Statistics and Probability Commons^™

Power Approximations For Generalized Linear Mixed Models In R Using Steep Priors On Variance Components, Sydney Geisler

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

When designing an experiment, researchers often want to know how likely they are to detect statistically significant effects in the resulting data, i.e., they want to estimate their statistical power. The probability distribution method is a flexible way to do this, and it is currently implemented in the statistical software package SAS. This method requires a hypothetical data set (showing the magnitude of hypothesized effects) and constant values of variance components, which are critical elements of the statistical models used. The statistical software package R is increasingly popular, but the probability distribution method has not yet been implemented in R, …

Statistical Challenges And Methods For Missing And Imbalanced Data, Rose Adjei

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Missing data remains a prevalent issue in every area of research. The impact of missing data, if not carefully handled, can be detrimental to any statistical analysis. Some statistical challenges associated with missing data include, loss of information, reduced statistical power and non-generalizability of findings in a study. It is therefore crucial that researchers pay close and particular attention when dealing with missing data. This multi-paper dissertation provides insight into missing data across different fields of study and addresses some of the above mentioned challenges of missing data through simulation studies and application to real datasets. The first paper of …

Bayesian Adaptive Clinical Trial Design, Mengyi Lu

Dissertations & Theses (Open Access)

The landscape of drug development in oncology has changed from conventional chemotherapies to molecular targeted therapies and immunotherapies, which provide innovative therapeutic modalities for treating cancers. These novel therapeutic agents work through mechanisms that fundamentally differ from standard chemotherapeutic agents, making the conventional trial design paradigm inefficient and dysfunctional. Specifically, the focus of dose-finding trials has shifted from finding the maximum tolerated dose (MTD) to the optimal biological dose (OBD), defined as the dose that optimizes the risk–benefit tradeoff. How to accurately identify the OBD and its dosing schedule is of great importance to maximize efficacy and safety of targeted …

Evaluating The Health Impacts Of Fruit And Vegetable Intake At The Individual Level And Food Pantry Level Among Food Pantry Users, Jiacheng Chen

Legacy Theses & Dissertations (2009 - 2024)

Background: Chronic diseases impose heavy burdens on individuals and the healthcare system in the US. Many factors were found to be associated with chronic diseases, including demographics, family history, social environmental factors, and individual behavioral factors such as diet and physical activity. Among those factors, fruit and vegetable intake can have substantial health impacts via a variety of causal pathways. Fruit and vegetable (F&V) consumption is generally lower among individuals living in households experiencing food insecurity and rely on food assistance programs. Decreased F&V intake among food pantry users may negatively impact health. However, conducting quantitative analysis on this population …

Metabolic Alterations And Cardiovascular Risk After Hepatitis C Cure In Subjects With Or At Risk For Hiv, Christophe Maxime Fokoua Dongmo

Legacy Theses & Dissertations (2009 - 2024)

Background. Hepatitis C virus (HCV) infection engenders substantial metabolic changes. These changes are altered when the virus is cleared after successful treatment. We measured these metabolic alterations that occur after HCV cure; further, we assessed whether these alterations differed in subgroups defined by patients’ characteristics.

Green On The Map - The Influence Of Conservation Easements On The Naturalness Of Landscapes In The United States, Nakisha Fouch

All Dissertations

Large protected areas have long been the cornerstone of conservation biology, however, in an era branded by the human dominance of ecosystems, regional landscape structure and function are often a consequence of accumulated land-use decisions that may or may not include a nod to conservation planning. With underrepresentation of habitats in publicly protected areas, attention has focused on the function of alternative land conservation mechanisms. Private conservation easements (CEs) have proliferated in the United States, yet assessing landscape-level function is confounded by holder and donor intent, national and regional policy, regional landscape contexts, varying extents, resolution, and temporal scale. Over …

Learning Graphical Models Of Multivariate Functional Data With Applications To Neuroimaging, Jiajing Niu

All Dissertations

This dissertation investigates the functional graphical models that infer the functional connectivity based on neuroimaging data, which is noisy, high dimensional and has limited samples. The dissertation provides two recipes to infer the functional graphical model: 1) a fully Bayesian framework 2) an end-to-end deep model.

