Statistics and Probability Commons^™

Systematic Review And Meta-Analysis: Tuberculosis, Tnfα Inhibitors, And Crohn's Disease, Brent L. Cao

Honors Undergraduate Theses

Inflammation is often a protective reaction against harmful foreign agents. However, in many disease conditions, the mechanisms behind the inflammatory response are poorly understood. Often times, the inflammation causes adverse effects, such as joint pain, abdominal pain, fever, fatigue, and loss of appetite. Thus, many treatments aim to inhibit the inflammatory response in order to control adverse symptoms. Such treatments include TNFα inhibitors. However, a major risk associated with drugs inhibiting tumor necrosis factor alpha (TNFα) is serious infection, including tuberculosis (TB).

Anti-TNFα therapy is used to treat patients with Crohn’s disease, for which the risk of tuberculosis may be …

High Dimensional Multivariate Inference Under General Conditions, Xiaoli Kong

Theses and Dissertations--Statistics

In this dissertation, we investigate four distinct and interrelated problems for high-dimensional inference of mean vectors in multi-groups.

The first problem concerned is the profile analysis of high dimensional repeated measures. We introduce new test statistics and derive its asymptotic distribution under normality for equal as well as unequal covariance cases. Our derivations of the asymptotic distributions mimic that of Central Limit Theorem with some important peculiarities addressed with sufficient rigor. We also derive consistent and unbiased estimators of the asymptotic variances for equal and unequal covariance cases respectively.

The second problem considered is the accurate inference for high-dimensional repeated …

The Family Of Conditional Penalized Methods With Their Application In Sufficient Variable Selection, Jin Xie

Theses and Dissertations--Statistics

When scientists know in advance that some features (variables) are important in modeling a data, then these important features should be kept in the model. How can we utilize this prior information to effectively find other important features? This dissertation is to provide a solution, using such prior information. We propose the Conditional Adaptive Lasso (CAL) estimates to exploit this knowledge. By choosing a meaningful conditioning set, namely the prior information, CAL shows better performance in both variable selection and model estimation. We also propose Sufficient Conditional Adaptive Lasso Variable Screening (SCAL-VS) and Conditioning Set Sufficient Conditional Adaptive Lasso Variable …

Comparing Various Machine Learning Statistical Methods Using Variable Differentials To Predict College Basketball, Nicholas Bennett

Williams Honors College, Honors Research Projects

The purpose of this Senior Honors Project is to research, study, and demonstrate newfound knowledge of various machine learning statistical techniques that are not covered in the University of Akron’s statistics major curriculum. This report will be an overview of three machine-learning methods that were used to predict NCAA Basketball results, specifically, the March Madness tournament. The variables used for these methods, models, and tests will include numerous variables kept throughout the season for each team, along with a couple variables that are used by the selection committee when tournament teams are being picked. The end goal is to find …

Campus Climate Sexual Assault Survey (2015) Analysis, Felicia Rosin

Williams Honors College, Honors Research Projects

The issue of sexual assault has garnered widespread attention in recent years, as is evident by the growing number of high-profile cases and mainstream social movements. With this increasingly bright spotlight, it is no surprise that The University of Akron has interest in improving the sexual violence education programs offered to students. In 2015, the university conducted a survey to gather information on the campus climate surrounding sexual assault. This analysis dives into a deeper analysis of the data gathered in an attempt to pinpoint areas that require the university’s attention. The analysis covers topics identified by Dean of Students …

Joint Analysis Of Multiple Phenotypes In Association Studies, Xiaoyu Liang

Dissertations, Master's Theses and Master's Reports

Genome-wide association studies (GWAS) have become a very effective research tool to identify genetic variants of underlying various complex diseases. In spite of the success of GWAS in identifying thousands of reproducible associations between genetic variants and complex disease, in general, the association between genetic variants and a single phenotype is usually weak. It is increasingly recognized that joint analysis of multiple phenotypes can be potentially more powerful than the univariate analysis, and can shed new light on underlying biological mechanisms of complex diseases. Therefore, developing statistical methods to test for genetic association with multiple phenotypes has become increasingly important. …

