Statistics and Probability Commons^™

Bar-Code Variable: A Novel Approach To Efficiently Find Interaction Effects, Lee Sak Park

Theses and Dissertations--Statistics

This paper introduces the bar-code variable, a novel method for processing a sequence of binary explanatory variables efficiently in the linear regression modeling framework. Represented as an integer or a sequence of bits, the bar-code variable captures infor- mation on original binary variables and their potential interaction effects. Utilizing the bar-code variable, the study explores streamlined feature selection in linear re- gression modeling with binary explanatory variables. The paper demonstrates how the bar-code variable, through re-parameterization, facilitates the transition from cell means estimates, µ̂, in the cell-means ANOVA model to coefficient estimates, β̂, in the linear regression model, and vice …

On Generative Models And Joint Architectures For Document-Level Relation Extraction, Aviv Brokman

Theses and Dissertations--Statistics

Biomedical text is being generated at a high rate in scientific literature publications and electronic health records. Within these documents lies a wealth of potentially useful information in biomedicine. Relation extraction (RE), the process of automating the identification of structured relationships between entities within text, represents a highly sought-after goal in biomedical informatics, offering the potential to unlock deeper insights and connections from this vast corpus of data. In this dissertation, we tackle this problem with a variety of approaches.

We review the recent history of the field of document-level RE. Several themes emerge. First, graph neural networks dominate the …

Difs And Bayescluster: Novel Methods For Single_Cell Rna Sequencing Analysis, Kun Liu

Theses and Dissertations--Statistics

Single-cell RNA sequencing (scRNA-seq) has transformed our understanding of cellular heterogeneity and gene expression dynamics. Despite its potential, the inherent noise and sparsity of scRNA-seq data pose significant challenges in clustering cells into biologically meaningful groups. This dissertation addresses these challenges through two novel methodologies aimed at enhancing the accuracy and robustness of scRNA-seq data analysis.

First, we introduce the Differential Feature Selection (DIFS) framework, designed to improve the identification of differential features in scRNA-seq data. DIFS employs a two-stage marker identification process. In the first stage, a modified Dip Test is used to filter and identify genes with significant …

A Case Report On A Women’S Residential Substance Use Program In A Rural And Urban Setting, Deborah Winders Davis, Yana Feygin, Madeline Shipley, Tiffany Cole Hall, Chaly Downs, Stephanie Hoskins, Natalie Pasquenza, Scott D. Duncan, Liza M. Creel

Biostatistics Faculty Publications

Purpose To describe program characteristics and outcomes of a residential substance use recovery program serving pregnant and parenting women in a rural and urban location.

Description This assessment of administrative records from April 1, 2020 through March 31, 2022, included women in a rural (n = 140) and urban (n = 321) county in Kentucky.

Assessment This retrospective case study used descriptive and non-parametric analyses to assess the population and examine differences between locations, race, and ethnicity for women served. Logistic regression tested predictors of goal achievement by community. Of 461 women served, 65 (14.1%) delivered a baby while in …

Health Care For People Who Are Incarcerated: Teaching Third-Year Medical Students About Rights, Challenges, And Avenues Of Advocacy, Anna-Maria South, Kelsey N. Karnik, Sara Hieneman, Anthony A. Mangino, Michelle R. Lofwall

Biostatistics Faculty Publications

Introduction: Incarcerated patients are a vulnerable patient population with unique barriers to health care that physicians in every specialty encounter. Current medical school curricula lack universal education on health care for incarcerated people.

Methods: We developed an interactive workshop to provide third-year medical students at the University of Kentucky with information about delivering care outside of dedicated carceral settings to individuals who are incarcerated. The workshop included education on the demographic characteristics and medical conditions present in these populations along with understanding incarcerated persons’ rights to health care and how to interact with them and the associated jail/prison workforce often …

Correction: Bayesian Kinetic Modeling For Tracer-Based Metabolomic Data, Xu Zhang, Ya Su, Andrew N. Lane, Arnold Stromberg, Teresa Whei-Mei Fan, Chi Wang

Statistics Faculty Publications

No abstract provided.