We first propose a fully Bayesian regularization scheme to estimate functional graphical models. We consider a direct Bayesian analog of the functional graphical lasso proposed by Qiao et al. (2019).. We then propose a regularization strategy via the graphical horseshoe. We compare both Bayesian approaches to the frequentist functional graphical lasso, and compare the …

Lindley Processes With Correlated Changes, John Grant

All Dissertations

This dissertation studies a Lindley random walk model when the increment process driving the walk is strictly stationary. Lindley random walks govern customer waiting times in many queueing models and several natural and business processes, including snow depths, frozen soil depths, inventory quantities, etc. Probabilistic properties of a Lindley process with time-correlated stationary changes are explored. We provide a streamlined argument that the process admits a limiting stationary distribution when the mean of the incremental changes is negative and that the Lindley process is strictly stationary when starting from this stationary distribution. The Markov characteristics of the process are explored …

Weather Parameters Influencing The Incidence Of Citrus Canker Caused By Aw Strain In The Rio Grande Valley, Amit Sharma

Theses and Dissertations

Citrus canker caused by bacterium Xanthomonas citri subsp. citri (Xcc) seriously affects the citrus industry by making the fruit unmarketable due to unsightly lesions on the fruit. Canker caused by Aw strain of Xcc was reported in the citrus trees located in the residential areas of the Rio Grande Valley (RGV). Canker severity differs amongst cultivars/varieties, and it is influenced by prevailing environmental conditions. Multiple regression modeling of the disease incidence with the environmental variables such as temperature, humidity, windspeed, wind gust, and rainfall was performed to understand the environmental conditions that are favorable for spread of citrus …

Estimation Of The Parameters In A Mixture Of Two Normal Distributions And The Generalized Pivotal Quantity Method, Md Faruk Hossain

UNLV Theses, Dissertations, Professional Papers, and Capstones

A pivotal quantity is a random variable that is a function of both the random data and the unknown population parameters and whose probability distribution does not depend on any of the unknown parameters. The population parameters here may include nuisance parameters. Historically, pivotal quantities have been used for the construction of test statistics for hypothesis testing of some of these unknown parameters. They have also been used for the construction of confidence intervals for some of these parameters.Generalized pivotal quantities (GPQ) were introduced by Tsui and Weerahandi (1989) and Weerahandi (1993). A GPQ is a function, not only of …

A Multistate Competing Risks Framework For Preconception Prediction Of Pregnancy Outcomes, Kaitlyn Cook, Neil J. Perkins, Enrique Schisterman, Sebastien Haneuse

Statistical and Data Sciences: Faculty Publications

Background: Preconception pregnancy risk profiles—characterizing the likelihood that a pregnancy attempt results in a full-term birth, preterm birth, clinical pregnancy loss, or failure to conceive—can provide critical information during the early stages of a pregnancy attempt, when obstetricians are best positioned to intervene to improve the chances of successful conception and full-term live birth. Yet the task of constructing and validating risk assessment tools for this earlier intervention window is complicated by several statistical features: the final outcome of the pregnancy attempt is multinomial in nature, and it summarizes the results of two intermediate stages, conception and gestation, whose outcomes …

Statistical Methods For Modern Threats, Brandon Lumsden

All Dissertations

More than ever before, technology is evolving at a rapid pace across the broad spectrum of biological sciences. As data collection becomes more precise, efficient, and standardized, a demand for appropriate statistical modeling grows as well. Throughout this dissertation, we examine a variety of new age data arising from modern technology of the 21st century. We begin by employing a suite of existing statistical techniques to address research questions surrounding three medical conditions presenting in public health sciences. Here we describe the techniques used, including generalized linear models and longitudinal models, and we summarize the significant associations identified between research …

Retrospective Varying Coefficient Association Analysis Of Longitudinal Binary Traits, Gang Xu

UNLV Theses, Dissertations, Professional Papers, and Capstones

Many genetic studies contain rich information on longitudinal phenotypes that require powerful analytical tools for optimal analysis. Genetic analysis of longitudinal data that incorporates temporal variation is important for understanding the genetic architecture and biological variation of complex diseases. Most of the existing methods assume that the contribution of genetic variants is constant over time and fails to capture the dynamic pattern of disease progression. However, the relative influence of genetic variants on complex traits fluctuates over time.We developed several tests to fill the gap of analyzing time-varying genetic effects in longitudinal GWAS for binary traits. First, we propose a …

Statistical Methods For Meta-Analysis In Large-Scale Genomic Experiments, Wimarsha Thathsarani Jayanetti

Mathematics & Statistics Theses & Dissertations

Recent developments in high throughput genomic assays have opened up the possibility of testing hundreds and thousands of genes simultaneously. With the availability of vast amounts of public databases, researchers tend to combine genomic analysis results from multiple studies in the form of a meta-analysis. Meta-analysis methods can be broadly classified into two main categories. The first approach is to combine the statistical significance (pvalues) of the genes from each individual study, and the second approach is to combine the statistical estimates (effect sizes) from the individual studies. In this dissertation, we will discuss how adherence to the standard null …

