Applied Statistics Commons^™

Physically Based Preconditioning Techniques Applied To The First Order Particle Transport And To Fluid Transport In Porous Media, Michael Rigley

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Solving linear systems is at the heart of many scientific applications from the PreAlgebra's student solving for x and y for basic geometry problems to the computational scientist solving billions of equations with billions of variables for weather forecasting, modeling fusion reactions, or web search algorithms. In this study we look at improving the efficiency of solving large linear systems that result from two applications. The first includes linear systems that result from solving differential equations for the movement of atomic particles in particle emitting, void, and absorbing regions. The second includes solving linear systems that result from solving differential …

Implementation And Application Of The Curds And Whey Algorithm To Regression Problems, John Kidd

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

A common statistical problem is trying to predict two or more variables using a set of predictor variables. The simplest model for this situation is called multivariate linear regression. This method uses each set of predictor variables to predict each of the response variables separately. This approach seems counter-intuitive as any possible relationship between the variables being predicted is ignored.

Breiman and Friedman found a way to take advantage of relationships among the response variables to increase the accuracy of the predictions for each of the predicted variables with an algorithm they called Curds and
Whey. It uses other statistical …

Success In Professional Baseball: The Value Of Above Average Position Players, Heath Detweiler

Senior Honors Theses

In professional baseball, efficient spending is the key to success. Because modern player contracts are so costly, front offices must seek out the most valuable players. In addition, to reach the playoffs, teams need offensively above average players at some positions. Together, these facts lead to an interesting question of whether or not defensive position impacts the value of offensively above average players. To answer this question, reliable metrics of offensive ability must be employed and appropriately analyzed.

Through an analysis involving on-base percentage, park-adjusted linear weights, and weighted on-base average over the course of the 2010 through 2013 Major …

A Comparison Of Students’ Perceptions Of Stress In Parallel Problem-Based And Lecture-Based Curricula, Sonia Wardley, Brooks Applegate, Deyab Almaleki, James Van Rhee

Research and Creative Activities Poster Day

Introduction

What is stress? Research asserts that stress is the mental state that results from an inability to cope (Burton 2004)

Why focus on stress?

• Persistent stress can lead to serious psychological problems such as interpersonal difficulties, depression, anxiety, and even suicide (Shapiro 2000)
• Several studies have found up to a third of medical students experience stress-related problems

The importance of this study comes from: A review of the extent literature suggests there is no systematic inquiry of the effects of stress experienced by students in LBL and PBL curricula in PA education

A Scalable Supervised Subsemble Prediction Algorithm, Stephanie Sapp, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Subsemble is a flexible ensemble method that partitions a full data set into subsets of observations, fits the same algorithm on each subset, and uses a tailored form of V-fold cross-validation to construct a prediction function that combines the subset-specific fits with a second metalearner algorithm. Previous work studied the performance of Subsemble with subsets created randomly, and showed that these types of Subsembles often result in better prediction performance than the underlying algorithm fit just once on the full dataset. Since the final Subsemble estimator varies depending on the data used to create the subset-specific fits, different strategies for …

What Residualizing Predictors In Regression Analyses Does (And What It Does Not Do), Lee H. Wurm, Sebastiano A. Fisicaro

Psychology Faculty Research Publications

Psycholinguists are making increasing use of regression analyses and mixed-effects modeling. In an attempt to deal with concerns about collinearity, a number of researchers orthogonalize predictor variables by residualizing (i.e., by regressing one predictor onto another, and using the residuals as a stand-in for the original predictor). In the current study, the effects of residualizing predictor variables are demonstrated and discussed using ordinary least-squares regression and mixed-effects models. Some of these effects are almost certainly not what the researcher intended and are probably highly undesirable. Most importantly, what residualizing does not do is change the result for the residualized variable, …

A Metaevaluation Of Evaluations Of Health Care Programs That Employ The Chronic Care Model, Jan Fields

Dissertations

Background: The purpose of this dissertation is to explore the use of metaevaluation to evaluate the quality of healthcare studies conducted on programs that employ the Chronic Care Model (CCM) to provide chronic illness care. In this study, healthcare studies of CCM programs are regarded as program evaluations. Method: Using a non-experimental cross-sectional design, 28 healthcare studies of CCM programs were evaluated using the accuracy standards portion of the Program Evaluations Metaevaluation Checklist (Stufflebeam, 2011). The results of the metaevaluations were analyzed and compared to the HEAL grade of the same healthcare studies as determined by the Hierarchy of Evidence …

Using Multi-Objective Value Estimation To Support Predictive Analytics For Human Service Project Management, David D. Wingard

