Statistics and Probability Commons^™

Inference Of Heterogeneity In Meta-Analysis Of Rare Binary Events And Rss-Structured Cluster Randomized Studies, Chiyu Zhang

Statistical Science Theses and Dissertations

This dissertation contains two topics: (1) A Comparative Study of Statistical Methods for Quantifying and Testing Between-study Heterogeneity in Meta-analysis with Focus on Rare Binary Events; (2) Estimation of Variances in Cluster Randomized Designs Using Ranked Set Sampling.

Meta-analysis, the statistical procedure for combining results from multiple studies, has been widely used in medical research to evaluate intervention efficacy and safety. In many practical situations, the variation of treatment effects among the collected studies, often measured by the heterogeneity parameter, may exist and can greatly affect the inference about effect sizes. Comparative studies have been done for only one or …

Fractional Random Weighted Bootstrapping For Classification On Imbalanced Data With Ensemble Decision Tree Methods, Sean Charles Carter

USF Tampa Graduate Theses and Dissertations

Ensemble methods are commonly used for building predictive models for classification. Models that are unstable to perturbations in the training set, such as the decision tree, often see considerable reductions in error when grouped, using bootstrapped resamples of the training data to train many models. The non-parametric bootstrap, however, has limited efficacy when used on severely imbalanced data, especially when the number of observations of one or more classes is exceptionally small. We explore the fractional random weighted bootstrap, which randomly assigns fractional weights to observations, as an alternative resampling pro cedure in training machine learning ensembles, particularly decision tree …

9th Annual Postdoctoral Science Symposium, University Of Texas Md Anderson Cancer Center Postdoctoral Association

Annual Postdoctoral Science Symposium Abstracts

The mission of the Annual Postdoctoral Science Symposium (APSS) is to provide a platform for talented postdoctoral fellows throughout the Texas Medical Center to present their work to a wider audience. The MD Anderson Postdoctoral Association convened its inaugural Annual Postdoctoral Science Symposium (APSS) on August 4, 2011.

The APSS provides a professional venue for postdoctoral scientists to develop, clarify, and refine their research as a result of formal reviews and critiques of faculty and other postdoctoral scientists. Additionally, attendees discuss current research on a broad range of subjects while promoting academic interactions and enrichment and developing new collaborations.

Sample Size Requirements And Considerations For Models To Assess Human-Machine System Performance, Jennifer S. G. Lopez

Theses and Dissertations

Hierarchical Linear Models (HLMs), also known as multi-level models, are an extension of multiple regression analysis and can aid in the understanding of human and machine workloads of a system. These models allow for prediction and testing in systems with hierarchies of two or more levels. The complex interrelated variability of these multi-level models exists in operational settings, such as the Air Force Distributed Common Ground System Full Motion Video (AF DCGS FMV) community which is composed of individuals (Level-1), groups (Level-2), units (Level-3), and organizations (Level-4). Through the development of sample size requirements and considerations for multi-level models, this …

Who Can Act? Critical Assumptions At The Foundations Of Statistical Analysis, Peter J. Taylor

Working Papers on Science in a Changing World

Thinking about a simple teaching example on the t-test for comparing the average (mean) for some measurement in a group versus the average in another led me to articulate a sequence of thoughts and questions about the foundations of statistical analysis. In particular, my inquiry explores contrasts between: the statistical emphasis on averages or types around which there is variation or noise; variation as a mixture of types; the dynamics (or heterogeneous mix of dynamics) that generated the data analyzed; and participatory restructuring of these dynamics in the future. Two key issues are: Who is assumed to be able to …

Sample Size Calculation Of Clinical Trials With Correlated Outcomes, Dateng Li

Statistical Science Theses and Dissertations

In this thesis, we investigate sample size calculation for three kinds of clinical trials: (1). Randomized controlled trials (RCTs) with longitudinal count outcomes; (2). Cluster randomized trials (CRTs) with count outcomes; (3). CRTs with multiple binary co-primary endpoints.

