Regression Analyses Assessing The Impact Of Environmental Factors On Covid-19 Transmission And Mortality, 2021 Wayne State University
Regression Analyses Assessing The Impact Of Environmental Factors On Covid-19 Transmission And Mortality, El Hussain Shamsa, Kezhong Zhang
Medical Student Research Symposium
No abstract provided.
Review Of Forecasting Univariate Time-Series Data With Application To Water-Energy Nexus Studies & Proposal Of Parallel Hybrid Sarima-Ann Model, Cory Sumner Yarrington
Graduate Theses, Dissertations, and Problem Reports
The necessary materials for most human activities are water and energy. Integrated analysis to accurately forecast water and energy consumption enables the implementation of efficient short and long-term resource management planning as well as expanding policy and research possibilities for the supportive infrastructure. However, the integral relationship between water and energy (water-energy nexus) poses a difficult problem for modeling. The accessibility and physical overlay of data sets related to water-energy nexus is another main issue for a reliable water-energy consumption forecast. The framework of urban metabolism (UM) uses several types of data to build a global view and highlight issues ...
Neither “Post-War” Nor Post-Pregnancy Paranoia: How America’S War On Drugs Continues To Perpetuate Disparate Incarceration Outcomes For Pregnant, Substance-Involved Offenders, Becca S. Zimmerman
Pitzer Senior Theses
This thesis investigates the unique interactions between pregnancy, substance involvement, and race as they relate to the War on Drugs and the hyper-incarceration of women. Using ordinary least square regression analyses and data from the Bureau of Justice Statistics’ 2016 Survey of Prison Inmates, I examine if (and how) pregnancy status, drug use, race, and their interactions influence two length of incarceration outcomes: sentence length and amount of time spent in jail between arrest and imprisonment. The results collectively indicate that pregnancy decreases length of incarceration outcomes for those offenders who are not substance-involved but not evenhandedly -- benefitting white pregnant ...
Gene Set Testing By Distance Correlation, 2020 University of Arkansas, Fayetteville
Gene Set Testing By Distance Correlation, Sho-Hsien Su
Theses and Dissertations
Pathways are the functional building blocks of complex diseases such as cancers. Pathway-level studies may provide insights on some important biological processes. Gene set test is an important tool to study the differential expression of a gene set between two groups, e.g., cancer vs normal. The differential expression of a gene set could be due to the difference in mean, variability, or both. However, most existing gene set tests only target the mean difference but overlook other types of differential expression. In this thesis, we propose to use the recently developed distance correlation for gene set testing. To assess ...
Lecture Notes On Modern Multivariate Statistical Learning-Version Iv, 2020 Iowa State University and Analytics Iowa LLC
Lecture Notes On Modern Multivariate Statistical Learning-Version Iv, Stephen B. Vardeman
This set of notes is the most recent reorganization and update-in-progress of Modern Multivariate Statistical Learning course material developed 2009-2020 over 7 offerings of PhD-level courses and 4 offerings of an MS-level course in the Iowa State University Statistics Department, a short course given in the Statistics Group at Los Alamos National Lab, and two offered through Statistical Horizons LLC. Early versions of the courses were based mostly on the topics and organization of The Elements of Statistical Learning by Hastie, Tibshirani, and Friedman, though very substantial parts benefitted from Izenman’s Modern Multivariate Statistical Techniques, and from Principles and ...
Resource-Saving Technologies For The Production Of Elastic Leather Materials: Collective Monograph, 2020 University of Tennessee, Knoxville
Resource-Saving Technologies For The Production Of Elastic Leather Materials: Collective Monograph, Olena Korotych, Anatolii Danylkovych, Serhii Bilinskyi, Serhii Bondarenko, Slava Branovitska, Vasyl Chervinskyi, Nataliia Khliebnikova, Alona Kudzieva, Viktor Lishchuk, Nataliia Lysenko, Olena Mokrousova, Nataliia Omelchenko, Vera Palamar, Yuliia Potakh, Oksana Romanyuk, Olga Sanginova, Oleksandr Zhyhotsky
Chemistry Publications and Other Works
This monograph contains a collection of recent research papers focusing on advancing existing technologies and developing new technologies to improve the environmentally friendliness and save resources during the production of elastic leather materials. The papers are organized based on the type of technological process used to preserve raw hides. A lot of attention is devoted to mathematical planning, simulations, and multicriteria optimization of the technological processes using newly developed chemical reagents. The monograph contains a complex study of physicochemical properties and characteristics of the resulting leather materials. The developed technologies were tested by the private joint-stock company Chinbar (Kyiv, Ukraine ...
A Geochemical And Statistical Investigation Of The Big Four Springs Region In Southern Missouri, 2020 Missouri State University
A Geochemical And Statistical Investigation Of The Big Four Springs Region In Southern Missouri, Jordan Jasso Vega
MSU Graduate Theses
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 ...
