Statistics and Probability Commons^™

Racial And Ethnic Proportions Of Early In-Person Voters In Cuyahoga County, General Election 2008, And Implications For 2012, Norman Robbins, Mark Salling

All Maxine Goodman Levin School of Urban Affairs Publications

No abstract provided.

Demographic And Socioeconomic Conditions And A Patron Borrowing Analysis Of Cleveland Public Library Branch And Main Libraries, Mark Salling

All Maxine Goodman Levin School of Urban Affairs Publications

We provide here an analysis of the demographic and socioeconomic characteristics of the Cleveland Public Library’s (CPL) service area and that of the neighborhoods in which the library’s patrons live. We also describe the borrowing patterns for the branch and downtown, Main Library, locations. The census-based demographic and socioeconomic data used for the analysis include income, number of children, race, Hispanic ethnicity, language spoken at home, ability to speak English, public-versus-private school attendance by grade level, housing tenure (owner/renter), educational attainment, employment status, and place of employment (Cleveland versus other). Data from the 2010 census and the Census Bureau’s 2005-2009 …

Critical Assessment Of Outcomes In Acute Aortic Dissection (Type A) At A Community Hospital: A 10 Year Review, Timothy S. Misselbeck, James K. Wu Md, Stephen Deturk Ba, Michael F. Szwerc Md, Sanjay M. Mehta Md, Theodore G. Phillips Md, Gary W. Szydlowski Md, Raymond L. Singer Md

Department of Surgery

No abstract provided.

Generalizing Amdahl’S Law For Power And Energy, Rong Ge, Kirk W. Cameron

Mathematics, Statistics and Computer Science Faculty Research and Publications

Extending Amdahl's law to identify optimal power-performance configurations requires considering the interactive effects of power, performance, and parallel overhead.

Categoricity And Topological Graphs, Paul Bankston

Mathematics, Statistics and Computer Science Faculty Research and Publications

Let X be a topological graph, with arcs joined only at end points. If Y is any locally connected metrizable compactum that is co-elementarily equivalent to X, then Y is homeomorphic to X. In particular, X and Y are homeomorphic if some lattice base for one is elementarily equivalent to some lattice base for the other.

General Recognition Theory Extended To Include Response Times: Predictions For A Class Of Parallel Systems, James T. Townsend, Joseph W. Houpt, Noah H. Silbert

Psychology Faculty Publications

General Recognition Theory (GRT; Ashby & Townsend, 1986) is a multidimensional theory of classification. Originally developed to study various types of perceptual independence, it has also been widely employed in diverse cognitive venues, such as categorization. The initial theory and applications have been static, that is, lacking a time variable and focusing on patterns of responses, such as confusion matrices. Ashby proposed a parallel, dynamic stochastic version of GRT with application to perceptual independence based on discrete linear systems theory with imposed noise (Ashby, 1989). The current study again focuses on cognitive/perceptual independence within an identification classification paradigm. We extend …

The Dependent Samples T And Wilcoxon Sign Rank Maximum Test, Saverpierre Maggio

Wayne State University Dissertations

A maximum test using the parametric dependent samples t-test and the non-parametric Wilcoxon sign rank test was created using a FORTRAN program and various subroutines of the International Mathematical and Statistical Libraries (IMSL, 1980). Two tailed critical values were derived from a mixed normal distribution. Critical values obtained were at the 0.05, 0.025, 0.01 and 0.005 alpha levels via sample sizes (n) 8 through 30, 45, 60, 90 and 120. Critical values were compared to values obtained through the application of the Bonferroni correction method. It was concluded that the Bonferroni is an unnecessary method. Findings of the study are …

Linear Rank Tests Of Uniformity: Understanding Inconsistent Outcomes And The Construction Of New Tests, Anna E. Bargagliotti