Dissertations

Human service organizations need outcome measurement approaches that support project management for efficiency and effectiveness. While, in recent years, human services have increased their capacity to manage data and measure outcomes empirically, several barriers remain. First, current outcome measurement practices are not designed to effectively support the management of human services programs for maximum efficiency and effectiveness. Second, human services organizations need a methodology to manage programs to identified outcomes. This dissertation explored meaningful solutions to both issues. In Paper 1 (Chapter II), this dissertation assessed strengths and limitations of current outcome evaluation approaches and suggested an innovative application of …

New Statistical Methods For Analysis Of Historical Data From Wildlife Populations, Trevor Hefley

Department of Statistics: Dissertations, Theses, and Student Research

Wildlife biologists, many times with the help of ordinary citizens, have developed and maintained long-term datasets for monitoring the status of wildlife populations. These datasets can range from a collection of citizen-reported sightings of a rare species, to datasets collected by biologists using standardized methods. The commonality is that these datasets span a temporal and spatial scale that is beyond the scope of most scientific studies. Ensuring the continued persistence of wildlife populations requires predictions of the impact of human actions. Regardless if the predictions are quantitative or qualitative, the best we can do is use the past data to …

Predictors And Moderators Of Outcomes Of Hiv/Std Sex Risk Reduction Interventions In Substance Abuse Treatment Programs: A Pooled Analysis Of Two Randomized Controlled Trials, Paul Crits-Christoph, Robert Gallop, Jaclyn S. Sadicario, Hannah M. Markell, Donald A. Calsyn, Wan Tang, Hua He, Xin Tu, George Woody

Mathematics Faculty Publications

No abstract provided.

On The Joys Of Missing Data, Todd D. Little, Terrence D. Jorgensen, Kyle M. Lang, E. Whitney G. Moore

Kinesiology, Health and Sport Studies

We provide conceptual introductions to missingness mechanisms—missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR)—and state-of-the-art methods of handling missing data—full-information maximum likelihood (FIML) and multiple imputation (MI)—followed by a discussion of planned missing designs: multiform questionnaire protocols, two-method measurement models, and wave-missing longitudinal designs. We reviewed 80 articles of empirical studies published in the 2012 issues of the Journal of Pediatric Psychology to present a picture of how adequately missing data are currently handled in this field. To illustrate the benefits of utilizing MI or FIML and incorporating planned missingness into study designs, …

Demonstration Databases (Supplemental To Psychology & Health Article), Blair T. Johnson

CHIP Documents

Here is a database (in Stata, R, SAS, SPSS formats) that was used to demonstrate simple slopes analysis in meta-regression in an online supplement to the article, "Panning for the gold in health research: Incorporating studies’ methodological quality in meta-analysis," published in the journal Psychology & Health in 2014. It is an archive (zip) file that also contains the Stata syntax used in the demonstrations.

Meta-Analysis Of Social-Personality Psychological Research, Blair T. Johnson, Alice H. Eagly

CHIP Documents

This publication provides a contemporary treatment of the subject of meta-analysis in relation to social-personality psychology. Meta-analysis literally refers to the statistical pooling of the results of independent studies on a given subject, although in practice it refers as well to other steps of research synthesis, including defining the question under investigation, gathering all available research reports, coding of information about the studies and their effects, and interpretation/dissemination of results. Discussed as well are the hallmarks of high-quality meta-analyses.

Instrumental Neutron Activation Analysis (Inaa) Of Shell-Tempered Ceramics In The Ancestral Caddo Region: Rethinking Methods, Robert Z. Selden Jr., Timothy K. Perttula

CRHR: Archaeology

The geochemical analysis of shell-tempered ceramics in the ancestral Caddo region has been a matter of confusion since the mid-1990s. While Caddo archaeologists have long perceived most or all of the shell-tempered ceramics in East Texas to have originated from two different areas within the Red River basin, the geochemical data and interpretations remain inconsistent with that idea. This poster takes another look at this dataset, and considers an approach that was initially put forth by MURR, and then seemingly abandoned. Using only the geochemical data from shell-tempered sherds, we take a closer look at the contributions of calcium (Ca), …

Advances In Documentation, Digital Curation, Virtual Exhibition, And A Test Of 3d Geometric Morhpometrics: A Case Study Of The Vanderpool Vessels From The Ancestral Caddo Territory, Robert Z. Selden Jr., Timothy K. Perttula, Michael J. O'Brien

CRHR: Archaeology

Three-dimensional (3D) digital scanning of archaeological materials is typically used as a tool for artifact documentation. With the permission of the Caddo Nation of Oklahoma, 3D documentation of Caddo funerary vessels from the Vanderpool site (41SM77) was conducted with the initial goal of ensuring that these data would be publicly available for future research long after the vessels were repatriated. A digital infrastructure was created to archive and disseminate the resultant 3D datasets, ensuring that they would be accessible by both researchers and the general public (CRHR 2014a). However, 3D imagery can be used for much more than documentation. To …