Improving The Quality And Design Of Retrospective Clinical Outcome Studies That Utilize Electronic Health Records, 2020 HCA Healthcare Mountain MidAmerica and Continental Divisions
Improving The Quality And Design Of Retrospective Clinical Outcome Studies That Utilize Electronic Health Records, Oliwier Dziadkowiec, Jeffery Durbin, Vignesh Jayaraman Muralidharan, Megan Novak, Brendon Cornett
HCA Healthcare Journal of Medicine
Electronic health records (EHRs) are an excellent source for secondary data analysis. Studies based on EHR-derived data, if designed properly, can answer previously unanswerable clinical research questions. In this paper we will highlight the benefits of large retrospective studies from secondary sources such as EHRs, examine retrospective cohort and case-control study design challenges, as well as methodological and statistical adjustment that can be made to overcome some of the inherent design limitations, in order to increase the generalizability, validity and reliability of the results obtained from these studies.
Effect Of Predictor Dependence On Variable Selection For Linear And Log-Linear Regression, 2020 University of Arkansas, Fayetteville
Effect Of Predictor Dependence On Variable Selection For Linear And Log-Linear Regression, Apu Chandra Das
Theses and Dissertations
We propose a Bayesian approach to the Dirichlet-Multinomial (DM) regression model, which uses horseshoe, Laplace, and horseshoe plus priors for shrinkage and selection. The Dirichlet-Multinomial model can be used to find the significant association between a set of available covariates and taxa for a microbiome sample. We incorporate the covariates in a log-linear regression framework. We design a simulation study to make a comparison among the performance of the three shrinkage priors in terms of estimation accuracy and the ability to detect true signals. Our results have clearly separated the performance of the three priors and indicated that the horseshoe ...
Learning Networks With Categorical Data Using Distance Correlation, And A Novel Graph-Based Multivariate Test, 2020 University of Arkansas, Fayetteville
Learning Networks With Categorical Data Using Distance Correlation, And A Novel Graph-Based Multivariate Test, Jian Tinker
Theses and Dissertations
We study the use of distance correlation for statistical inference on categorical data, especially the induction of probability networks. Szekely et al. first defined distance correlation for continuous variables in , and Zhang translated the concept into the categorical setting in  by defining dCor(X,Y) for categorical variables X = (x1,...,xI) and Y = (y1,...,yJ) where P(X=xi)=[pi]i and P(Y=yi)=[pi]j with the formula [Please open the document]
Part I of the dissertation covers the background we need to understand this formula, and prepares us to analyze the properties and performance of ...
Assessing Differential Item Functioning In The Perceived Stress Scale, 2020 University of Arkansas, Fayetteville
Assessing Differential Item Functioning In The Perceived Stress Scale, Nana Amma Berko Asamoah
Theses and Dissertations
When an item on a test functions differently for subgroups of respondents with respect to an exogenous variable (or covariate) after conditioning on the latent variable of interest, the item is said to exhibit Differential Item Functioning (DIF). The 10-item Perceived Stress Scale (PSS10) is administered to respondents via MTurk to quantify “perceived stress” and identify if items on the scale function differently for specific subgroups defined by age, sex, race, marital status, number of children, employment status and social media usage.
The purpose of this study was to compare traditional DIF detection approaches (Mantel-Haenszel, logistic regression, likelihood ratio test ...
Chemostratigraphy Of Carbonate Gravity Flows Of The Wolfcamp Formation In Crockett County, Midland Basin, Texas, 2020 Stephen F Austin State University
Chemostratigraphy Of Carbonate Gravity Flows Of The Wolfcamp Formation In Crockett County, Midland Basin, Texas, Alex Blizzard, Julie Bloxson
Electronic Theses and Dissertations
Sediment gravity flows into deep-water environments are important stratigraphic traps in lithologically diverse reservoirs generating multiple plays for hydrocarbon exploration. These highly heterogeneous deposits can be studied by utilizing chemostratigraphy and higher-order sequence stratigraphy; being an accurate method for reservoir characterization. Studying these gravity flows along a carbonate platform’s slope can further expand an understanding of the stratigraphy that is filling adjacent basins. The application of elemental analyses can support in identifying mineralogy that impact reservoir quality, especially when conventional testing cannot be applied.
This study utilizes five cores containing the Wolfcamp Formation from the southeastern slope of the ...
Forecasting Daily Stock Market Return With Multiple Linear Regression, 2020 Louisiana Tech University
Forecasting Daily Stock Market Return With Multiple Linear Regression, Shengxuan Chen
Mathematics Senior Capstone Papers
The purpose of this project is to use data mining and big data analytic techniques to forecast daily stock market return with multiple linear regression. Using mathematical and statistical models to analyze the stock market is important and challenging. The accuracy of the final results relies on the quality of the input data and the validity of the methodology. In the report, within 5-year period, the data regarding eleven financial and economical features are observed and recorded on each trading day. After preprocessing the raw data with statistical method, we use the multiple linear regression to predict the daily return ...