Mathematics, Statistics and Data Science Faculty Works

Several nonparametric tests exist to test for differences among alternatives when using ranked data. Testing for differences among alternatives amounts to testing for uniformity over the set of possible permutations of the alternatives. Well-known tests of uniformity, such as the Friedman test or the Anderson test, are based on the impact of the usual limiting theorems (e.g. central limit theorem) and the results of different summary statistics (e.g. mean ranks, marginals, and pairwise ranks). Inconsistencies can occur among statistical tests' outcomes - different statistical tests can yield different outcomes when applied to the same ranked data. In this paper, we …

Analysis Of Discrete Choice Probit Models With Structured Correlation Matrices, Bhaskara Ravi

Mathematics & Statistics Theses & Dissertations

Discrete choice models are very popular in Economics and the conditional logit model is the most widely used model to analyze consumer choice behavior, which was introduced in a seminal paper by McFadden (1974). This model is based on the assumption that the unobserved factors, which determine the consumer choices, are independent and follow a Gumbel distribution, widely known as the Independence of irrelevant Alternatives (IIA) assumption. Alternate models that relax IIA assumption are the Generalized Extreme Value (GEV) models, which allow dependency between unobserved factors. However, GEV models do not incorporate all dependency patterns, other choice behaviors such as …

Spatially Dense Drip Hydrological Monitoring And Infiltration Behaviour At The Wellington Caves, South East Australia, Catherine N. Jex, Gregoire Mariethoz, Andy Baker, Peter Graham, Martin S. Andersen, Ian Acworth, Nerilee Edwards, Cecilia Azcurra

International Journal of Speleology

Despite the fact that karst regions are recognised as significant groundwater resources, the nature of groundwater flow paths in the unsaturated zone of such fractured rock is at present poorly understood. Many traditional methods for constraining groundwater flow regimes in karst aquifers are focussed on the faster drainage components and are unable to inform on the smaller fracture or matrix-flow components of the system. Caves however, offer a natural inception point to observe both the long term storage and the preferential movement of water through the unsaturated zone of such fractured carbonate rock by monitoring of drip rates of stalactites, …

Using Etf Data To Monitor Systemic Risk, Melissa A. Siemer, Brett Amidan

STAR Program Research Presentations

In 2010, President Obama signed The Dodd-Frank Wall Street Reform and Consumer Protection Act, which requires financially based government agencies and 35 major US banks to monitor systemic risk. This was in response to the recent near financial collapse due to major mistakes made by organizations generally considered "too big to fail". Systemic risk is the risk of the collapse of an entire financial system or market. It refers to the risks imposed by interdependencies in a system or market, where the failure of a single entity or cluster of entities can cause a cascading failure. In April 2011, the …

Study Of Volatility Structures In Geophysics And Finance Using Garch Models, Francis Biney

Open Access Theses & Dissertations

This work investigates the underlying volatility processes in earthquake series, explosive series, high frequency (tick) data and financial indices. Furthermore it examines the applicability of a range of GARCH specifications for modeling volatility of these series in order to identify similarities and differences in the volatility structures. The GARCH

variants considered include the basic GARCH, IGARCH, ARFIMA (0,d,0)-GARCH and FIGARCH specifications. In all the applications the methodology provides insight into features of these series volatility.

Arma-Garch Model Applied To Exchange-Traded Funds, Rebecca Davis

Open Access Theses & Dissertations

In this paper, time-varying volatility of some of the leading exchange-traded funds are studied. The ARMA mean equation with GARCH errors is used to model the series correlations and the conditional heteroscadesticity in the asset

returns. The conditional distributions of the standardized residuals are assumed to be skew-generalized error distribution. The high kurtosis and fat tail of the returns, were captured in all the data by fitting an ARMA-GARCH model with the conditional distribution of, skew-generalized error distribution.