Is Corequisite Developmental Math Effective At East Tennessee State University?, Christine Padden

Electronic Theses and Dissertations

This thesis looks at the corequisite developmental math program at East Tennessee State University (ETSU) and compares the effectiveness to the previous developmental math program by comparing the student outcomes in MATH 1530. MATH 1530 is a non-calculus based statistic and probability course that satisfies most majors’ general education math requirements. ETSU sees approximately 1,000 students a year pass through MATH 1530 which is around 6.7% of the total enrollment at ETSU[9]. We are interested in the last five years of the developmental math program before it was changed to corequisite developmental math and the first five years of corequisite …

Spatio-Temporal Analysis Of Tree Ring Chronology And Precipitation, Ruizhe Yin

Graduate Theses and Dissertations

Tree ring chronology data is known to reflect regional climate due to the strong impact of rainfall and temperature. Therefore, tree ring data can be used to reconstruct historical climate in order to understand how climate changed in the past and make prediction about the future behavior of the climate. For simplicity, this research only considers the influence of precipitation on tree ring growth within the New England area. A total of 94 measurement sites are used to record tree ring width over 881 years and corresponding precipitation data are given at some locations for 121 years. We developed a …

Effect Of Cross-Validation On The Output Of Multiple Testing Procedures, Josh Dallas Price

Graduate Theses and Dissertations

High dimensional data with sparsity is routinely observed in many scientific disciplines. Filtering out the signals embedded in noise is a canonical problem in such situations requiring multiple testing. The Benjamini--Hochberg procedure using False Discovery Rate control is the gold standard in large scale multiple testing. In Majumder et al. (2009) an internally cross-validated form of the procedure is used to avoid a costly replicate study and the complications that arise from population selection in such studies (i.e. extraneous variables). I implement this procedure and run extensive simulation studies under increasing levels of dependence among parameters and different data generating …

Mathematics Versus Statistics, Mindy B. Capaldi

Journal of Humanistic Mathematics

Mathematics and statistics are both important and useful subjects, but the former has maintained prominence in the American education system. On the other hand, statistics is more prevalent in daily life and is an increasingly marketable subject to know. This article gives a personal history of one mathematician’s bumpy road to learning and teaching statistics. Additionally, arguments for how and why to include statistics in the K-12 and college curricula are provided.

Estimation Of Association Between A Longitudinal Marker And Interval-Censored Progression Times, Naghmeh Daneshi

Dissertations and Theses

In longitudinal studies, we observe the subjects who are likely to progress to a new state during the study time. For example, in clinical trials the stage of a progressing disease is recorded at each follow-up visit. The primary goal is to estimate the relationship between the attributes and the subject's progression state. In such studies, some subjects complete all their follow-up visits and their progression state are observed without any missingness. However, others miss their follow-up visits and when they come back, they learn that they have progressed to a new state. In this case, not only are their …

Differentially Expressed Genes In Blood From Young Pigs Between Two Swine Lines Divergently Selected For Feed Efficiency: Potential Biomarkers For Improving Feed Efficiency, Haibo Liu, Yet T. Nguyen, Daniel S. Nettleton, Jack C. M. Dekkers, Christopher K. Tuggle

Dan Nettleton

The goal of this study was to find potential gene expression biomarkers in blood of piglets that can be used to predict pigs’ future feed efficiency. Using RNA-seq technology, we found 453 genes were differentially expressed (false discovery rate (FDR) ≤ 0.05) in the blood of two Yorkshire lines of pigs divergently selected for feed efficiency (FE) based on residual feed intake (RFI). Genes involved in several biosynthetic processes were overrepresented among genes more highly expressed in the low RFI line compared to the high RFI line. Weighted gene co-expression network analysis (WGCNA) also revealed genes involved in some of …

Advances In Measurement Error Modeling, Linh Nghiem

Statistical Science Theses and Dissertations

Measurement error in observations is widely known to cause bias and a loss of power when fitting statistical models, particularly when studying distribution shape or the relationship between an outcome and a variable of interest. Most existing correction methods in the literature require strong assumptions about the distribution of the measurement error, or rely on ancillary data which is not always available. This limits the applicability of these methods in many situations. Furthermore, new correction approaches are also needed for high-dimensional settings, where the presence of measurement error in the covariates adds another level of complexity to the desirable structure …

Samples, Unite! Understanding The Effects Of Matching Errors On Estimation Of Total When Combining Data Sources, Benjamin Williams

Statistical Science Theses and Dissertations

Much recent research has focused on methods for combining a probability sample with a non-probability sample to improve estimation by making use of information from both sources. If units exist in both samples, it becomes necessary to link the information from the two samples for these units. Record linkage is a technique to link records from two lists that refer to the same unit but lack a unique identifier across both lists. Record linkage assigns a probability to each potential pair of records from the lists so that principled matching decisions can be made. Because record linkage is a probabilistic …

Market Research On Student Concert Attendance At Bgsu's College Of Musical Arts, Mary Solomon