Experimental Validation Of Robotic Manifold Tracking In Gyre-Like Flows, Matthew Michini, M. Ani Hsieh, Eric Forgoston, Ira B. Schwartz

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

In this paper, we present a first attempt toward experimental validation of a multi-robot strategy for tracking manifolds and Lagrangian coherent structures (LCS) in flows. LCS exist in natural fluid flows at various scales, and they are time-varying extensions of stable and unstable manifolds of time invariant dynamical systems. In this work, we present the first steps toward experimentally validating our previously proposed real-time manifold and LCS tracking strategy that relies solely on local measurements. Although we have validated the strategy in simulations using analytical flow models, experimental flow data, and actual ocean data, the strategy has never been implemented …

Transportation Of Perishable And Refrigerated Foods In Mylar Foil Bags And Insulated Containers: A Time-Temperature Study, Yanyan Li, John P. Schrade, Haiyan Su, John Specchio

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

Data are lacking on the temperature changes of food during transport without the use of refrigerated trucks. The purpose of this study was to evaluate the ability of several insulated and noninsulated containers with or without frozen gel packs to keep perishable and refrigerated foods within the temperature safe zone in relationship to duration of transport. The study was designed to duplicate the practices exhibited by customers purchasing perishable food products from a cash-and-carry business. Approximately 40 perishable food items were evaluated. Four types of containers were tested: a mylar foil bag, a commercial insulated bag, a generic insulated bag, …

Performance Modeling And Optimization Techniques For Heterogeneous Computing, Supada Laosooksathit

Doctoral Dissertations

Since Graphics Processing Units (CPUs) have increasingly gained popularity amoung non-graphic and computational applications, known as General-Purpose computation on GPU (GPGPU), CPUs have been deployed in many clusters, including the world's fastest supercomputer. However, to make the most efficiency from a GPU system, one should consider both performance and reliability of the system.

This dissertation makes four major contributions. First, the two-level checkpoint/restart protocol that aims to reduce the checkpoint and recovery costs with a latency hiding strategy in a system between a CPU (Central Processing Unit) and a GPU is proposed. The experimental results and analysis reveals some benefits, …

Generalized Weibull And Inverse Weibull Distributions With Applications, Valeriia Sherina

College of Graduate Studies: Theses & Dissertations

In this thesis, new classes of Weibull and inverse Weibull distributions including the generalized new modified Weibull (GNMW), gamma-generalized inverse Weibull (GGIW), the weighted proportional inverse Weibull (WPIW) and inverse new modified Weibull (INMW) distributions are introduced. The GNMW contains several sub-models including the new modified Weibull (NMW), generalized modified Weibull (GMW), modified Weibull (MW), Weibull (W) and exponential (E) distributions, just to mention a few. The class of WPIW distributions contains several models such as: length-biased, hazard and reverse hazard proportional inverse Weibull, proportional inverse Weibull, inverse Weibull, inverse exponential, inverse Rayleigh, and Frechet distributions as special cases. Included …

Generalized Classes Of Distributions With Applications To Income And Lifetime Data, Shujiao Huang

College of Graduate Studies: Theses & Dissertations

In this thesis, new classes of distributions namely: exponentiated Kumaraswamy-Dagum (EKD), Log-exponentiated Kumaraswamy-Dagum (Log-EKD), McDonald Log-logistic (McLLog) and Gamma-Dagum (GD) distributions are presented. A thorough and comprehensive investigation of these classes of distributions is conducted. Mathematical properties of these classes of distributions including series expansion, hazard and reverse hazard functions, moments, generating functions, mean and median deviations, Bonferroni and Lorenz curves, distribution of order statistics, moments of order statistics and entropies are presented. Estimation of parameters of these distributions via maximum likelihood technique, Fisher information and asymptotic confidence intervals are given. Maximum likelihood estimation of the parameters of the exponentiated …

Dynamic Bayesian Approaches To The Statistical Calibration Problem, Derick Lorenzo Rivers

Theses and Dissertations

The problem of statistical calibration of a measuring instrument can be framed both in a statistical context as well as in an engineering context. In the first, the problem is dealt with by distinguishing between the "classical" approach and the "inverse" regression approach. Both of these models are static models and are used to estimate "exact" measurements from measurements that are affected by error. In the engineering context, the variables of interest are considered to be taken at the time at which you observe the measurement. The Bayesian time series analysis method of Dynamic Linear Models (DLM) can be used …

Planned Missing Data Designs & Small Sample Size: How Small Is Too Small?, Fan Jia, E. Whitney G. Moore, Richard Kinai, Kelly S. Crowe, Alexander M. Schoemann, Todd D. Little