Some New And Generalized Distributions Via Exponentiation, Gamma And Marshall-Olkin Generators With Applications, Hameed Abiodun Jimoh

College of Graduate Studies: Theses & Dissertations

Three new generalized distributions developed via completing risk, gamma generator, Marshall-Olkin generator and exponentiation techniques are proposed and studied. Structural properties including quantile functions, hazard rate functions, moment, conditional moments, mean deviations, R\'enyi entropy, distribution of order statistics and maximum likelihood estimates are presented. Monte Carlo simulation is employed to examine the performance of the proposed distributions. Applications of the generalized distributions to real lifetime data are presented to illustrate the usefulness of the models.

Estimating The Respiratory Lung Motion Model Using Tensor Decomposition On Displacement Vector Field, Kingston Kang

Theses and Dissertations

Modern big data often emerge as tensors. Standard statistical methods are inadequate to deal with datasets of large volume, high dimensionality, and complex structure. Therefore, it is important to develop algorithms such as low-rank tensor decomposition for data compression, dimensionality reduction, and approximation.

With the advancement in technology, high-dimensional images are becoming ubiquitous in the medical field. In lung radiation therapy, the respiratory motion of the lung introduces variabilities during treatment as the tumor inside the lung is moving, which brings challenges to the precise delivery of radiation to the tumor. Several approaches to quantifying this uncertainty propose using a …

Spatial Modelling And Wildlife Health Surveillance: A Case Study Of White Nose Syndrome In Ontario, Lauren Yee

Theses and Dissertations (Comprehensive)

Wildlife data is often limited by survey effort, small sample sizes, and spatial biases associated with collection and missing data. These factors can create unique challenges from a surveillance perspective when trying to extract spatial patterns of habitat suitability and disease distributions for conservation and management purposes. This thesis examined data quality from a wildlife health database in the context of spatial analysis of wildlife disease. Spatial analysis of the data to predict habitat suitability of bats and white nose syndrome afflicted bats was examined by using the MaxEnt modelling method. Methods to reduce spatial bias were examined and specific …

Statistical Methods For Analyzing Multivariate Phenotypes And Detecting Rare Variant Associations, Huanhuan Zhu

Dissertations, Master's Theses and Master's Reports

This dissertation includes four papers with each distributed in one chapter.

In chapter 1, I compared the performance of eight multivariate phenotype association tests. The motivation to conduct this power comparison paper is as follows. For nearly 15 years, genome-wide association studies (GWAS) have been widely used to identify genetic variants associated with human diseases and traits. GWAS typically investigate genetic variants for a predefined phenotype, thus fail to identify weak but important effects. In recent years, many multivariate association tests have been developed. However, there is a lack of comprehensive summary of such kinds of approaches. To fill this …

Statistical Analysis Of Momentum In Basketball, Mackenzi Stump

Honors Projects

The “hot hand” in sports has been debated for as long as sports have been around. The debate involves whether streaks and slumps in sports are true phenomena or just simply perceptions in the mind of the human viewer. This statistical analysis of momentum in basketball analyzes the distribution of time between scoring events for the BGSU Women’s Basketball team from 2011-2017. We discuss how the distribution of time between scoring events changes with normal game factors such as location of the game, game outcome, and several other factors. If scoring events during a game were always randomly distributed, or …

Bayesian Model For Detection Of Outliers In Linear Regression With Application To Longitudinal Data, Zahraa Al-Sharea

Graduate Theses and Dissertations

Outlier detection is one of the most important challenges with many present-day applications. Outliers can occur due to uncertainty in data generating mechanisms or due to an error in data recording/processing. Outliers can drastically change the study's results and make predictions less reliable. Detecting outliers in longitudinal studies is quite challenging because this kind of study is working with observations that change over time. Therefore, the same subject can produce an outlier at one point in time produce regular observations at all other time points. A Bayesian hierarchical modeling assigns parameters that can quantify whether each observation is an outlier …