Honors Projects

Bowling Green State University boasts a well established College of Musical Arts which holds concerts performed by esteemed faculty, prestigious guest artists, and students. The school hosts these events in Kobacker Hall and Bryan Recital Hall which can accommodate up to 800 and 250 audience members, respectively. However, performances in Kobacker hall only fill one- fourth of the 800 seats, on average. Why is this so? This project aims to investigate the factors that influence students’ decisions to attend concerts at the College of Musical Arts (CMA). By methodology of survey research and statistical analysis, this project will look into …

Bias Reduction In Machine Learning Classifiers For Spatiotemporal Analysis Of Coral Reefs Using Remote Sensing Images, Justin J. Gapper

Computational and Data Sciences (PhD) Dissertations

This dissertation is an evaluation of the generalization characteristics of machine learning classifiers as applied to the detection of coral reefs using remote sensing images. Three scientific studies have been conducted as part of this research: 1) Evaluation of Spatial Generalization Characteristics of a Robust Classifier as Applied to Coral Reef Habitats in Remote Islands of the Pacific Ocean 2) Coral Reef Change Detection in Remote Pacific Islands using Support Vector Machine Classifiers 3) A Generalized Machine Learning Classifier for Spatiotemporal Analysis of Coral Reefs in the Red Sea. The aim of this dissertation is to propose and evaluate a …

The Reproducibility Crisis In Scientific Research, Sarah Eline

Senior Honors Projects, 2010-2019

Following the push for evidence based practice, came a huge proliferation of research journals and journal articles. With this increase in quantity came an increased concern about the quality of these articles being published, which led to a multifield investigation regarding the reproducibility of scientific research. With studies in the fields of psychology and biomedicine only reaching approximately a 30% reproducibility rate, a conversation has been sparked that spans across every field of research. Upon further investigation, various causes for this reproducibility crisis have surfaced which include, lack of data sharing/ transparency, statistical errors, funding corruption, and the culture surrounding …

Advanced Statistics In Arkansas Sports Reporting, Andrew Lee Epperson

Graduate Theses and Dissertations

This study seeks to analyze how Arkansas’ sports journalists are adapting to the recent surge in available advanced statistics that are being used by certain national news organizations. Using in-depth qualitative research that includes in-depth interviews with a number of individuals in the print, broadcast, and athletics side of sports coverage, we discover how journalists and coaches use these next-generation analytics, what they fundamentally mean for the evolution of each respective path, and why so few Arkansas reporters and writers use them at the time of this paper’s defense. We see how budgets and deadlines restrict the use of these …

A Self-Contained Course In The Mathematical Theory Of Statistics For Scientists & Engineers With An Emphasis On Predictive Regression Modeling & Financial Applications., Tim Smith

Timothy Smith

Preface & Acknowledgments

This textbook is designed for a higher level undergraduate, perhaps even first year graduate, course for engineering or science students who are interested to gain knowledge of using data analysis to make predictive models. While there is no statistical perquisite knowledge required to read this book, due to the fact that the study is designed for the reader to truly understand the underlying theory rather than just learn how to read computer output, it would be best read with some familiarity of elementary statistics. The book is self-contained and the only true perquisite knowledge is a solid …

Daily And Seasonal Variability Of Offshore Wind Power On The Central California Coast And Statewide Demand, Matthew Douglas Kehrli

Physics

No abstract provided.

The Evolution Of Data Science: A New Mode Of Knowledge Production, Jennifer Lewis Priestley, Robert J. Mcgrath

Faculty and Research Publications

Is data science a new field of study or simply an extension or specialization of a discipline that already exists, such as statistics, computer science, or mathematics? This article explores the evolution of data science as a potentially new academic discipline, which has evolved as a function of new problem sets that established disciplines have been ill-prepared to address. The authors find that this newly-evolved discipline can be viewed through the lens of a new mode of knowledge production and is characterized by transdisciplinarity collaboration with the private sector and increased accountability. Lessons from this evolution can inform knowledge production …

Sensitivity Analyses For Tumor Growth Models, Ruchini Dilinika Mendis

Masters Theses & Specialist Projects

This study consists of the sensitivity analysis for two previously developed tumor growth models: Gompertz model and quotient model. The two models are considered in both continuous and discrete time. In continuous time, model parameters are estimated using least-square method, while in discrete time, the partial-sum method is used. Moreover, frequentist and Bayesian methods are used to construct confidence intervals and credible intervals for the model parameters. We apply the Markov Chain Monte Carlo (MCMC) techniques with the Random Walk Metropolis algorithm with Non-informative Prior and the Delayed Rejection Adoptive Metropolis (DRAM) algorithm to construct parameters' posterior distributions and then …

