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Evaluation Of Repeated Biomarkers: Non-Parametric Comparison Of Areas Under The Receiver Operating Curve Between Correlated Groups Using An Optimal Weighting Scheme, Ping Xu 2012 University of South Florida

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 2012 University of South Florida

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 2012 University of South Florida

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, …


Stochastic Hybrid Dynamic Systems: Modeling, Estimation And Simulation, Daniel Siu 2012 University of South Florida

Stochastic Hybrid Dynamic Systems: Modeling, Estimation And Simulation, Daniel Siu

USF Tampa Graduate Theses and Dissertations

Stochastic hybrid dynamic systems that incorporate both continuous and discrete dynamics have been an area of great interest over the recent years. In view of applications, stochastic hybrid dynamic systems have been employed to diverse fields of studies, such as communication networks, air traffic management, and insurance risk models. The aim of the present study is to investigate properties of some classes of stochastic hybrid dynamic systems.

The class of stochastic hybrid dynamic systems investigated has random jumps driven by a non-homogeneous Poisson process and deterministic jumps triggered by hitting the boundary. Its real-valued continuous dynamic between jumps is described …


Probability Of Identification: A Statistical Model For The Validation Of Qualitative Botanical Identification Methods, Robert A. LaBudde, James M. Harnly 2012 Old Dominion University

Probability Of Identification: A Statistical Model For The Validation Of Qualitative Botanical Identification Methods, Robert A. Labudde, James M. Harnly

Mathematics & Statistics Faculty Publications

A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive nontarget (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of …


The Dependent Samples T And Wilcoxon Sign Rank Maximum Test, Saverpierre Maggio 2012 Wayne State University

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 2012 Loyola Marymount University

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 …


Arma-Garch Model Applied To Exchange-Traded Funds, Rebecca Davis 2012 University of Texas at El Paso

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 2012 University of Texas at El Paso

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 2012 University of Texas at El Paso

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 2012 University of Texas at El Paso

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 2012 University of Denver

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 2012 University of South Florida

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 2012 University of South Florida

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 …


A Quality Improvement Initiative Using A Novel Travel Survey To Define High-Risk International Travel And Promote Patient-Centered Counseling, Craig A. Mackaness DO, Mark Knouse MD, Suzanne J. Templer DO, Deepti Verma MD, Allison Osborne BA, Michael J. Weiss MPH 2012 Lehigh Valley Health Network

A Quality Improvement Initiative Using A Novel Travel Survey To Define High-Risk International Travel And Promote Patient-Centered Counseling, Craig A. Mackaness Do, Mark Knouse Md, Suzanne J. Templer Do, Deepti Verma Md, Allison Osborne Ba, Michael J. Weiss Mph

Department of Medicine

No abstract provided.


Abel Dynamic Equations Of The First And Second Kind, Sabrina Heike Streipert 2012 Missouri University of Science and Technology

Abel Dynamic Equations Of The First And Second Kind, Sabrina Heike Streipert

Masters Theses

"In this work, we study Abel dynamic equations of the first and the second kind. After a brief introduction to time scales, we introduce the Abel differential equations of the first and the second kind, as well as the canonical Abel form in the continuous case. Using the existing information, we derive novel results for time scales. We provide formulas for the Abel dynamic equations of the second kind and present a solution method. We furthermore achieve a special class of Abel equations of the first kind and discuss the canonical Abel equation. We get relations between common dynamic equations …


Equivalent Circuit Model Of Coaxial Probes For Patch Antennas, Y. S. Hu, Yanzhi Zhang, Jun Fan 2012 Missouri University of Science and Technology

Equivalent Circuit Model Of Coaxial Probes For Patch Antennas, Y. S. Hu, Yanzhi Zhang, Jun Fan

Mathematics and Statistics Faculty Research & Creative Works

An equivalent circuit model of coaxial probes is derived directly from the intrinsic via circuit model. as all the higher-order evanescent modes have been included analytically in the parasitic circuit elements, only the propagating mode needs to be considered by the simplest uniform-current model of a coaxial probe in numerical solvers such as -nite element method (FEM) or -nite divergence time domain (FDTD). This avoids dense meshes or sub-gridding techniques and greatly reduces the computational efforts for accurate calculation of the probe input impedance. the derived equivalent circuit model and the new feeding technique have been validated by both analytical …


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 2012 Water Research Centre and Connected Waters Initiative Research Centre, University of New South Wales, Sydney. Affiliated to the National Centre for Groundwater Research and Training (NCGRT), Australia

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, …


Sieve Bootstrap Based Prediction Intervals And Unit Root Tests For Time Series, Maduka Rupasinghe 2012 Missouri University of Science and Technology

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 …


The Cumulative Impact Of Unemployment On Risks Of Acute Myocardial Infarction, Guangya Liu, Matthew E. Dupree, Linda K. George, Eric D. Peterson 2012 Duke Law School

The Cumulative Impact Of Unemployment On Risks Of Acute Myocardial Infarction, Guangya Liu, Matthew E. Dupree, Linda K. George, Eric D. Peterson

Faculty Scholarship

Background: Employment instability is a major source of strain affecting an increasing number of adults in the United States. Little is known about the cumulative effect of multiple job losses and unemployment on the risks for acute myocardial infarction (AMI).

Methods: We investigated the associations between different dimensions of unemployment and the risks for AMI in US adults in a prospective cohort study of adults (N=13 451) aged 51 to 75 years in the Health and Retirement Study with biennial follow-up interviews from 1992 to 2010. Unadjusted rates of age-specific AMI were used to demonstrate observed differences by employment status, …


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