite the increase in tropical cyclogenesis potential [17–25]. In this paper, …

Variational Autoencoder Inverse Mapper For Extraction Of Compton Form Factors: Benchmarks And Conditional Learning, Douglas Adams, Md Fayaz Bin Hossen, Joshua Bautista, Gia-Wei Chern, Simonetta Liuti, Marie Boër, Marija Čuić, Michael Engelhardt, Gary R. Goldstein, Huey-Wen Lin, Yaohang Li

Computer Science Faculty Publications

Deeply virtual exclusive scattering processes (DVES) serve as precise probes of nucleon quark and gluon distributions in coordinate space. These distributions are derived from generalized parton distributions (GPDs) via Fourier transform relative to proton momentum transfer. QCD factorization theorems enable DVES to be parameterized by Compton form factors (CFFs), which are convolutions of GPDs with perturbatively calculable kernels. Accurate extraction of CFFs from DVCS, benefiting from interference with the Bethe–Heitler (BH) process and a simpler final state structure, is essential for inferring GPDs. This paper focuses on extracting CFFs from DVCS data using a variational autoencoder inverse mapper (VAIM) and …

Component Model Development Of Heat Exchangers, Expanders, And Control Valves For Autonomous Cryogenics Plant Cool-Down, William Harris Buhrig Iv

Mechanical & Aerospace Engineering Theses & Dissertations

The traditional method of cryogenic plant cool-down involves having continuous on-call staff to head into the office at any time to modify the existing multi-layered PID control systems if the on-call staff member detects a significant deviation from the cool-down plan. This thesis aims to outline an effective method for modeling the structure of systems with performance characteristics that deviate from design requirements and from ideal inlet-outlet correspondence, enabling the adjustment and modification of existing control structures across all Thomas Jefferson National Accelerator Facility (JLab) cryogenic refrigeration plants. Analytical Modeling and Gaussian Process Regression (GPR) are applied to model the …

A Modern Optimization Approach With Data-Driven Analytical Modeling For The Healthcare Business Segment (Hbs) From The S&P 500, Aditya Chakraborty, Chris Tsokos

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Introduction: The S&P consists of eleven business segments, which are classified according to the type of industry. The current study focuses on developing a non-linear analytical model for the Healthcare Business Segment (HBS) of the S&P 500, as a function of different economic & financial indicators. Materials and Methods: The analytical model used six financial indicators together with four economic indicators to predict the weekly average closing price (WCP) of HBS stocks. Johnson’s SB transformation corrected skewness, while desirability-based optimization identified indicator values maximizing WCP. The model’s performance and generalizability were validated through repeated 10-fold cross-validation. Results: All attributable contributors …

Group Antenatal Care Positively Transforms The Care Experience: Results Of An Effectiveness Trial In Malawi, Crystal L. Patil, Kathleen F. Noor, Esnath Kapito, Li C. Liu, Xiaohan Mei, Elizabeth Chodzaza, Genesis Chorwe-Sungani, Ursula Kafuulafula, Elizabeth T. Abrams, Allissa Desloge, Ashley Gresh, Rohan D. Jeremiah, Dhruvi R. Patel, Anne Batchelder, Heidy Wang, Jocelyn Faydenko, Sharon S. Rising, Ellen Chirwa

Department of Medicine Faculty Publications

Background

We developed and tested a Centering-based group antenatal (ANC) model in Malawi, integrating health promotion for HIV prevention and mental health. We present effectiveness data and examine congruence with only the Group ANC theory of change model, which identifies key processes as supportive relationships, empowered partners in learning and care, and meaningful services, leading to better ANC experiences and outcomes.

