Statistics and Probability Commons^™

Cardiometabolic Risk Assessments By Body Mass Index Z-Score Or Waist-To-Height Ratio In A Multiethnic Sample Of Sixth-Graders, Henry S. Kahn, Laure El Ghormli, Russell Jago, Gary D. Foster, Robert G. Mcmurray, John B. Buse, Diane D. Stadler, Roberto P. Trevino, Tom Baranowski, Healthy Study Group

GW Biostatistics Center

Convention defines pediatric adiposity by the body mass index -score (BMIz) referenced to normative growth charts. Waist-to-height ratio (WHtR) does not depend on sex-and-age references. In the HEALTHY Study enrollment sample, we compared BMIz with WHtR for ability to identify adverse cardiometabolic risk. Among 5,482 sixth-grade students from 42 middle schools, we estimated explanatory variations (R²) and standardized beta coefficients of BMIz or WHtR for cardiometabolic risk factors: insulin resistance (HOMA-IR), lipids, blood pressures, and glucose. For each risk outcome variable, we prepared adjusted regression models for four subpopulations stratified by sex and high versus lower fatness. …

Adaptive Stochastic Systems: Estimation, Filtering, And Noise Attenuation, Araz Ryan Hashemi

Wayne State University Dissertations

This dissertation investigates problems arising in identification and control of stochastic systems. When the parameters determining the underlying systems are unknown and/or time varying, estimation and adaptive filter- ing are invoked to to identify parameters or to track time-varying systems. We begin by considering linear systems whose coefficients evolve as a slowly- varying Markov Chain. We propose three families of constant step-size (or gain size) algorithms for estimating and tracking the coefficient parameter: Least-Mean Squares (LMS), Sign-Regressor (SR), and Sign-Error (SE) algorithms.

The analysis is carried out in a multi-scale framework considering the relative size of the gain (rate of …

Community Colleges And Public Health: An Integral Part Of The Continuum Of Education For Public Health, Richard Riegelman, Cynthia Wilson

Epidemiology Faculty Publications

No abstract provided.

Hiv Testing Implementation In Two Urban Cities: Practice, Policy, And Perceived Barriers., Camden J Hallmark, Jennifer Skillicorn, Thomas P Giordano, Jessica A Davila, Marlene Mcneese, Nestor Rocha, Avemaria Smith, Stacey Cooper, Amanda D. Castel

Epidemiology Faculty Publications

BACKGROUND: Although funding has supported the scale up of routine, opt-out HIV testing in the US, variance in implementation mechanisms and barriers in high-burden jurisdictions remains unknown.

METHODS: We conducted a survey of health care organizations in Washington, DC and Houston/Harris County to determine number of HIV tests completed in 2011, policy and practices associated with HIV testing, funding mechanisms, and reported barriers to testing in each jurisdiction and to compare results between jurisdictions.

RESULTS: In 2012, 43 Houston and 35 DC HIV-testing organizations participated in the survey. Participants represented 85% of Department of Health-supported testers in DC and 90% …

The Bivariate Erlang And Its Application In Modeling Recurrence Times Of Kidney Dialysis Data, Norou Diawara, S.H. Sathish Indika, Melva Grant, Edgard M. Maboudou-Tchao

Mathematics & Statistics Faculty Publications

Recent advances in computer modeling allows us to find closer fits to data. Our emphasis is on the interdependence between occurrence at kidney dialysis. The interdependence between kidney dialysis occurrences is modelled by a bivariate exponential that we propose in this article. The application is shown on the McGilchrist and Aisbett kidney data set with the use of the exponential distribution. The proposed bivariate exponential model has exponential marginal densities, correlated via a latent random variables and with finite probability of simultaneous occurrence. Extension of the model to a bivariate Erlang type distribution with same shape parameter is presented.

Statistics 301 Bilingual (English/Spanish), Laura Cayon

IMPACT Symposium

This poster outlining the redesign of STAT 301 (Elementary Statistical Methods) was presented at the IMPACT Symposium 2014.

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 Least-Squares Regressions Iii: Further Theory And Classification, Nataniel Greene

Publications and Research

This paper continues the work of this series with two results. The first is an exponential equivalence theorem which states that every generalized least-squares regression line can be generated by an equivalent exponential regression. It follows that every generalized least-squares line has an effective normalized exponential parameter between 0 and 1 which classifies the line on the spectrum between ordinary least-squares and the extremal line for a given set of data. The second result is the presentation of fundamental formulas for the generalized least-squares slope and y-intercept.

