Statistics and Probability Commons^™

A New Two Parametric Weighted Generalized Entropy For Lifetime Distributions, Bilal Ahmad Bhat, Mirza Abdul Khaliq Baig

Journal of Modern Applied Statistical Methods

The concept of weighted generalized entropy and its dynamic residual (version) is developed. The general expressions of these two uncertainty measures corresponding to some well-known lifetime distributions are derived. It is shown that the proposed dynamic entropy determines the survival function uniquely. Some significant properties and inequalities of this dynamic entropy are also discussed.

Risk Of New Bloodstream Infections And Mortality Among People Who Inject Drugs With Infective Endocarditis., Charlie Tan, Esfandiar Shojaei, Joshua C. Wiener, Meera Shah, Sharon Koivu, Michael Silverman

Epidemiology and Biostatistics Publications

IMPORTANCE: People who inject drugs (PWID) who are being treated for infective endocarditis remain at risk of new bloodstream infections (BSIs) due to ongoing intravenous drug use (IVDU).

OBJECTIVES: To characterize new BSIs in PWID receiving treatment for infective endocarditis, to determine the clinical factors associated with their development, and to determine whether new BSIs and treatment setting are associated with mortality.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study was performed at 3 tertiary care hospitals in London, Ontario, Canada, from April 1, 2007, to March 31, 2018. Participants included a consecutive sample of all PWID 18 years or …

Energy Stable Numerical Schemes For Ternary Cahn-Hilliard System, Wenbin Chen, Cheng Wang, Shufen Wang, Xiaoming Wang, Steven M. Wise

Mathematics and Statistics Faculty Research & Creative Works

We present and analyze a uniquely solvable and unconditionally energy stable numerical scheme for the ternary Cahn-Hilliard system, with a polynomial pattern nonlinear free energy expansion. One key difficulty is associated with presence of the three mass components, though a total mass constraint reduces this to two components. Another numerical challenge is to ensure the energy stability for the nonlinear energy functional in the mixed product form, which turns out to be non-convex, non-concave in the three-phase space. to overcome this subtle difficulty, we add a few auxiliary terms to make the combined energy functional convex in the three-phase space, …

Machine Learning Approaches For Improving Prediction Performance Of Structure-Activity Relationship Models, Gabriel Idakwo

Dissertations

In silico bioactivity prediction studies are designed to complement in vivo and in vitro efforts to assess the activity and properties of small molecules. In silico methods such as Quantitative Structure-Activity/Property Relationship (QSAR) are used to correlate the structure of a molecule to its biological property in drug design and toxicological studies. In this body of work, I started with two in-depth reviews into the application of machine learning based approaches and feature reduction methods to QSAR, and then investigated solutions to three common challenges faced in machine learning based QSAR studies.

First, to improve the prediction accuracy of learning …

The Impact Of Improved Access To After-Hours Primary Care On Emergency Department And Primary Care Utilization: A Systematic Review., Michael Hong, Amardeep Thind, Gregory S Zaric, Sisira Sarma

Epidemiology and Biostatistics Publications

Access to after-hours primary care is problematic in many developed countries, leading patients to instead visit the emergency department for non-urgent conditions. However, emergency department utilization for conditions treatable in primary care settings may contribute to emergency department overcrowding and increased health system costs. This systematic review examines the impact of various initiatives by developed countries to improve access to after-hours primary care on emergency department and primary care utilization. We performed a systematic review on the impact of improved access to after-hours primary and searched CINAHL, EMBASE, MEDLINE, and Scopus. We identified 20 studies that examined the impact of …

Heart Failure In Humans Reduces Contractile Force In Myocardium From Both Ventricles, Cheavar A. Blair, Elizabeth A Brundage, Katherine L. Thompson, Arnold J. Stromberg, Maya Guglin, Brandon J Biesiadecki, Kenneth S. Campbell

Statistics Faculty Publications

This study measured how heart failure affects the contractile properties of the human myocardium from the left and right ventricles. The data showed that maximum force and maximum power were reduced by approximately 30% in multicellular preparations from both ventricles, possibly because of ventricular remodeling (e.g., cellular disarray and/or excess fibrosis). Heart failure increased the calcium (Ca²⁺) sensitivity of contraction in both ventricles, but the effect was bigger in right ventricular samples. The changes in Ca²⁺ sensitivity were associated with ventricle-specific changes in the phosphorylation of troponin I, which indicated that adrenergic stimulation might induce different effects …

A Novel Correction For The Adjusted Box-Pierce Test — New Risk Factors For Emergency Department Return Visits Within 72 Hours For Children With Respiratory Conditions — General Pediatric Model For Understanding And Predicting Prolonged Length Of Stay, Sidy Danioko

Computational and Data Sciences (PhD) Dissertations

This thesis represents the results of three research projects that underline the breadth and depth of my interests.