Stigma And Efficacy Beliefs Regarding Opioid Use Disorder Treatment And Naloxone In Communities Participating In The Healing Communities Study Intervention, Nicky Lewis, Barry Eggleston, Redonna K. Chandler, Dawn Goddard-Eckrich, Jamie E. Luster, Dacia Beard, Emma Rodgers, Rouba A. Chahine, Philip M. Westgate, Shoshana N. Benjamin, Janae Holloway, Thomas Clarke, R. Craig Lefebvre, Michael D. Stein, Donald W. Helme, Jennifer Reynolds, Sharon L. Walsh, Darcy Freedman, Nabila El-Bassel, Kara Stephens, Anita Silwal, Michelle R. Lofwall, Janet E. Childerhose, Hilary L. Surratt, Brooke N. Crockett, Amy L. Farmer, James L. David, Laura Fanucchi, Judy Harness, Ben Wilburn, Kelli Bursey, Kristin Mattson, Sarah Mann, Rebecca D. Jackson, Aimee Shadwick, Katherine Calver, Deborah Chassler, Jennifer Kimball, Nancy Regan, Jeffrey H. Samet, Rachel Sword-Cruz, Michael D. Slater

Biostatistics Faculty Publications

Background The HEALing Communities Study (HCS) included health campaigns as part of a community-engaged intervention to reduce opioid-related overdose deaths in 67 highly impacted communities across Kentucky, Massachusetts, New York, and Ohio. Five campaigns were developed with community input to provide information on opioid use disorder (OUD) and overdose prevention, reduce stigma, and build demand for evidence-based practices (EBPs). An evaluation examined the recognition of campaign messages about naloxone and whether stigma and efficacy beliefs regarding OUD treatment and naloxone changed in HCS intervention communities.

Methods Data were collected through surveys offered on Facebook/Instagram to members of communities participating in …

Weighted Mean Difference Statistics For Paired Data In The Presence Of Missing Values, Yuntong Li, Brent J. Shelton, William St Clair, Heidi L. Weiss, John L. Villano, Arnold Stromberg, Chi Wang, Li Chen

Markey Cancer Center Faculty Publications

Missing data is a common issue in many biomedical studies. Under a paired design, some subjects may have missing values in either one or both of the conditions due to loss of follow-up, insufficient biological samples, etc. Such partially paired data complicate statistical comparison of the distribution of the variable of interest between the two conditions. In this article, we propose a general class of test statistics based on the difference in weighted sample means without imposing any distributional or model assumption. An optimal weight is derived from this class of tests. Simulation studies show that our proposed test with …

A Proposed Fair Approach For Disseminating Geospatial Information System Maps, P. Travis Thompson, Sweta Ojha, Christian D. Powell, Kelly G. Pennell, Hunter N. B. Moseley

Markey Cancer Center Faculty Publications

We present a draft Minimum Information about Geospatial Information System (MIaGIS) standard for facilitating public deposition of geospatial information system (GIS) datasets that follows the FaIR (Findable, accessible, Interoperable and Reusable) principles. the draft MIaGIS standard includes a deposition directory structure and a minimum javascript object notation (JSON) metadata formatted file that is designed to capture critical metadata describing GIS layers and maps as well as their sources of data and methods of generation. the associated miagis Python package facilitates the creation of this MIAGIS metadata file and directly supports metadata extraction from both Esri JSON and GEOJSON GIS data …

Identifying And Sharing Per-And Polyfluoroalkyl Substances Hot-Spot Areas And Exposures In Drinking Water, Sweta Ojha, P. Travis Thompson, Christian D. Powell, Hunter N. B. Moseley, Kelly G. Pennell

Markey Cancer Center Faculty Publications

Exposure to per- and polyfluoroalkyl substances (PFAS) in drinking water is widely recognized as a public health concern. Decision-makers who are responsible for managing PFAS drinking water risks lack the tools to acquire the information they need. In response to this need, we provide a detailed description of a Kentucky dataset that allows decision-makers to visualize potential hot-spot areas and evaluate drinking water systems that may be susceptible to PFAS contamination. The dataset includes information extracted from publicly available sources to create five different maps in ArcGIS Online and highlights potential sources of PFAS contamination in the environment in relation …

Statistical Tolerance Regions For Flexible Modeling Paradigms, Yafan Guo

Theses and Dissertations--Statistics

Tolerance intervals in a regression setting allow the user to quantify, with a specified degree of confidence, bounds for a specified proportion of the sampled population when conditioned on a set of covariate values. While methods are available for tolerance intervals in fully-parametric regression settings, the construction of tolerance intervals for semiparametric regression models has been treated in a limited capacity. The first project fills this gap and develops likelihood-based approaches for the construction of pointwise one-sided and two-sided tolerance intervals for semiparametric regression models. A numerical approach is also presented for constructing simultaneous tolerance intervals. An appealing facet of …