Constructing A Confidence Interval For The Fraction Who Benefit From Treatment, Using Randomized Trial Data, Emily J. Huang, Ethan X. Fang, Daniel F. Hanley, Michael Rosenblum

Johns Hopkins University, Dept. of Biostatistics Working Papers

The fraction who benefit from treatment is the proportion of patients whose potential outcome under treatment is better than that under control. Inference on this parameter is challenging since it is only partially identifiable, even in our context of a randomized trial. We propose a new method for constructing a confidence interval for the fraction, when the outcome is ordinal or binary. Our confidence interval procedure is pointwise consistent. It does not require any assumptions about the joint distribution of the potential outcomes, although it has the flexibility to incorporate various user-defined assumptions. Unlike existing confidence interval methods for partially …

Comparison Of Adaptive Randomized Trial Designs For Time-To-Event Outcomes That Expand Versus Restrict Enrollment Criteria, To Test Non-Inferiority, Josh Betz, Jon Arni Steingrimsson, Tianchen Qian, Michael Rosenblum

Johns Hopkins University, Dept. of Biostatistics Working Papers

Adaptive enrichment designs involve preplanned rules for modifying patient enrollment criteria based on data accrued in an ongoing trial. These designs may be useful when it is suspected that a subpopulation, e.g., defined by a biomarker or risk score measured at baseline, may benefit more from treatment than the complementary subpopulation. We compare two types of such designs, for the case of two subpopulations that partition the overall population. The first type starts by enrolling the subpopulation where it is suspected the new treatment is most likely to work, and then may expand inclusion criteria if there is early evidence …

A Cross-Sectional Exploration Of Household Financial Reactions And Homebuyer Awareness Of Registered Sex Offenders In A Rural, Suburban, And Urban County., John Charles Navarro

Electronic Theses and Dissertations

As stigmatized persons, registered sex offenders betoken instability in communities. Depressed home sale values are associated with the presence of registered sex offenders even though the public is largely unaware of the presence of registered sex offenders. Using a spatial multilevel approach, the current study examines the role registered sex offenders influence sale values of homes sold in 2015 for three U.S. counties (rural, suburban, and urban) located in Illinois and Kentucky within the social disorganization framework. Homebuyers were surveyed to examine whether awareness of local registered sex offenders and the homebuyer’s community type operate as moderators between home selling …

Tree-Based Regression For Interval-Valued Data, Chih-Ching Yeh

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Regression methods for interval-valued data have been increasingly studied in recent years. As most of the existing works focus on linear models, it is important to note that many problems in practice are nonlinear in nature and therefore development of nonlinear regression tools for intervalvalued data is crucial. In this project, we propose a tree-based regression method for interval-valued data, which is well applicable to both linear and nonlinear problems. Unlike linear regression models that usually require additional constraints to ensure positivity of the predicted interval length, the proposed method estimates the regression function in a nonparametric way, so the …

Novel Bayesian Adaptive Clinical Trial Designs In Early Phases, Haitao Pan

Dissertations and Theses (Open Access)

Early phase, or phase I and phase II, trials are the first step in testing new medicines that have been developed in the lab. The main goal of phase I clinical trials is to establish the recommended dose of new drugs for phase II trials. For the cytotoxic drugs, the goal is to find maximum tolerated dose (MTD). The guiding principle for dose escalation in phase I trials is to avoid exposing too many patients to subtherapeutic doses while preserving safety and maintaining rapid accrual. Therefore, dose escalation methods, especially Bayesian designs, are recommended to be used in phase I …

A Tail-Based Test For Differential Expression Analysis And Pathway Analysis In Rna-Sequencing Data, Jiong Chen

Dissertations and Theses (Open Access)

RNA sequencing data have been abundantly generated in biomedical research for biomarker discovery and pathway analysis. Such data at the exon-level are usually heavily tailed and correlated. Conventional statistical tests based on the mean or median difference for differential expression likely suffer from low power when the between-group difference occurs mostly in the upper or lower tail of the distribution of gene expression. We propose a tail-based test to make comparisons between groups in terms of a specific distribution area rather than a single location. The proposed test, which is derived from quantile regression, adjusts for covariates and accounts for …