Methods

We conducted a hybrid effectiveness-implementation trial at seven clinics in Blantyre District, Malawi, comparing outcomes for 1887 pregnant women randomly assigned to Group ANC or Individual ANC. Group effects on outcomes were summarized and evaluated using t-tests, Mann-Whitney, …

Contributions To Nonparametric Testing In Clustered Data, Hasika Kalani Wickrama Senevirathne

Mathematics & Statistics Theses & Dissertations

Clustered data refers to a specific kind of correlated data where units within the same cluster are correlated while units from different clusters are independent. The number of units in each cluster, known as the cluster size, can be associated with the cluster’s outcome. This is known as the informative cluster size (ICS) and affects the inference drawn from clustered data. Recently, a hypothesis testing method has been developed to detect the presence of ICS. However, considering ICS alone may not be sufficient when comparing outcomes across multiple groups of units within clustered data. The size of a group within …

Numerical Investigation And Statistical Analysis Of The Flow Patterns Behind Square Cylinders Arranged In A Staggered Configuration Utilizing The Lattice Boltzmann Method, M. Abid, N. Yasin, M. Saqlain, S. Ul-Islam, S. Ahmad

Mathematics & Statistics Faculty Publications

Flow past bluff bodies like square cylinders is important in engineering applications, but flow patterns behind staggered cylinder arrangements remain poorly understood. Existing studies have focused on tandem or side-by-side configurations, while offset orientations have received less attention. The aim of this paper is to numerically investigate flow dynamics and force characteristics behind two offset square cylinders using the single relaxation time lattice Boltzmann method. The effects of changing both the Reynolds number (Re = 1-150) and gap spacing ratio (g* = 0.5-5) between the cylinders are analyzed. Instantaneous vorticity contours, time histories of drag and lift coefficients, power spectra …

Investigation Of The Effect Of Preparation Parameters On The Structural And Mechanical Properties Of Gelatin/Elastin/Sodium Hyaluronate Scaffolds Fabricated By The Combined Foaming And Freeze-Drying Techniques, Mansour Qamash, S. Misagh Imani, Meisam Omidi, Ciara Glancy, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

This paper aimed to evaluate the effects of different preparation parameters, including agitation speed, agitation time, and chilling temperature, on the structural and mechanical properties of a novel gelatin/elastin/sodium hyaluronate tissue engineering scaffold, recently developed by our research group. Fabricated using a combination of foaming and freeze-drying techniques, the scaffolds were assessed to understand how these parameters influence their morphology, internal microstructure, porosity, mechanical properties, and degradation behavior. The fabrication process used in this study involved preparing a homogeneous aqueous solution containing 8% gelatin, 2% elastin, and 0.5% sodium hyaluronate (w/v), which was then subjected to mechanical agitation at speeds …

A New Method To Determine The Posterior Distribution Of Coefficient Alpha, John Mart V. Delosreyes

Psychology Theses & Dissertations

There is a focus within the behavioral/social sciences on non-physical, psychological constructs (i.e., constructs). These constructs are indirectly measured using measurement instruments that consist of questions that capture the manifestations of these constructs. The indirect nature of measuring constructs results in a need of ensuring that measurement instruments are reliable. The most popular statistic used to estimate reliability is coefficient alpha as it is easy to compute and has properties that make it desirable to use. Coefficient alpha’s popularity has resulted in a wide breadth of research into its qualities. Notably, research about coefficient alpha’s distribution has led to developments …

Copula Based Models For Bivariate Zero-Inflated Count Time Series Data, Dimuthu Fernando

Mathematics & Statistics Theses & Dissertations

Count time series data have multiple applications. The applications can be found in areas of finance, climate, public health and crime data analyses. In most scenarios, time is an important part of the data. Time series counts then 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, and when a value, say zero, occurs more often than usual, analysis presents crucial challenges. There is presence of zeroinflation in the data. The literature on bivariate or multivariate count time series, as well as zero-inflated …

Inference For Multiple Utility In Time-Dependent Choice Pairs Under Copula-Based Models, Sasanka Adikari

Mathematics & Statistics Theses & Dissertations

Models for discrete choice experiments (DCE) are frequently used to analyze consumer choices about products and services. A family of DCE, best-worst scaling experiments, offers more in-depth insights into consumer preferences by eliciting a best and worst choice from a set of options, rather than just a single preference. Traditional approaches often assume that choices are mutually exclusive over time, which may not always be the case. This dissertation proposes a novel model for DCE that takes into account the changing nature of consumer choices over time and the priority constraint of transition probabilities. The model introduces a copula combination …

Poisson Regression Model With Application To Wastewater Surveillance Under A Threshold Linear Mixed Model For Covid-19 Sensitivity Rates, Norou Diawara, Hueiwang Anna Jeng, Kyle Curtis, Raul Gonzalez, Nancy Welch, Cynthia Jackson, Rekha Singh, David Jurgens, Sasanka Adikari, Omotomilola Jegede