Kinesiology, Health and Sport Studies

Utilizing planned missing data (PMD) designs (ex. 3-form surveys) enables researchers to ask participants fewer questions during the data collection process. An important question, however, is just how few participants are needed to effectively employ planned missing data designs in research studies. This paper explores this question by using simulated three-form planned missing data to assess analytic model convergence, parameter estimate bias, standard error bias, mean squared error (MSE), and relative efficiency (RE).Three models were examined: a one-time point, cross-sectional model with 3 constructs; a two-time point model with 3 constructs at each time point; and a three-time point, mediation …

The Initial Phases Of A Consistent Pricing System That Reflects The Online Sale Value Of A Horse, Curran A. Prettyman

Lewis Honors College Capstone Collection

Horses are one of the most uniquely priced commodities. This document provides a solution to an industry-wide weakness of inconsistent pricing and confusion. In the following report, an evaluation of the industry flaw is presented, an econometric approach is described in full, and a solution is proposed using insight gained from a regression analysis. This report uses an econometric approach to determine the impact of hunter jumper horse qualities on internet sale prices. Data is compiled from bigeq.com for seventy-eight horses in the states of Illinois, Indiana, Kentucky, Michigan, and Ohio. A linear regression analysis for twelve variables establishes that …

Genetic Association Testing Of Copy Number Variation, Yinglei Li

Theses and Dissertations--Statistics

Copy-number variation (CNV) has been implicated in many complex diseases. It is of great interest to detect and locate such regions through genetic association testings. However, the association testings are complicated by the fact that CNVs usually span multiple markers and thus such markers are correlated to each other. To overcome the difficulty, it is desirable to pool information across the markers. In this thesis, we propose a kernel-based method for aggregation of marker-level tests, in which first we obtain a bunch of p-values through association tests for every marker and then the association test involving CNV is based on …

Multi-Peak Solutions To Two Types Of Free Boundary Problems, Yi Li, Shuangjie Peng

Mathematics and Statistics Faculty Publications

We consider the existence of multi-peak solutions to two types of free boundary problems arising in confined plasma and steady vortex pair under conditions on the nonlinearity we believe to be almost optimal. Our results show that the “core” of the solution has multiple connected components, whose boundary called free boundary of the problems consists approximately of spheres which shrink to distinct single points as the parameter tends to zero.

A General Procedure Of Estimating Population Mean Using Information On Auxiliary Attribute, Sachin Malik, Rajesh Singh, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

This paper deals with the problem of estimating the finite population mean when some information on auxiliary attribute is available. It is shown that the proposed estimator is more efficient than the usual mean estimator and other existing estimators. The results have been illustrated numerically by taking empirical population considered in the literature.

A Generalized Family Of Estimators For Estimating Population Mean Using Two Auxiliary Attributes, Sachin Malik, Rajesh Singh, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

This paper deals with the problem of estimating the finite population mean when some information on two auxiliary attributes are available. A class of estimators is defined which includes the estimators recently proposed by Malik and Singh (2012), Naik and Gupta (1996) and Singh et al. (2007) as particular cases. It is shown that the proposed estimator is more efficient than the usual mean estimator and other existing estimators. The study is also extended to two-phase sampling. The results have been illustrated numerically by taking empirical population considered in the literature.

Fusarium Head Blight Resistance And Agronomic Performance In Soft Red Winter Wheat Populations, Daniela Sarti Dvorjak

Theses and Dissertations--Plant and Soil Sciences

Fusarium head blight (FHB), caused by Fusarium graminearum Schwabe [telomorph: Gibberella zeae Schwein.(Petch)], is recognized as one of the most destructive diseases of wheat (Triticum aestivum L. and T. durum L.) and barley (Hordeum vulgare L.) worldwide. Breeding for FHB resistance must be accompanied by selection for desirable agronomic traits. Donor parents with two FHB resistance quantitative trait loci (QTL) Fhb1 (chromosome 3BS) and QFhs.nau-2DL (chromosome 2DL) were crossed to four adapted SRW wheat lines to generate backcross and forward cross progeny. F₂ individuals were genotyped and assigned to 4 different groups according to presence/ absence of …

An Investigation Of Sensitivity Of An F Test In Locating Change Points In Linear Regression, Jing Sun

College of Graduate Studies: Theses & Dissertations

Change point is a statistic phenomenon, which has many direct applications in climatology, bioinformatics, finance, oceanography and medical imaging. In this thesis, we investigate the sensitivity of the F-test for detecting change points in linear regression, using a two-phase linear regression model. it offers an effective method to detect "undocumented" change points using a form of an F-test. Using simulated data, we explore its sensitivity and accuracy with respect t different parameters in the model.