Statistics and Probability Commons^™

The Psychological Impacts Of False Positive Ovarian Cancer Screening: Assessment Via Mixed And Trajectory Modeling, Amanda T. Wiggins

Theses and Dissertations--Epidemiology and Biostatistics

Ovarian cancer (OC) is the fifth most common cancer among women and has the highest mortality of any cancer of the female reproductive system. The majority (61%) of OC cases are diagnosed at a distant stage. Because diagnoses occur most commonly at a late-stage and prognosis for advanced disease is poor, research focusing on the development of effective OC screening methods to facilitate early detection in high-risk, asymptomatic women is fundamental in reducing OC-specific mortality. Presently, there is no screening modality proven efficacious in reducing OC-mortality. However, transvaginal ultrasonography (TVS) has shown value in early detection of OC. TVS presents …

New Microarray Image Segmentation Using Segmentation Based Contours Method, Yuan Cheng

Doctoral Dissertations

The goal of the research developed in this dissertation is to develop a more accurate segmentation method for Affymetrix microarray images. The Affymetrix microarray biotechnologies have become increasingly important in the biomedical research field. Affymetrix microarray images are widely used in disease diagnostics and disease control. They are capable of monitoring the expression levels of thousands of genes simultaneously. Hence, scientists can get a deep understanding on genomic regulation, interaction and expression by using such tools.

We also introduce a novel Affymetrix microarray image simulation model and how the Affymetrix microarray image is simulated by using this model. This simulation …

The Impact Of Local Patent Rules On Rate And Timing Of Case Resolution Relative To Claim Construction: An Empirical Study Of The Past Decade, Pauline M. Pelletier

Journal of Business & Technology Law

No abstract provided.

Numerical Solutions To The Gross-Pitaevskii Equation For Bose-Einstein Condensates, Luigi Galati

College of Graduate Studies: Theses & Dissertations

In this thesis we compare various potential operators for the two-dimensional (2D) Gross-Pitaevskii equation (GPE) for Bose-Einstein condensates. Both the 2D and the 1D models are scaled to get a three parameter model. Smoothness of initial conditions is considered and choice of method (Split-Step Fourier method with Strang Splitting) is justied. Numerical simulations provide graphical evidence of properties of both focusing and nonfocusing cases.

Nfl Betting Market: Using Adjusted Statistics To Test Market Efficiency And Build A Betting Model, James P. Donnelly

CMC Senior Theses

The use of statistical analysis has been prevalent in the sports gambling industry for years. More recently, we have seen the emergence of "adjusted statistics", a more sophisticated way to examine each play and each result (further explanation below). And while adjusted statistics have become commonplace for professional and recreational bettors alike, little research has been done to justify their use. In this paper the effectiveness of this data is tested on the most heavily wagered sport in the world – the National Football League (NFL). The results are studied with two central questions in mind: Does the market account …

Why Police Learn From Third-Party Data, Randall K. Johnson

Faculty Works

This essay argues that third-party data collection, particularly of administrative complaints and departmental audit information, holds greater promise than lawsuit data collection. It does so by asserting that third-party data collection is more useful for three reasons. First, third-party data collection prevents manipulation by individual police officers and law enforcement agencies. Second, it assures that police behavioral trends are actually identified. Lastly, third-party data collection helps to deter published § 1983 cases. The essay, however, only models and tests the final claim.

Connecting Big Data With Big Decisions: Ideas For Synthesizing Analytics And Decision Analysis, Jeffrey Keisler

Management Science and Information Systems Faculty Publication Series

This paper describes an approach to connect decision analysis models with outputs of analytic methods applied to various types of big data. Decision analysis models focus on issues of concern to a decision maker and incorporate use of a range of methods and axioms to develop insights about what the decision maker should do. In particular, decision analysis models typically use subjective judgments from the decision maker to describe beliefs about the likelihood of events and the desirability of outcomes. In order for human judgments to be improved by the availability of large amounts of data and processing power, it …

The Spectral Analysis Of Longitudinal Data With Applications To Atmospheric Variables, Amy Potrzeba Macrina

Legacy Theses & Dissertations (2009 - 2024)