Furthermore, the sample cross-correlations of these significant exchange-traded funds and the corresponding financial indices they mimic were computed. The empirical conclusion was …

Secondary Structure Prediction Of Long Rna Sequences Based On Inversion Excursions And A Modularized Mapreduce Framework, Daniel Tesfai Yehdego

Open Access Theses & Dissertations

Ribonucleic acid (RNA) molecules and their secondary structures play important roles in many biological processes including gene expression and regulation. The genomes of many viruses are also RNA molecules. Since secondary structures are crucial for RNA functionality, computational predictions of the RNA secondary structures have been widely studied. However, the tremendous demands on computer memory and computing time for complex secondary structures limit the capability of existing thermodynamically based algorithms for structure predictions to handling only short RNA sequences with a few hundred bases. One approach to overcome this limitation is by first cutting long RNA sequences into shorter, non-overlapping …

Analysis Of Differential Item Functioning On Selected Items Assessing Conceptual Knowledge Of Descriptive Statistics For Spanish-Speaking Ell And Non-Ell College Students, Angelica Amy Monarrez Rodriguez

Open Access Theses & Dissertations

Recently, there has been growing interest in promoting conceptual understanding of statistical concepts in the classroom. The Assessment Resource Tools for Improving Statistical Thinking (ARTIST) project is a resource for maintaining and developing scales useful for measuring statistical conceptual knowledge. The focus of this study is to investigate whether items assessing conceptual knowledge of measures of center and variation from the (ARTIST) database show evidence of differential item functioning when administered to English Language Learners (ELLs). This is pertinent topic since the population of English Language Learners (ELL) in the United States has been growing rapidly in the past few …

Generalized Linear Latent Mixed Modeling Of Functional Independent Measures And Patient Outcomes, Maduranga Kasun Dassanayake

Open Access Theses & Dissertations

The Functional Independent Measure (FIM) is one of the most widely accepted functional assessment measures used in the rehabilitation community. Past research studies have investigated the relationship between place of discharge, admission FIM scores or FIM difference scores, and patients' characteristics and found relationships between those variables. However, most of these studies fail to account for the multi-layered multidimensionality of the FIM and the measurement error associated with the FIM items. This study utilizes Generalized Linear Latent Mixed Models (GLLAMM) and Structural Equation Models (SEM) to assess which patient characteristics are associated with FIM difference scores and the structural relationship …

A Reply To David Richards’ Review Of Measuring Human Rights, Todd Landman, Edzia Carvalho

Human Rights & Human Welfare

Professor Richards highlights, in his generous review of our book Measuring Human Rights that one of the aims of the book is to bring to the forefront the importance of conceptualization before operationalization – that conceptual clarity (or lack of it) is at the heart of the problems concerning the measurement of human rights. He draws out three key issues from the book as the springboard for further discussion on measurement of the concept – a) the “Respect, Protect and Fulfill” (RPF) framework, b) the lack of reliable data sources, and c) the conceptual links between human rights, human development, …

Bayesian Inference On Mixed-Effects Models With Skewed Distributions For Hiv Longitudinal Data, Ren Chen

USF Tampa Graduate Theses and Dissertations

Statistical models have greatly improved our understanding of the pathogenesis of HIV-1 infection

and guided for the treatment of AIDS patients and evaluation of antiretroviral (ARV) therapies.

Although various statistical modeling and analysis methods have been applied for estimating the

parameters of HIV dynamics via mixed-effects models, a common assumption of distribution is

normal for random errors and random-effects. This assumption may lack the robustness against

departures from normality so may lead misleading or biased inference. Moreover, some covariates

such as CD4 cell count may be often measured with substantial errors. Bivariate clustered

(correlated) data are also commonly encountered in …

Linear Mixed-Effects Models: Applications To The Behavioral Sciences And Adolescent Community Health, Lizmarie Gabriela Maldonado

USF Tampa Graduate Theses and Dissertations

Linear mixed-effects (LME) modeling is a widely used statistical method for analyzing repeated measures or longitudinal data. Such longitudinal studies typically aim to investigate and describe the trajectory of a desired outcome. Longitudinal data have the advantage over cross-sectional data by providing more accuracy for the model. LME models allow researchers to account for random variation among individuals and between individuals.