Firstly, I devoted some efforts to the well-known Box-Pierce goodness-of-fit tests for time series models which has been an important research topic over the last few decades. All previously proposed tests are focused on changes of the test statistics. Instead, I adopted a different approach that takes the best performing test and modifying the rejection region. Thus, I developed a semiparametric correction of the Adjusted Box-Pierce test that attains the best I error rates for all sample sizes and lags and outperforms …

Nanoceria Distribution And Effects Are Mouse-Strain Dependent, Robert A. Yokel, Michael T. Tseng, D. Allan Butterfield, Matthew L. Hancock, Eric A. Grulke, Jason M. Unrine, Arnold J. Stromberg, Alan K. Dozier, Uschi M. Graham

Pharmaceutical Sciences Faculty Publications

Prior studies showed nanoparticle clearance was different in C57BL/6 versus BALB/c mice, strains prone to Th1 and Th2 immune responses, respectively. Objective: Assess nanoceria (cerium oxide, CeO₂ nanoparticle) uptake time course and organ distribution, cellular and oxidative stress, and bioprocessing as a function of mouse strain. Methods: C57BL/6 and BALB/c female mice were i.p. injected with 10 mg/kg nanoceria or vehicle and terminated 0.5 to 24 h later. Organs were collected for cerium analysis; light and electron microscopy with elemental mapping; and protein carbonyl, IL-1β, and caspase-1 determination. Results: Peripheral organ cerium significantly increased, generally more …

Marginal Methods And Software For Clustered Data With Cluster- And Group-Size Informativeness., Mary Elizabeth Gregg

Electronic Theses and Dissertations

Clustered data result when observations have some natural organizational association. In such data, cluster size is defined as the number of observations belonging to a cluster. A phenomenon termed informative cluster size (ICS) occurs when observation outcomes vary in a systematic way related to the cluster size. An additional form of informativeness, termed informative within-cluster group size (IWCGS), arises when the distribution of group-defining categorical covariates within clusters similarly carries information related to outcomes. Standard methods for the marginal analysis of clustered data can produce biased estimates and inference when data have informativeness. A reweighting methodology has been developed that …

Evaluating Particulate Matter 2.5 In The Yangtze River Delta, Muhammad Abdullah

Graduate Theses/Dissertations

Particulate Matter 2.5 (PM_2.5) is a growing concern in industrialized countries. In China, high concentrations of PM_2.5 are causing devastating health and environmental effects for the people living there. Coal-burning for domestic and industrial purposes is the main culprit for decreasing air quality in China. The focus of this paper is on the Yangtze River Delta (YRD) located on the eastern coast of China. Hourly PM_2.5 readings from March 2015 to June 2016 were obtained from 125 air quality monitoring stations (AQMS) in 23 cities in the YRD. In this study, PM_2.5 readings were examined …

A Geochemical And Statistical Investigation Of The Big Four Springs Region In Southern Missouri, Jordan Jasso Vega

Graduate Theses/Dissertations

The Big Four Springs region hosts four major first-order magnitude springs in southern Missouri and northern Arkansas. These springs are Big Spring (Carter County, MO), Greer Spring (Oregon County, MO), Mammoth Spring (Fulton County, AR), and Hodgson Mill Spring (Ozark County, MO). Based on historic dye traces and hydrogeological investigations, these springs drain an area of approximately 1500 square miles and collectively discharge an average of 780 million gallons of water per day. The rocks from youngest to oldest that are found in Big Four Springs region are the Cotter and Jefferson City Dolomite (Ordovician), Roubidoux Formation (Ordovician), Gasconade Dolomite …

Severe Acute Respiratory Syndrome Coronavirus 2 Transmission Potential, Iran, 2020, Kamalich Muniz-Rodriguez, Isaac Fung, Shayesteh R. Ferdosi, Sylvia Ofori, Yiseul Lee, Amna Tariq, Gerardo Chowell

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

To determine the transmission potential of severe acute respiratory syndrome coronavirus 2 in Iran in 2020, we estimated the reproduction number as 4.4 (95% CI 3.9–4.9) by using a generalized growth model and 3.5 (95% CI 1.3–8.1) by using epidemic doubling time. The reproduction number decreased to 1.55 after social distancing interventions were implemented.