Demand Forecasting In Wholesale Alcohol Distribution: An Ensemble Approach, 2020 Southern Methodist University
Demand Forecasting In Wholesale Alcohol Distribution: An Ensemble Approach, Tanvi Arora, Rajat Chandna, Stacy Conant, Bivin Sadler, Robert Slater
SMU Data Science Review
In this paper, historical data from a wholesale alcoholic beverage distributor was used to forecast sales demand. Demand forecasting is a vital part of the sale and distribution of many goods. Accurate forecasting can be used to optimize inventory, improve cash ow, and enhance customer service. However, demand forecasting is a challenging task due to the many unknowns that can impact sales, such as the weather and the state of the economy. While many studies focus effort on modeling consumer demand and endpoint retail sales, this study focused on demand forecasting from the distributor perspective. An ensemble approach was applied ...
The Expanded View Of Individualism And Collectivism: One, Two, Or Four Dimensions?, 2020 Kennesaw State University
The Expanded View Of Individualism And Collectivism: One, Two, Or Four Dimensions?, Jennifer L. Priestley, Kamal Fatehi, Gita Taasoobshirazi
Recent research to analyze and discuss cultural differences has employed a combination of five major dimensions of individualism–collectivism, power distance, uncertainty avoidance, femininity– masculinity (gender role differentiation), and long-term orientation. Among these dimensions, individualism–collectivism has received the most attention. Chronologically, this cultural attribute has been regarded as one, then two, and more recently, four dimensions of horizontal and vertical individualism and collectivism. However, research on this issue has not been conclusive and some have argued against this expansion. The current study attempts to explain and clarify this discussion by using a shortened version of the scale developed by ...
Interdependence Across Foreign Exchange Rate Markets- A Mixed Copula Approach, 2020 Western Kentucky University
Interdependence Across Foreign Exchange Rate Markets- A Mixed Copula Approach, Richard Adjei-Boateng
Masters Theses & Specialist Projects
The purpose of this thesis is to study the dependence structure of exchange rate pairs using a mixture of copula as opposed to a single copula approach. Mixed copula models have the ability to generate dependence structures that do not belong to existing copula families. The flexibility in choosing component copulas in this mixture model aids the construction of a system that is simultaneously parsimonious and flexible enough to generate most dependence patterns in exchange rate data. Furthermore, the method of mixture copulas facilitates the separation of both the structure and degree of dependence, concepts that are respectively embodied in ...
Bayesian Methods For The Assessment Of Reporting Errors For Data-Sparse Population-Periods With Applications To Estimating Mortality, 2020 University of Massachusetts Amherst
Bayesian Methods For The Assessment Of Reporting Errors For Data-Sparse Population-Periods With Applications To Estimating Mortality, Emily Peterson
Population level mortality data is often subject to substantial reporting errors due to misclassification of cause of death, misclassification of death status, or age reporting errors. Accuracy of error-prone data sources can be assessed by comparing such data to gold standard data for the same population-period. We present Bayesian methods for assessing the extent of reporting errors across different population-periods and generalizing those to settings where gold-standard data are lacking. Firstly, we investigate misclassification errors of maternal cause of death reporting in civil registration vital statistics data. We use a Bayesian hierarchical bivariate random-walk model to estimate country-year specific sensitivity ...
Nanoindentation Characterization Of Elastic Properties Of Shales And Swelling Clay Minerals, 2020 University of Massachusetts Amherst
Nanoindentation Characterization Of Elastic Properties Of Shales And Swelling Clay Minerals, Shengmin Luo
Oil and gas shales are a class of multiscale, multiphase, hybrid inorganic-organic sedimentary rocks that consist of a generally uniform, preferentially oriented clay matrix with randomly embedded silt and sand particles as solid inclusions. A thorough understanding of the mechanical properties of shales is crucial for the exploration and production of oil and gas in the unconventional shale reservoirs, but it can be a challenging task due to their nature of compositional heterogeneity and microstructural anisotropy. In efforts to better characterize the mechanical properties of shales across different length scales and to fundamentally understand the laws of upscaling from individual ...
Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, 2020 Florida International University
Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang
FIU Electronic Theses and Dissertations
Alzheimer’s disease (AD) is the most common form of dementia affecting 10% of the population over the age of 65 and the growing costs in managing AD are estimated to be $259 billion, according to data reported in the 2017 by the Alzheimer's Association. Moreover, with cognitive decline, daily life of the affected persons and their families are severely impacted. Taking advantage of the diagnosis of AD and its prodromal stage of mild cognitive impairment (MCI), an early treatment may help patients preserve the quality of life and slow the progression of the disease, even though the underlying ...
Characterizing Uncertainty In Correlated Response Variables For Pareto Front Optimization, 2020 Air Force Institute of Technology
Characterizing Uncertainty In Correlated Response Variables For Pareto Front Optimization, Peter A. Calhoun
Theses and Dissertations
Current research provides a method to incorporate uncertainty into Pareto front optimization by simulating additional response surface model parameters according to a Multivariate Normal Distribution (MVN). This research shows that analogous to the univariate case, the MVN understates uncertainty, leading to overconfident conclusions when variance is not known and there are few observations (less than 25-30 per response). This research builds upon current methods using simulated response surface model parameters that are distributed according to an Multivariate t-Distribution (MVT), which can be shown to produce a more accurate inference when variance is not known. The MVT better addresses uncertainty in ...