Mathematics & Statistics Faculty Publications

A Threshold Linear Mixed Model (TLMM) has been developed to identify specific thresholds based on wastewater SARS-CoV-2 viral concentrations, which reflect COVID-19 cases. The thresholds can guide decisions regarding public health responses and prevention measures. To assess the practical application of TLMM, a simple simulation was conducted using a sample size of 100 and 500 replications. The simulation allowed for comparing parameter estimators by assessing bias and standard deviation and the root of the mean square error. The model and estimation procedures were applied to reported wastewater and clinic data to test its application for real-world scenarios. Our results demonstrated …

Cheiloscopy Patterns In Individuals With And Without Parafunctional Oral Habits: A Cross-Sectional Observation Pilot Study, Emily Regan, Brenda Bradshaw, Ann Bruhn, Walter Melvin, Sinjini Sikdar

Dental Hygiene Faculty Publications

Purpose

Lip prints are unique and have potential for use as a human identifier. The purpose of this study was to observe possible cheiloscopy differences of individuals with and without parafunctional oral habits such as smoking, vaping, playing a wind instrument or using an asthma inhaler.

Methods

This IRB approved blinded cross-sectional observation pilot study collected lip prints from 66 individuals, three of which were excluded. Participants cleansed their lips, then lipstick was applied to the vermillion zones of the upper and lower lips. Adhesive tape was applied to the lips and prints were transferred to white bond paper for …

Statistical Methods For Meta-Analysis In Large-Scale Genomic Experiments, Wimarsha Thathsarani Jayanetti

Mathematics & Statistics Theses & Dissertations

Recent developments in high throughput genomic assays have opened up the possibility of testing hundreds and thousands of genes simultaneously. With the availability of vast amounts of public databases, researchers tend to combine genomic analysis results from multiple studies in the form of a meta-analysis. Meta-analysis methods can be broadly classified into two main categories. The first approach is to combine the statistical significance (pvalues) of the genes from each individual study, and the second approach is to combine the statistical estimates (effect sizes) from the individual studies. In this dissertation, we will discuss how adherence to the standard null …

The Online Ordering Behaviors Among Participants In The Oklahoma Women, Infants, And Children Program: A Cross-Sectional Analysis, Qi Zhang, Kayoung Park, Junzhou Zhang, Chuanyi Tang

Community & Environmental Health Faculty Publications

The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) is a nutrition assistance program in the United States (U.S.). Participants in the program redeem their prescribed food benefits in WIC-authorized grocery stores. Online ordering is an innovative method being pilot-tested in some stores to facilitate WIC participants' food benefit redemption, which has become especially important in the COVID-19 pandemic. The present research aimed to examine the online ordering (OO) behaviors among 726 WIC households who adopted WIC OO in a grocery chain, XYZ (anonymous) store, in Oklahoma (OK). These households represented approximately 5% of WIC households who redeemed …

A Copula Model Approach To Identify The Differential Gene Expression, Prasansha Liyanaarachchi

Mathematics & Statistics Theses & Dissertations

Deoxyribonucleic acid, more commonly known as DNA, is a complex double helix-shaped molecule present in all living organisms and hosts thousands of genes. However, only a few genes exhibit differential expression and play a vital role in a particular disease such as breast cancer. Microarray technology is one of the modern technologies developed to study these gene expressions. There are two major microarray technologies available for expression analysis: Spotted cDNA array and oligonucleotide array. The focus of our research is the statistical analysis of data that arises from the spotted cDNA microarray. Numerous models have been proposed in the literature …

Empirical Modeling Of Tilt-Rotor Aerodynamic Performance, Michael C. Stratton

Mechanical & Aerospace Engineering Theses & Dissertations

There has been increasing interest into the performance of electric vertical takeoff and landing (eVTOL) aircraft. The propellers used for the eVTOL propulsion systems experience a broad range of aerodynamic conditions, not typically experienced by propellers in forward flight, that includes large incidence angles relative to the oncoming airflow. Formal experiment design and analysis techniques featuring response surface methods were applied to a subscale, tilt-rotor wind tunnel test for three, four, five, and six blade, 16-inch diameter, propeller configurations in support of development of the NASA LA-8 aircraft. Investigation of low-speed performance included a maximum speed of 12 m/s and …