Linear Methods For Regression With Small Sample Sizes Relative To The Number Of Variables., Rajesh Sikder

Electronic Theses and Dissertations

In data sets where there are a small number of observations but a large number of variables observed for each observation, ordinary least squares estimation cannot be used for regression models. There are many alternative including stepwise regression, penalized methods such as ridge regression and the LASSO, and methods based on derived inputs such as principal components regression and partial least squares regression. In this thesis, these five methods are described. K-fold cross validation is also discussed as a way for determining regularization parameters for each method. The performance of these methods in estimation and prediction is also examined through …

Effects Of Gender And Socioeconomic Status Towards Form Four Pupils’ Statistical Thinking Abilities, Jing Hui Ong

Student Works (2020-2029)

Statistical thinking abilities of Form Four students are not known as there is a lack of studies that measures it. Despite the fact that the students were exposed to the same curriculum and pedagogy, the thinking abilities of students varied in terms of gender. There is also uncertainty in whether socio-economic status is a cause that affects statistical thinking abilities due to lack of research in that particular area. This study aimed to examine the effects of gender and socio-economic status on statistical thinking abilities of Form Four students. To answer the three research questions of this study, survey descriptive …

Data Mining For Structural Damage Identification Using Hybrid Artificial Neural Network Based Algorithm For Beam And Slab Girder, Gordan Meisam

Student Works (2020-2029)

One of the approaches for structural health monitoring (SHM) consists of two major components, i.e. a network of sensors to collect the response data and an extraction method to obtain information on the structural health condition. Data mining (DM) is a novel data extraction technology which can employ for development of inverse analysis. Implementation of DM techniques in different areas of civil engineering has recently given very good results. However, application of DM in SHM is not used as much as expected, thus, many challenges are still ahead. Therefore, it is necessary to develop the applicability of DM in SHM. …

Statistical Methods For Resolving Intratumor Heterogeneity With Single-Cell Dna Sequencing, Alexander Davis

Dissertations and Theses (Open Access)

Tumor cells have heterogeneous genotypes, which drives progression and treatment resistance. Such genetic intratumor heterogeneity plays a role in the process of clonal evolution that underlies tumor progression and treatment resistance. Single-cell DNA sequencing is a promising experimental method for studying intratumor heterogeneity, but brings unique statistical challenges in interpreting the resulting data. Researchers lack methods to determine whether sufficiently many cells have been sampled from a tumor. In addition, there are no proven computational methods for determining the ploidy of a cell, a necessary step in the determination of copy number. In this work, software for calculating probabilities from …

D-Vine Pair-Copula Models For Longitudinal Binary Data, Huihui Lin

Mathematics & Statistics Theses & Dissertations

Dependent longitudinal binary data are prevalent in a wide range of scientific disciplines, including healthcare and medicine. A popular method for analyzing such data is the multivariate probit (MP) model. The motivation for this dissertation stems from the fact that the MP model fails even the binary correlations are within the feasible range. The reason being the underlying correlation matrix of the latent variables in the MP model may not be positive definite. In this dissertation, we study alternatives that are based on D-vine pair-copula models. We consider both the serial dependence modeled by the first order autoregressive (AR(1)) and …

A Bayesian Markov Chain Monte Carlo Approach To Uncertainty Quantification, Matthew Isaac

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Uncertainty quantification (UQ) is a framework used frequently in engineering analyses to understand how uncertainty in system inputs lead to uncertainty in the system output. An instability is observed in a UQ method proposed by Roy and Oberkampf and a Bayesian Markov Chain Monte Carlo approach to UQ is offered as an alternative. The Bayesian approach allows analysts to incorporate information from various available sources including observed measurements and expert opinion and to update the analysis and results as more information becomes available. An illustrative engineering example is provided as a platform to demonstrate the Bayesian UQ approach and to …

Activation Of Trpa1 Nociceptor Promotes Systemic Adult Mammalian Skin Regeneration, Jenny J. Wei, Hali S. Kim, Casey A. Spencer, Donna Brennan-Crispi, Ying Zheng, Nicolette M. Johnson, Misha Rosenbach, Christopher Miller, Denis H. Y. Leung, George Cotsarelis, Thomas H. Leung

Research Collection School Of Economics

Adult mammalian wounds, with rare exception, heal with fibrotic scars that severely disrupt tissue architecture and function. Regenerative medicine seeks methods to avoid scar formation and restore the original tissue structures. We show in three adult mouse models that pharmacologic activation of the nociceptor TRPA1 on cutaneous sensory neurons reduces scar formation and can also promote tissue regeneration. Local activation of TRPA1 induces tissue regeneration on distant untreated areas of injury, demonstrating a systemic effect. Activated TRPA1 stimulates local production of interleukin-23 (IL-23) by dermal dendritic cells, leading to activation of circulating dermal IL-17–producing γδ T cells. Genetic ablation of …

Analyzing The Fractal Dimension Of Various Musical Pieces, Nathan Clark

Industrial Engineering Undergraduate Honors Theses

One of the most common tools for evaluating data is regression. This technique, widely used by industrial engineers, explores linear relationships between predictors and the response. Each observation of the response is a fixed linear combination of the predictors with an added error element. The method is built on the assumption that this error is normally distributed across all observations and has a mean of zero. In some cases, it has been found that the inherent variation is not the result of a random variable, but is instead the result of self-symmetric properties of the observations. For data with these …