Applications Of Bayesian Nonparametrics To Reliability And Survival Data, Li Li

Theses and Dissertations

Reliability and survival data are widely encountered across many common settings. Subjects under investigation often include machines, bioassays, patients, etc.; their reliability or survival distribution, and its association with covariate processes, are commonly of interest. Within this dissertation, the first two chapters focus on reliability data where repairable systems fail and get interventions, e.g. repairs in the event process. It begins with a nonparametric test for the commonly assumed ''good as old'' assumption for minimal repair models and then a semi-parametric regression model is introduced for reliability data using Kijima's effective age. The third chapter focuses on survival data observed …

Resampling-Based Multiple Comparisons For Generalized Linear Models, Josephine Sarpong Akosa

Open Access Theses & Dissertations

Diverse applications in medical and epidemiological research routinely utilize generalized linear modeling to explain the relationship between the incidence of disease and particular risk factors. Researchers' interest in such models are estimated quantities from the model such as the response probabilities, the relative risks or the odds ratios and not the model itself. Often, the simultaneous estimation of these quantities or a subset of the quantities are warranted. The results are usually reported via confidence intervals at a pre-specified level of significance. Utilizing the usual 95% pointwise confidence intervals for the simultaneous inference inflates the risk of making type I …

Measuring Circuit Splits: A Cautionary Note, Aaron-Andrew P. Bruhl

Faculty Publications

A number of researchers have recently published new measures of the Supreme Court’s behavior in resolving conflicts in the lower courts. These new measures represent an improvement over prior, cruder approaches, but it turns out that measuring the Court’s resolutions of conflicts is surprisingly difficult. The aim of this methodological comment is to describe those difficulties and to establish several conclusions that follow from them. First, the new measures of the Court’s behavior are certainly imprecise and may reflect biased samples. Second, using the Supreme Court Database, which some studies rely on to assemble a dataset of cases resolving conflicts, …

Incorporating Dependence Boundaries In Simulating Associated Discrete Data, Mary E. Haynes

Theses and Dissertations

In the study of associated discrete variables, limitations on the range of the possible association measures (Pearson correlation, odds ratio, etc.) arise from the form of the joint probability function between the variables. These limitations are known as the Fréchet bounds. The bounds for cases involving associated binary variables are explored in the context of simulating datasets with a desired correlation and set of marginal probabilities. A new method for creating such datasets is compared to an existing method that uses the multivariate probit. A method for simulating associated binary variables using a desired odds ratio and known marginal probabilities …

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 …

Lost In Translation: Statistical Inference In Court, Erica Beecher-Monas

Law Faculty Research Publications

No abstract provided.

Identification Of Genomic Factors Using Family-Based Association Studies, Libo Wang

Open Access Dissertations

Genome-wide association studies become increasingly popular and important for detecting genetic associations of complex traits. However, it is well known that spurious associations could arise from statistical analysis without proper consideration of genetic relatedness of samples. Many methods have been proposed to guard against these spurious associations. Here we focus on multi-locus association studies of quantitative traits and the case-control status, and propose algorithms that take into consideration of genetic related samples to address possible confounding issues. As supervised dimension reduction methods, these algorithms performs well to conduct association studies with a large number of biomarkers but a relative small …

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 …

Roughened Random Forests For Binary Classification, Kuangnan Xiong

Legacy Theses & Dissertations (2009 - 2024)

Binary classification plays an important role in many decision-making processes. Random forests can build a strong ensemble classifier by combining weaker classification trees that are de-correlated. The strength and correlation among individual classification trees are the key factors that contribute to the ensemble performance of random forests. We propose roughened random forests, a new set of tools which show further improvement over random forests in binary classification. Roughened random forests modify the original dataset for each classification tree and further reduce the correlation among individual classification trees. This data modification process is composed of artificially imposing missing data that are …

A Stochastic Volatility Model With Leverage Effect And Regime Switching, Hong Jiang

Legacy Theses & Dissertations (2009 - 2024)

Modeling the volatility of asset returns is a very important study in financial economics. Among the time-varying volatility models, the Stochastic Volatility (SV) models are argued to have advantages over the autoregressive conditional heteroskedasticity (ARCH) models. The purpose of this article is to put forward a generalized and flexible Stochastic Volatility model, the Stochastic Volatility Model with Leverage Effect and Regime Switching (SVLR model), which could capture the complex features of financial time series to the most extent.