D-Vine Copula Model For Dependent Binary Data, Huihui Lin, N. Rao Chaganty

College of Sciences Posters

High-dimensional dependent binary data are prevalent in a wide range of scientific disciplines. A popular method for analyzing such data is the Multivariate Probit (MP) model. But the MP model sometimes fails even within a feasible range of binary correlations, because the underlying correlation matrix of the latent variables may not be positive definite. In this research, we proposed pair copula models, assuming the dependence between the binary variables is first order autoregressive (AR(1))or equicorrelated structure. Also, when Archimediean copula is used, most paper converted Kendall Tau to corresponding copula parameter, there is no explicit function of Pearson’s correlation coefficient …

Rotorcraft Blade Angle Calibration Methods, Brian David Calvert Jr.

Mechanical & Aerospace Engineering Theses & Dissertations

The most vital system of a rotorcraft is the rotor system due to its effects on the overall flight quality of the vehicle. Therefore, it is of importance to be able to accurately determine blade position during flight so that fine adjustments can be made to ensure a safe and efficient flight. In this study, a current calibration method focusing on the pitch, flap, and lead-lag blade angles is analyzed and found to have larger than acceptable error associated with the sensor calibrations. A literature review is conducted which reveals four novel methods that can potentially increase the accuracy of …

Nonparametric False Discovery Rate Control For Identifying Simultaneous Signals, Sihai Dave Zhao, Yet Tian Nguyen

Mathematics & Statistics Faculty Publications

It is frequently of interest to identify simultaneous signals, defined as features that exhibit statistical significance across each of several independent experiments. For example, genes that are consistently differentially expressed across experiments in different animal species can reveal evolutionarily conserved biological mechanisms. However, in some problems the test statistics corresponding to these features can have complicated or unknown null distributions. This paper proposes a novel nonparametric false discovery rate control procedure that can identify simultaneous signals even without knowing these null distributions. The method is shown, theoretically and in simulations, to asymptotically control the false discovery rate. It was also …

Copula-Based Zero-Inflated Count Time Series Models, Mohammed Sulaiman Alqawba

Mathematics & Statistics Theses & Dissertations

Count time series data are observed in several applied disciplines such as in environmental science, biostatistics, economics, public health, and finance. In some cases, a specific count, say zero, may occur more often than usual. Additionally, serial dependence might be found among these counts if they are recorded over time. Overlooking the frequent occurrence of zeros and the serial dependence could lead to false inference. In this dissertation, we propose two classes of copula-based time series models for zero-inflated counts with the presence of covariates. Zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), and zero-inflated Conway-Maxwell-Poisson (ZICMP) distributed marginals of the …

Latent Choice Models To Account For Misclassification Errors In Discrete Transportation Data, Lacramioara Elena Balan

Civil & Environmental Engineering Theses & Dissertations

One of the most fundamental tasks when it comes to analyzing data using statistical methods is to understand the relationship between the explanatory variables and the outcome. Misclassification of explanatory variables is a common risk when using statistical modeling techniques. In this dissertation, we define ‘misclassification,’ as a response that is reported or recorded in the wrong category; for example, a variable is registered as a one when it should have the value zero. Misclassification can easily happen in any data; for example, in an interview setting where the respondent misunderstands the question or the interviewer checks the wrong box. …

Spatio-Temporal Cluster Detection And Local Moran Statistics Of Point Processes, Jennifer L. Matthews

Mathematics & Statistics Theses & Dissertations

Moran's index is a statistic that measures spatial dependence, quantifying the degree of dispersion or clustering of point processes and events in some location/area. Recognizing that a single Moran's index may not give a sufficient summary of the spatial autocorrelation measure, a local indicator of spatial association (LISA) has gained popularity. Accordingly, we propose extending LISAs to time after partitioning the area and computing a Moran-type statistic for each subarea. Patterns between the local neighbors are unveiled that would not otherwise be apparent. We consider the measures of Moran statistics while incorporating a time factor under simulated multilevel Palm distribution, …