Use Of Healthcare Utilization Records For Analyzing Trends In Clinical Toxoplasmosis: A Comparison Of Nevada And The United States, Elijah Kreutzer

UNLV Theses, Dissertations, Professional Papers, and Capstones

Toxoplasmosis, a zoonotic disease caused by the parasitic protist Toxoplasma gondii, is a ubiquitous, global public health concern with a wide variety of clinical manifestations. Surveillance for the disease is lacking even in developed countries, and what surveillance is present most often focuses on pregnant women. This research investigated trends in clinical toxoplasmosis in Nevada and nationally to address the lack of knowledge concerning how Nevada discharges compare to national discharges in cases of toxoplasmosis. Specifically, this research sought to determine what characterizes toxoplasmosis in Nevada across inpatient, outpatient, and emergency department settings, as well as how these cases differ …

Natural Language Processing For Disaster Tweets, Akinyemi D. Apampa, Nan Li

Publications and Research

Our goal is to establish an automatic model that identifies which tweets are about natural disasters based on the content of the tweets. Our method is to construct a decision tree based on keyword searching. We will construct the model using 7,645 tweets and test our model on 3,465 tweets as an assessment of the performance.

(R1953) M-Regression Estimation With The K Nearest Neighbors Smoothing Under Quasi-Associated Data In Functional Statistics, Bellatrach Nadjet, Bouabsa Wahiba, Attouch Mohammed Kadi, Fetitah Omar

Applications and Applied Mathematics: An International Journal (AAM)

The main goal of this paper is to study the non parametric M-estimation under quasi-associated sequence with the k Nearest Neighbor’s method shortly (kNN). We construct an estimator of this nonparametric function and we study its asymptotic properties. Furthermore, a comparison study based on simulated data is also provided to illustrate the highly sensitive of the kNN approach to the presence of even a small proportion of outliers in the data.

(R1974) A Multi Server Markovian Working Vacation Queue With Server State Dependent Rates And With Partial Breakdown, A. Sundaramoorthy, R. Kalyanaraman

Applications and Applied Mathematics: An International Journal (AAM)

In this article, we consider an M/M/C queue in which the arrival rate and service rate depends on the state of the system. In addition, the servers takes working vacation and the system may breakdown. Whenever breakdown takes place, the repair process immediately commences. During the repair period the customers are given service in a reduced service rate. Based on the vacation termination point, two models have been defined. The steady state probability vector of the number of customers in the queue and the stability condition are obtained using Matrix-Geometric method. The stationary waiting time distributions have been obtained. Some …

Bayesian Methods For Graphical Models With Neighborhood Selection., Sagnik Bhadury

Electronic Theses and Dissertations

Graphical models determine associations between variables through the notion of conditional independence. Gaussian graphical models are a widely used class of such models, where the relationships are formalized by non-null entries of the precision matrix. However, in high-dimensional cases, covariance estimates are typically unstable. Moreover, it is natural to expect only a few significant associations to be present in many realistic applications. This necessitates the injection of sparsity techniques into the estimation method. Classical frequentist methods, like GLASSO, use penalization techniques for this purpose. Fully Bayesian methods, on the contrary, are slow because they require iteratively sampling over a quadratic …

Learning From Public Spaces In Historic Cities, Cody Josh Kucharski

Symposium of Student Scholars

Successful public spaces in cities are key for enhancing social cohesion and improving health and safety. Learning from historic cities involves the development of representational and analytical tools aimed at capturing their essence as places of human interaction. The research reports findings of the spatial analysis of twenty Adriatic and Ionian coastal cities, which addresses the question of how the network of public spaces calibrates different degrees of spatial enclosure necessary for creating successful social interactions. Cities in the littoral region include well-preserved historic centers that are renowned for the successful integration of urban squares into the urban fabric. For …

The Potential Of Private Health Insurance Ownership Based On The 2018-2020 National Socioeconomic Survey Data, Arief Rosyid Hasan, Adang Bachtiar, Cicilya Candi

Kesmas

In 2014, the Indonesian Government introduced a social security program in the health sector. However, Indonesia’s out-of-pocket expenses remain high due to a lack of public interest in National Health Insurance services. Financing expensive health services with high out-of-pocket expenses has the potential to cause poverty. Private health insurance is considered a solution to this problem. This study aimed to determine the socioeconomic factors of private health insurance ownership and its potential in Indonesia. This study used secondary data from the 2018, 2019, and 2020 National Socioeconomic Surveys. Logistic regression analysis showed that the variables related to private health insurance …