Longitudinal data analysis is an observational study that analyzes data that has been collected over long periods of time where time can be arbitrary. It is a popular method that has been widely used over the time domain approach. An equivalent method to the time domain approach is the frequency domain approach. This method allows researchers to observe the spectral properties of the data. In the world everything exists in continuous time t, but we made observations of a given variable at some specific times. Currently spectral analysis is well developed for time series when observations are made at equal …

Raman Spectroscopy For The Identification Of Body Fluid Traces : Mixtures And Contaminations, Race And Gender Differentation, Aliaksandra Sikirzhytskaya

Legacy Theses & Dissertations (2009 - 2024)

Body fluid traces are an important type of forensic evidence, which play a significant role in the reconstruction of a violent crime and often help to identify a victim or suspect based on DNA analysis. Despite a great need, there is no a single method, which could identify multiple body fluids. In addition, majority of current methods are destructive for the evidence. For about eight years, our laboratory has been working on the development of a new nondestructive method for identification of body fluid traces based on Raman microspectroscopy combined with advanced statistics. High differentiation power of the method has …

Non-Likelihood Based Model Evaluation And Comparison With Application To Genetic And Clinical Hiv-1 Outcomes, Ashley Elise Giambrone

Legacy Theses & Dissertations (2009 - 2024)

Although treatment for human immunodeficiency virus type-1 (HIV-1) has undergone drastic change and morbidity and mortality has decreased over time, the development of drug-resistant HIV-1 is of concern for the long-term antiretroviral treatment of infected individuals. Drug-resistant virus is known to manifest with potentially complex mutational patterns in the HIV-1 genotype sequence and is associated with decreased response to therapy. Resistance occurs either as a result of development of mutations in the viral genome under selective drug pressure or as a result of naturally occurring polymorphisms. The most effective treatment methods are still debated at this time; however, current treatment …

Augmenting Program Data With Secondary Data Sources To Improve The Quality Of Existing Statistics : Four Examples From The New York State Department Of Health Hospital-Acquired Infection Reporting Program, Valerie Benson Haley

Legacy Theses & Dissertations (2009 - 2024)

The objective of this dissertation is to illustrate the novel application of methods that can be used to improve the accuracy of hospital-acquired infection (HAI) rates. Public reporting of HAI rates is relatively new. New York was one of the first states to mandate reporting in acute care hospitals (2007), followed by national pay-for-reporting in 2011, and national value-based purchasing in 2013. Given the financial ramifications of public reporting, it is critical that the data are validated and adjusted for differences in underlying risk among patient populations so that hospital performance can be fairly compared. However, limited information on the …

Flexible Variable And Model Selection With Ordinal Categorical Responses And Multiple Covariates, Wan-Hsiang Hsu

Legacy Theses & Dissertations (2009 - 2024)

Ordered categorical responses are common in many applied studies; moreover, with the rapid growth of computational power and technologies, ultrahigh dimensional data becomes very widespread. For example, there could be ten thousands of dimensions in a gene expression data and of interest is to classify the disease stage with specific genes and predict a clinical prognosis by using these specific genes. However, there are some unique challenges, including (1) the curse of dimensionality and (2) the modeling strategy for allowing dynamic covariate effects. Thus, variable selection for mining ultrahigh dimensional data and flexible modeling strategy for allowing dynamic covariate effects …

Data Mining And Pattern Discovery Using Exploratory And Visualization Methods For Large Multidimensional Datasets, Hsin-Fang Li

Theses and Dissertations--Epidemiology and Biostatistics

Oral health problems have been a major public health concern profoundly affecting people’s general health and quality of life. Given that oral health data is composed of several measurable dimensions including clinical measurements, socio-behavioral factors, genetic predispositions, self-reported assessments, and quality of life measures, strategies for analyzing multidimensional data are neither computationally straightforward nor efficient. Researchers face major challenges to identify tools that circumvent the processes of manually probing the data.