Controlling For Confounding Via Propensity Score Methods Can Result In Biased Estimation Of The Conditional Auc: A Simulation Study, Hadiza I. Galadima, Donna K. Mcclish

Community & Environmental Health Faculty Publications

In the medical literature, there has been an increased interest in evaluating association between exposure and outcomes using nonrandomized observational studies. However, because assignments to exposure are not random in observational studies, comparisons of outcomes between exposed and nonexposed subjects must account for the effect of confounders. Propensity score methods have been widely used to control for confounding, when estimating exposure effect. Previous studies have shown that conditioning on the propensity score results in biased estimation of conditional odds ratio and hazard ratio. However, research is lacking on the performance of propensity score methods for covariate adjustment when estimating the …

Density Estimation Of Spatio-Temporal Point Patterns Using Moran’S Statistics, Jennifer L. Lorio, Norou Diawara, Lance A. Waller

Mathematics & Statistics Faculty Publications

Moran’s Index is a statistic that measures spatial autocorrelation, quantifying the degree of dispersion (or spread) of objects in space. When investigating data in an area, a single Moran statistic may not give a sufficient summary of the autocorrelation spread. However, by partitioning the area and taking the Moran statistic of each subarea, we discover patterns of the local neighbors not otherwise apparent. In this paper, we consider the model of the spread of an infectious disease, incorporate time factor, and simulate a multilevel Poisson process where the dependence among the levels is captured by the rate of increase of …

A Proposed Taxonomy For The Systems Statistical Engineering Body Of Knowledge, Teddy Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

In the ASEM-IAC 2012, Cotter (2012) identified the gaps in knowledge that statistical engineering needs to address, explored additional gaps in knowledge not addressed in the prior works, and set forth a working definition of and body of knowledge for statistical engineering. In the ASEM-IAC 2015, Cotter (2015) proposed a systemic causal Bayesian hierarchical model that addressed the knowledge gap needed to integrate deterministic mathematical engineering causal models within a stochastic framework. Missing, however, is the framework for specifying the hierarchical qualitative systems structures necessary and sufficient for specifying systemic causal Bayesian hierarchical models. In the ASEM-IAC 2016, Cotter (2016) …

The Use Of Item Response Theory In Survey Methodology: Application In Seat Belt Data, Mark K. Ledbetter, Norou Diawara, Bryan E. Porter

Mathematics & Statistics Faculty Publications

Problem: Several approaches to analyze survey data have been proposed in the literature. One method that is not popular in survey research methodology is the use of item response theory (IRT). Since accurate methods to make prediction behaviors are based upon observed data, the design model must overcome computation challenges, but also consideration towards calibration and proficiency estimation. The IRT model deems to be offered those latter options. We review that model and apply it to an observational survey data. We then compare the findings with the more popular weighted logistic regression. Method: Apply IRT model to the observed data …

Barriers To Counseling Among Human Service Professionals: The Development And Validation Of The Fit, Stigma, & Value Scale, Edward S. Neukrug, Michael T. Kalkbrenner, Sandy-Ann M. Griffith

Counseling & Human Services Faculty Publications

This study sought to confirm rates of attendance in counseling of human service professionals and validate a 32-item questionnaire designed to identify barriers to counseling seeking behavior among this population. Results indicated that a large percentage of human service professionals attend counseling, with males and females attending at similar rates and non-Caucasians attending at lower rates. A multivariate analysis of variance and descriptive statistics identified the most common barriers to attendance in counseling and examined demographic differences in participants’ sensitivity towards barriers to attendance in counseling. A Principal Factor Analysis (PFA) revealed three subscales (fit, value, and stigma), which we …

Exploring New Models For Seatbelt Use In Survey Data, Mark K. Ledbetter, Norou Diawara, Bryan E. Porter

Virginia Journal of Science

Problem: Several approaches to analyze seatbelt use have been proposed in the literature. Two methods that have not been explored are the use of unweighted and weighted logistic regression models and the use of item response theory (IRT) or the Rasch model. Since accurate methods to predict seatbelt use behavior based upon observed data must include a built-in design method and model and overcome computation challenges, weighted and IRT methods deem to be other options for an observational survey of seatbelt use in the state of Virginia.

Method: The data observed from 136 sites within the Commonwealth of …