A Self-Contained Course In The Mathematical Theory Of Statistics For Scientists & Engineers With An Emphasis On Predictive Regression Modeling & Financial Applications., Tim Smith

Open Access Textbooks

Preface & Acknowledgments

This textbook is designed for a higher level undergraduate, perhaps even first year graduate, course for engineering or science students who are interested to gain knowledge of using data analysis to make predictive models. While there is no statistical perquisite knowledge required to read this book, due to the fact that the study is designed for the reader to truly understand the underlying theory rather than just learn how to read computer output, it would be best read with some familiarity of elementary statistics. The book is self-contained and the only true perquisite knowledge is a solid …

Reporting Number Needed To Treat In Clinical Trials Published In Physical Therapy Specific Literature 1989 - 2018, Susan Ann Talley

Wayne State University Dissertations

Evidence-based practice requires physical therapists to make clinical decisions about the best intervention to use when providing services to patients/clients. Although null hypothesis significance testing (NHST) is frequently used to interpret the outcome of a clinical trial investigating the comparative effectiveness of an intervention, statistical significance does not directly translate into clinical importance. Number needed to treat (NNT) is a measure of effect size (ES) that may be particularly useful when translating the results from clinical trials to PT clinical practice. The purpose of this study was to conduct a bibliometric content analysis of the methods of reporting research results …

Comparative Analysis Of Students’ Performance Between Online And On Campus In An Introductory Statistics Course, Kendal Mcdonald

The Corinthian

In this research, we compare students’ performance in an online and on-campus introductory statistics and probability course at Georgia College. MyStatLab is the learning management system used in both the online and on-campus courses for homework and quizzes. The online data is produced by five summer courses between Summer 2014 to Summer 2017 and the on-campus data is produced from nine on-campus courses from Spring 2014, Spring 2016, and Spring 2017. For homework, the research compares the scores made between online and on-campus. For quizzes, we test if there is a difference between the scores and the number of attempts …

Estimation And Variable Selection In High-Dimensional Settings With Mismeasured Observations, Michael Byrd

Statistical Science Theses and Dissertations

Understanding high-dimensional data has become essential for practitioners across many disciplines. The general increase in ability to collect large amounts of data has prompted statistical methods to adapt for the rising number of possible relationships to be uncovered. The key to this adaptation has been the notion of sparse models, or, rather, models where most relationships between variables are assumed to be negligible at best. Driving these sparse models have been constraints on the solution set, yielding regularization penalties imposed on the optimization procedure. While these penalties have found great success, they are typically formulated with strong assumptions on the …

Modeling Stochastically Intransitive Relationships In Paired Comparison Data, Ryan Patrick Alexander Mcshane

Statistical Science Theses and Dissertations

If the Warriors beat the Rockets and the Rockets beat the Spurs, does that mean that the Warriors are better than the Spurs? Sophisticated fans would argue that the Warriors are better by the transitive property, but could Spurs fans make a legitimate argument that their team is better despite this chain of evidence?

We first explore the nature of intransitive (rock-scissors-paper) relationships with a graph theoretic approach to the method of paired comparisons framework popularized by Kendall and Smith (1940). Then, we focus on the setting where all pairs of items, teams, players, or objects have been compared to …

Cramer Type Moderate Deviations For Random Fields And Mutual Information Estimation For Mixed-Pair Random Variables, Aleksandr Beknazaryan

Electronic Theses and Dissertations

In this dissertation we first study Cramer type moderate deviation for partial sums of random fields by applying the conjugate method. In 1938 Cramer published his results on large deviations of sums of i.i.d. random variables after which a lot of research has been done on establishing Cramer type moderate and large deviation theorems for different types of random variables and for various statistics. In particular results have been obtained for independent non-identically distributed random variables for the sum of independent random to estimate the mutual information between two random variables. The estimates enjoy a central limit theorem under some …

Bayesian Hierarchical Meta-Analysis Of Asymptomatic Ebola Seroprevalence, Peter Brody-Moore

CMC Senior Theses

The continued study of asymptomatic Ebolavirus infection is necessary to develop a more complete understanding of Ebola transmission dynamics. This paper conducts a meta-analysis of eight studies that measure seroprevalence (the number of subjects that test positive for anti-Ebolavirus antibodies in their blood) in subjects with household exposure or known case-contact with Ebola, but that have shown no symptoms. In our two random effects Bayesian hierarchical models, we find estimated seroprevalences of 8.76% and 9.72%, significantly higher than the 3.3% found by a previous meta-analysis of these eight studies. We also produce a variation of this meta-analysis where we exclude …