Testing The Independence Hypothesis Of Accepted Mutations For Pairs Of Adjacent Amino Acids In Protein Sequences, Jyotsna Ramanan, Peter Revesz

School of Computing: Faculty Publications

Evolutionary studies usually assume that the genetic mutations are independent of each other. However, that does not imply that the observed mutations are independent of each other because it is possible that when a nucleotide is mutated, then it may be biologically beneficial if an adjacent nucleotide mutates too. With a number of decoded genes currently available in various genome libraries and online databases, it is now possible to have a large-scale computer-based study to test whether the independence assumption holds for pairs of adjacent amino acids. Hence the independence question also arises for pairs of adjacent amino acids within …

Marketing The Mountain State: A Large N Study Of User Engagement On Twitter, Kirk Richardson

Capstone Projects – Politics and Government

Much of the evolving research on the use of social media in destination marketing emphasizes how information diffusion influences the reputational image of place. The present study uses Twitter data to focus on the relative differences in user engagement across discrete account types. Specifically, this is done to examine how the official destination marketing organization of Montana—the Montana Office of Tourism (MTOT)—performs relative to other account types. Several regression analyses conducted on Twitter data associated with an ongoing MTOT place branding campaign reveal that tweets sent from ‘official’ accounts are more likely to be retweeted, and are estimated to receive …

Incorporating Place And Space: A Hierarchical Spatial Approach To Exploring Preventable Congestive Heart Failure Hospitalizations In New York City, Rachael Weiss Riley

Dissertations and Theses

Background: Faced with rising medical care costs, increasing prevalence, and widening health disparities, preventing congestive heart failure (CHF) hospitalizations is a central public health concern. Despite evidence of geographical clustering in preventable CHF admissions, there is a lack of research designed to examine spatial patterning of CHF and the local area neighborhood determinants that contribute to this variability. This study sought to assess and evaluate the importance of both space and place in analyzing preventable CHF hospitalizations and readmissions by applying appropriate statistical techniques, clarifying the assumption inherent in each method, and interpreting the findings within the context of existing …

Mechanistic Mathematical Models: An Underused Platform For Hpv Research, Marc Ryser, Patti Gravitt, Evan R. Myers

Global Health Faculty Publications

Health economic modeling has become an invaluable methodology for the design and evaluation of clinical and public health interventions against the human papillomavirus (HPV) and associated diseases. At the same time, relatively little attention has been paid to a different yet complementary class of models, namely that of mechanistic mathematical models. The primary focus of mechanistic mathematical models is to better understand the intricate biologic mechanisms and dynamics of disease. Inspired by a long and successful history of mechanistic modeling in other biomedical fields, we highlight several areas of HPV research where mechanistic models have the potential to advance the …

Gilmore Girls And Instagram: A Statistical Look At The Popularity Of The Television Show Through The Lens Of An Instagram Page, Brittany Simmons

Student Scholar Symposium Abstracts and Posters

After going on the Warner Brothers Tour in December of 2015, I created a Gilmore Girls Instagram account. This account, which started off as a way for me to create edits of the show and post my photos from the tour turned into something bigger than I ever could have imagined. In just over a year I have over 55,000 followers. I post content including revival news, merchandise, and edits of the show that have been featured in Entertainment Weekly, Bustle, E! News, People Magazine, Yahoo News, & GilmoreNews.