A Bootstrap Method For A Multiple-Imputation Variance Estimator In Survey Sampling, Lili Yu, Yichuan Zhao

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

Rubin’s variance estimator of the multiple imputation estimator for a domain mean is not asymptotically unbiased. Kim et al. derived the closed-form bias for Rubin’s variance estimator. In addition, they proposed an asymptotically unbiased variance estimator for the multiple imputation estimator when the imputed values can be written as a linear function of the observed values. However, this needs the assumption that the covariance of the imputed values in the same imputed dataset is twice that in the different imputed datasets. In this study, we proposed a bootstrap variance estimator that does not need this assumption. Both theoretical argument and …

Pandemic Fatigue Impedes Mitigation Of Covid-19 In Hong Kong, Zhanwei Du, Lin Wang, Songwei Shan, Dickson Lam, Tim K. Tsang, Jingyi Xiao, Huizhi Gao, Bingyi Yang, Sheikh Taslim Ali, Sen Pei, Isaac Chun-Hai Fung, Eric H. Y. Lau, Qiuyan Liao, Peng Wu, Lauren Ancel Meyers, Gabriel M. Leung, Benjamin Cowling

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

Hong Kong has implemented stringent public health and social measures (PHSMs) to curb each of the four COVID-19 epidemic waves since January 2020. The third wave between July and September 2020 was brought under control within 2 m, while the fourth wave starting from the end of October 2020 has taken longer to bring under control and lasted at least 5 mo. Here, we report the pandemic fatigue as one of the potential reasons for the reduced impact of PHSMs on transmission in the fourth wave. We contacted either 500 or 1,000 local residents through weekly random-digit dialing of landlines …

Association Between The Health Belief Model, Exercise, And Nutrition Behaviors During The Covid-19 Pandemic, Keagan Kiely, Bill Mase, Andrew R. Hansen, Jessica S. Schwind

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

Introduction: The COVID-19 pandemic has affected our nation’s health further than the infection it causes. Physical activity levels and dietary intake have suffered while individuals grapple with the changes in behavior to reduce viral transmission. With unique nuances regarding the access to physical activity and nutrition during the pandemic, the constructs of Health Belief Model (HBM) may present themselves differently in nutrition and exercise behaviors compared to precautions implemented to reduce viral transmission studied in previous research. The purpose of this study was to investigate the extent of exercise and nutritional behavior change during the COVID-19 pandemic and explain the …

Convexity Of Regularized Optimal Transport Dissimilarity Measures For Signed Signals, Christian P. Fowler

Mathematics & Statistics ETDs

Debiased Sinkhorn divergence (DS divergence) is a distance function of

regularized optimal transport that measures the dissimilarity between two

probability measures of optimal transport. This thesis analyzes the advantages of

using DS divergence when compared to the more computationally expensive

Wasserstein distance as well as the classical Euclidean norm. Specifically, theory

and numerical experiments are used to show that Debiased Sinkhorn divergence

has geometrically desirable properties such as maintained convexity after data

normalization. Data normalization is often needed to calculate Sinkhorn

divergence as well as Wasserstein distance, as these formulas only accept

probability distributions as inputs and do not directly …

Statistical Methods For Differential Gene Expression Analysis Under The Case-Cohort Design, Lidong Wang

Mathematics & Statistics ETDs

Differential gene expression analysis has the potential to discover candidate biomarkers, therapeutic targets, and gene signatures. How to save money when using an unaffordable sample is a practical question. The case-cohort (CCH) study design can blend the economy of case-control studies with the advantages of cohort studies. But it has not been seen in the medical research literature where high-throughput genomic data were involved.

A score test does not need to fit the Cox PH model iteratively; hence, it can save computing time and avoid potential convergence issues. We developed a score test under the CCH design to identify DEGs …

Evaluation Of Circular Logistic Regression Models With Asymmetrical Link Functions, Feridun Tasdan

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Incorporating Interventions To An Extended Seird Model With Vaccination: Application To Covid-19 In Qatar, Elizabeth Amona

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Estimating R0 For Dengue Emergence In Central Argentina Using Statistical Models, Sahil Chindal

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Functional Data Analysis Of Covid-19, Nichole L. Fluke

Mathematics & Statistics ETDs

This thesis deals with Functional Data Analysis (FDA) on COVID data. The Data involves counts for new COVID cases, hospitalized COVID patients, and new COVID deaths. The data used is for all the states and regions in the United States. The data starts in March 1^st, 2020 and goes through March 31^st, 2021. The FDA smooths the data and looks to see if there are similarities or differences between the states and regions in the data. The data also shows which states and regions stand out from the others and which ones are similar. Also shown …