The purpose of this dissertation is to provide applications of the proposed methodology on oral health-related data that go beyond identifying risk factors from a single dimension, and to …

Quantifying The Risks Of Soil Lead In Urban Community Gardens: Sampling To Account For Spatial Variability, Lauren Elizabeth-Korgol Bugdalski

Wayne State University Theses

Urban gardening has recently gained popularity as a way to provide fresh produce and income to urban residents; however, finding suitable sites for urban gardens is challenging because of historical soil lead contamination particularly in post- industrial cities like Detroit, Michigan. Soil lead measurements from three Detroit gardens were modeled using geostatistical techniques to assess risk and alternate sampling strategies. General sampling recommendations for urban gardens were developed based on results of Monte Carlo simulations and associated risk assessment. Variograms and kriged concentration maps indicate spatial variability at scales as small as one meter, with site specific variability in spatial …

Student Fact Book, Fall 2013, Thirty-Seventh Annual Edition, Wright State University, Office Of Student Information Systems, Wright State University

Wright State University Student Fact Books

The student fact book has general demographic information on all students enrolled at Wright State University for Fall Semester, 2013.

Analysis Of Spatial Data, Xiang Zhang

Theses and Dissertations--Statistics

In many areas of the agriculture, biological, physical and social sciences, spatial lattice data are becoming increasingly common. In addition, a large amount of lattice data shows not only visible spatial pattern but also temporal pattern (see, Zhu et al. 2005). An interesting problem is to develop a model to systematically model the relationship between the response variable and possible explanatory variable, while accounting for space and time effect simultaneously.

Spatial-temporal linear model and the corresponding likelihood-based statistical inference are important tools for the analysis of spatial-temporal lattice data. We propose a general asymptotic framework for spatial-temporal linear models and …

James-Stein Type Compound Estimation Of Multiple Mean Response Functions And Their Derivatives, Limin Feng

Theses and Dissertations--Statistics

Charnigo and Srinivasan originally developed compound estimators to nonparametrically estimate mean response functions and their derivatives simultaneously when there is one response variable and one covariate. The compound estimator maintains self consistency and almost optimal convergence rate. This dissertation studies, in part, compound estimation with multiple responses and/or covariates. An empirical comparison of compound estimation, local regression and spline smoothing is included, and near optimal convergence rates are established in the presence of multiple covariates.

James and Stein proposed an estimator of the mean vector of a p dimensional multivariate normal distribution, which produces a smaller risk than the maximum …

An Implicit Interface Boundary Integral Method For Poisson’S Equation On Arbitrary Domains, Catherine Kublik, Nicolay M. Tanushev, Richard Tsai

Mathematics Faculty Publications

We propose a simple formulation for constructing boundary integral methods to solve Poisson’s equation on domains with smooth boundaries defined through their signed distance function. Our formulation is based on averaging a family of parameterizations of an integral equation defined on the boundary of the domain, where the integrations are carried out in the level set framework using an appropriate Jacobian. By the coarea formula, the algorithm operates in the Euclidean space and does not require any explicit parameterization of the boundaries. We present numerical results in two and three dimensions.

Models And Software Development For Interval-Censored Data, Chun Pan

Theses and Dissertations

Interval-censored time-to-event data occur naturally in studies of diseases where the symptoms are not directly observable, and periodic clinical examinations are required for detection. Due to the lack of well-established procedures, interval-censored data have been conventionally treated as right-censored data, however, this introduces bias at the first place. This dissertation focuses on methodological research and software development for interval-censored data. Specifically, it consists of three projects. The first project is to create an R package for regression analysis and survival curve estimation of interval-censored data based on several published papers by our research team. In the second project, a Bayesian …

The Complete Plus-Minus: A Case Study Of The Columbus Blue Jackets, Nathan Spagnola

Theses and Dissertations

A new hockey statistic termed the Complete Plus-Minus (CPM) was created to calculate the abilities of hockey players in the National Hockey League (NHL). This new statistic was used to analyze the Columbus Blue Jackets for the 2011-2012 season. The CPM for the Blue Jackets was created using two logistic regressions that modeled a goal being scored for and against the Blue Jackets. Whether a goal was scored for or against the team were the responses, while events on the ice were the predictors in the model. It was found that the team's poor performance was due to a weak …