I created a dataset of qualitative and quantitative outcomes from my …

Comparison Of Survival Curves Between Cox Proportional Hazards, Random Forests, And Conditional Inference Forests In Survival Analysis, Brandon Weathers

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Survival analysis methods are a mainstay of the biomedical fields but are finding increasing use in other disciplines including finance and engineering. A widely used tool in survival analysis is the Cox proportional hazards regression model. For this model, all the predicted survivor curves have the same basic shape, which may not be a good approximation to reality. In contrast the Random Survival Forests does not make the proportional hazards assumption and has the flexibility to model survivor curves that are of quite different shapes for different groups of subjects. We applied both techniques to a number of publicly available …

Trend And Return Level Of Extreme Snow Events In New York City, Mintaek Lee

Boise State University Theses and Dissertations

A major winter storm brought up to 42 inches of snow in parts of the Mid-Atlantic and Northeast United States for January 22-24, 2016. The blizzard of January 2016 impacted about 102.8 million people, where at least 55 people died due to the snowstorm and it caused economic losses in a range of $500 million to $3 billion. This thesis studies two important aspects of extreme snow events: maximum snowfall and maximum snow depth. We apply extreme value methods to extreme snowfall and snow depth data from the New York City area to examine if there are any significant linear …

Denoising Tandem Mass Spectrometry Data, Felix Offei

Electronic Theses and Dissertations

Protein identification using tandem mass spectrometry (MS/MS) has proven to be an effective way to identify proteins in a biological sample. An observed spectrum is constructed from the data produced by the tandem mass spectrometer. A protein can be identified if the observed spectrum aligns with the theoretical spectrum. However, data generated by the tandem mass spectrometer are affected by errors thus making protein identification challenging in the field of proteomics. Some of these errors include wrong calibration of the instrument, instrument distortion and noise. In this thesis, we present a pre-processing method, which focuses on the removal of noisy …

Telephone Polls And Pps Sampling: A Potential Boon To The Polling Industry, Jade Mckay Burt

Undergraduate Honors Capstone Projects

In the wake of the 2016 election, the polling industry has no shortage of critics. While these are difficult times for the industry as a whole, there are exciting innovations happening that will serve to benefit and revitalize the industry for years. One of these exciting innovations is Probability Proportional to Size (PPS) sampling. I will elaborate on what PPS sampling is and provide a mathematical foundation for its use in polling. I also discuss what some of the myriad of issues plaguing the polling industry are and then show how PPS sampling can be used to remedy many of …

Estimating Autoantibody Signatures To Detect Autoimmune Disease Patient Subsets, Zhenke Wu, Livia Casciola-Rosen, Ami A. Shah, Antony Rosen, Scott L. Zeger

Johns Hopkins University, Dept. of Biostatistics Working Papers

Autoimmune diseases are characterized by highly specific immune responses against molecules in self-tissues. Different autoimmune diseases are characterized by distinct immune responses, making autoantibodies useful for diagnosis and prediction. In many diseases, the targets of autoantibodies are incompletely defined. Although the technologies for autoantibody discovery have advanced dramatically over the past decade, each of these techniques generates hundreds of possibilities, which are onerous and expensive to validate. We set out to establish a method to greatly simplify autoantibody discovery, using a pre-filtering step to define subgroups with similar specificities based on migration of labeled, immunoprecipitated proteins on sodium dodecyl sulfate …

Contributions To Statistical Testing, Prediction, And Modeling, John C. Pesko

Mathematics & Statistics ETDs

1. "Parametric Bootstrap (PB) and Objective Bayesian (OB) Testing with Applications to Heteroscedastic ANOVA": For one-way heteroscedastic ANOVA, we show a close relationship between the PB and OB approaches to significance testing, demonstrating the conditions for which the two approaches are equivalent. Using a simulation study, PB and OB performance is compared to a test based on the predictive distribution as well as the unweighted test of Akritas & Papadatos (2004). We extend this work to the RCBD with subsampling model, and prove a repeated sampling property and large sample property for general OB significance testing.

2. "Early Identification of …

Session D-5: Informal Comparative Inference: What Is It?, Karen Togliatti

Professional Learning Day

Come and experience a hands-on task that has middle-school students grapple with informal inferential reasoning. Three key principles of informal inference – data as evidence, probabilistic language, and generalizing ‘beyond the data’ will be discussed as students build and analyze distributions to answer the question, “Does hand dominance play a role in throwing accuracy?” Connections to the CCSSM statistics standards for middle-school will be highlighted.