In this project, adolescent health was chosen as a topic of research due to the many changes that occur during this crucial time period as a precursor to overall well-being in adult life. Understanding the factors that influence how …

Sieve Bootstrap Based Prediction Intervals And Unit Root Tests For Time Series, Maduka Rupasinghe

Doctoral Dissertations

"The application of the sieve bootstrap procedure, which resamples residuals obtained by fitting a finite autoregressvie (AR) approximation to empirical time series, to obtaining prediction intervals for integrated, long-memory, and seasonal time series as well as constructing a test for seasonal unit roots, is considered. The advantage of this resampling method is that it does not require knowledge about the underlying process generating a given time series and has been shown to work well for ARMA processes. We extend the application of the sieve bootstrap to ARIMA and FARIMA processes. The asymptotic properties of the sieve bootstrap prediction intervals for …

Factors Associated With Loss To Follow-Up Among Hiv-Infected Patients At An Urban, Hospital-Based Outpatient Hiv Clinic, Timothy J. Friel Md, Anthony Nerino, Lynn Nagel, J D'Aversa, Anthony Strobel, Dorothy Faulkner Phd

Department of Medicine

No abstract provided.

Using Generalized Estimating Equations To Analyze Repeated Measures Binary Data From The Young Adolescent Crowd Study, Lauren Ashley Beacham

LSU Master's Theses

The young adolescent crowd study (YACS) was conducted in order to look at the influence of various factors on use of controlled substances by middle school students. The contributing factors investigated were demographics (gender and race), self-esteem in different modalities such as school or athletic performance, and the peer group students belong to. Each student has a binary response for whether they have used alcohol, marijuana or cigarettes which was recorded in both seventh and eighth grade. Since the data has a binary repeated measures response, generalized estimating equations (GEE) in a logistic regression setting is a good way to …

On The Skewness Of Order Statistics With Applications, Subhash C. Kochar, Maochao Xu

Mathematics and Statistics Faculty Publications and Presentations

Order statistics from heterogenous samples have been extensively studied in the literature. However, most of the work focused on the effect of heterogeneity on the magnitude and dispersion of order statistics. In this paper, we study the skewness of order statistics from heterogeneous samples in the sense of star order. The main results extended the results in Kochar and Xu (2009, 2011). Examples and applications in statistical inference are highlighted.

Benchmark Results For Testing Adaptive Finite Element Eigenvalue Procedures Ii (Cluster Robust Eigenvector And Eigenvalue Estimates), Stefano Giani, Luka Grubisic, Jeffrey S. Ovall

Mathematics and Statistics Faculty Publications and Presentations

As a model benchmark problem for this study we consider a highly singular transmission type eigenvalue problem which we study in detail both analytically as well as numerically. In order to justify our claim of cluster robust and highly accurate approximation of a selected groups of eigenvalues and associated eigenfunctions, we give a new analysis of a class of direct residual eigenspace/vector approximation estimates. Unlike in the first part of the paper, we now use conforming higher order finite elements, since the canonical choice of an appropriate norm to measure eigenvector approximation by discontinuous Galerkin methods is an open problem.

Statistical Content In Middle Grades Mathematics Textbooks, Maria Consuelo (Suzie) Capiral Pickle

USF Tampa Graduate Theses and Dissertations

Statistical Content in Middle Grades Mathematics Textbooks

Maria Consuelo (Suzie) Capiral Pickle

Abstract

This study analyzed the treatment and scope of

statistical concepts in four, widely-used, contemporary, middle

grades mathematics textbook series: Glencoe Math Connects,

Prentice Hall Mathematics, Connected Mathematics Project, and

University of Chicago School Mathematics Project. There were

three phases for the data analysis. Phase 1 addressed the location

and sequence of the statistical concepts. Phase 2 focused upon an

examination of the lesson narrative, its components and scope.

Phase 3 analyzed the level of cognitive demand required of the

students to complete the exercises, and the total …

Statistical Estimation Of Physiologically-Based Pharmacokinetic Models: Identifiability, Variation, And Uncertainty With An Illustration Of Chronic Exposure To Dioxin And Dioxin-Like-Compounds., Zachary John Thompson

USF Tampa Graduate Theses and Dissertations

Assessment of human exposure to environmental chemicals is inherently subject to uncertainty and variability. There are data gaps concerning the inventory, source, duration, and intensity of exposure

as well as knowledge gaps regarding pharmacokinetics in general. These gaps result in uncertainties in exposure assessment.

The uncertainties compound further with variabilities due to population variations regarding stage of life, life style, and susceptibility,

etc. Use of physiologically-based pharmacokinetic (PBPK) models promises to reduce the uncertainties and enhance extrapolation between species, between routes, from high to low dose, and from acute to chronic exposure. However, fitting PBPK models is challenging because of …

Stochastic Modeling Of Network-Centric Epidemiological Processes, Divine Wanduku

USF Tampa Graduate Theses and Dissertations

The technological changes and educational expansion have created the heterogeneity in the human species. Clearly, this heterogeneity generates a structure in the population

dynamics, namely: citizen, permanent resident, visitor, and etc. Furthermore, as the heterogeneity in the population increases, the human mobility between meta-populations patches

also increases. Depending on spatial scales, a meta-population patch can be decomposed into sub-patches, for examples: homes, neighborhoods, towns, etc. The dynamics of human

mobility in a heterogeneous and scaled structured population is still its infancy level. We develop and investigate (1) an algorithmic two scale human mobility dynamic model for a meta-population. Moreover,the two …

Evaluation Of Repeated Biomarkers: Non-Parametric Comparison Of Areas Under The Receiver Operating Curve Between Correlated Groups Using An Optimal Weighting Scheme, Ping Xu

USF Tampa Graduate Theses and Dissertations

Receiver Operating Characteristic (ROC) curves are often used to evaluate the prognostic performance of a continuous biomarker. In a previous research, a non-parametric ROC approach was introduced to compare two biomarkers with repeated measurements. An asymptotically normal statistic, which contains the subject-specific weights, was developed to estimate the areas under the ROC curve of biomarkers. Although two weighting schemes were suggested to be optimal when the within subject correlation is 1 or 0 by the previous study, the universal optimal weight was not determined. We modify this asymptotical statistic to compare AUCs between two correlated groups and propose a solution …

Statistical Modeling And Analysis Of Breast Cancer And Pancreatic Cancer, Zahra Kottabi

USF Tampa Graduate Theses and Dissertations

Abstract

The object of the present study is to apply statistical modeling and estimate the mean of optimism of breast cancer patients as function of attribute variables; delay, education and age for each race of breast cancer patients. Moreover, to investigate the nonlinear association between optimism, education, age and delay with respect to each race and both. Furthermore, to develop differential equations that will characterize the behavior of the pancreatic cancer tumor size as a function of time. Having such differential equations, the mean solution of which once plotted will identify the rate of change of tumor size as a …

Multi-Time Scales Stochastic Dynamic Processes: Modeling, Methods, Algorithms, Analysis, And Applications, Jean-Claude Pedjeu

USF Tampa Graduate Theses and Dissertations

By introducing a concept of dynamic process operating under multi-time scales in sciences and engineering, a mathematical model is formulated and it leads to a system of multi-time scale stochastic differential equations. The classical Picard-Lindel\"{o}f successive approximations scheme is expended to the model validation problem, namely, existence and uniqueness of solution process. Naturally, this generates to a problem of finding closed form solutions of both linear and nonlinear multi-time scale stochastic differential equations. To illustrate the scope of ideas and presented results, multi-time scale stochastic models for ecological and epidemiological processes in population dynamic are exhibited. Without loss in generality, …