Massachusetts Prevalence Of Opioid Use Disorder Estimation Revisited: Comparing A Bayesian Approach To Standard Capture-Recapture Methods, Jianing Wang, Nathan Doogan, Katherine L. Thompson, Dana Bernson, Daniel Feaster, Jennifer Villani, Redonna Chandler, Laura F. White, David Kline, Joshua A. Barocas

Statistics Faculty Publications

Background: The National Survey on Drug Use and Health (NSDUH) estimated the prevalence of opioid use disorder (OUD) among the civilian, noninstitutionalized people aged 12 years or older in Massachusetts as 1.2% between 2015 and 2017. Accurate estimation of the prevalence of OUD is critical to the success of treatment and resource planning. Various indirect estimation approaches have been used but are subject to data availability and infrastructure-related issues.

Methods: We used 2015 data from the Massachusetts Public Health Data Warehouse (PHD) to compare the results of two approaches to estimating OUD prevalence in the Massachusetts population. First, we used …

Statistical Intervals For Neural Network And Its Relationship With Generalized Linear Model, Sheng Yuan

Theses and Dissertations--Statistics

Neural networks have experienced widespread adoption and have become integral in cutting-edge domains like computer vision, natural language processing, and various contemporary fields. However, addressing the statistical aspects of neural networks has been a persistent challenge, with limited satisfactory results. In my research, I focused on exploring statistical intervals applied to neural networks, specifically confidence intervals and tolerance intervals. I employed variance estimation methods, such as direct estimation and resampling, to assess neural networks and their performance under outlier scenarios. Remarkably, when outliers were present, the resampling method with infinitesimal jackknife estimation yielded confidence intervals that closely aligned with nominal …

Probabilistic Methods For Inferring The Order Of Pathway Alterations During Carcinogenesis And Cancer Subtype Classification, Menghan Wang

Theses and Dissertations--Statistics

Carcinogenesis is a complex process involving somatic mutations in a number of key biological pathways. Studying cancer evolution is an important task which contributes to better understanding of cancer biology and facilitates identification of new therapeutic targets. We focus on two important questions in cancer evolution. The first question is to delineating the temporal order of pathway mutations during tumorigenesis. And the other question is to cluster patients into biologically meaningful cancer subtypes. We present new statistical methods to 1)leverage functional annotations of mutations to enhance estimation of the order of pathway mutations during carcinogenesis, 2) incorporate intra-tumoral heterogeneity information …

Tolerance Intervals For Various Regression Models, Xitong Zhou

Theses and Dissertations--Statistics

Among statistical intervals, confidence intervals and prediction intervals are well-known and commonly used. In many applications, the problem becomes finding an interval that covers at least a certain proportion $P$ of the population for a characteristic of interest with a specified confidence level $(1-\alpha)$. And such interval is named a $P$-content, $(1-\alpha)$-confidence Tolerance Interval (TI). The topic of the dissertation is the utility of tolerance intervals for various regression models. We begin with a discussion of tolerance intervals for linear and nonlinear regression models. We then propose a bootstrap method of constructing TIs for Tobit regression to deal with censored …

High Dimensional Data Analysis: Variable Screening And Inference, Lei Fang

Theses and Dissertations--Statistics

This dissertation focuses on the problem of high dimensional data analysis, which arises in many fields including genomics, finance, and social sciences. In such settings, the number of features or variables is much larger than the number of observations, posing significant challenges to traditional statistical methods.

To address these challenges, this dissertation proposes novel methods for variable screening and inference. The first part of the dissertation focuses on variable screening, which aims to identify a subset of important variables that are strongly associated with the response variable. Specifically, we propose a robust nonparametric screening method to effectively select the predictors …

Novel Modelling And Inference Considerations Involving The Exponentially-Modified Gaussian Distribution, Yanxi Li

Theses and Dissertations--Statistics

The exponentially-modified Gaussian (EMG) distribution is well-suited for analyzing data with positive skewness due to its characteristic positive skew from the exponential component. Despite its popularity in various fields, the EMG distribution has only been analyzed for univariate data without any regression settings. To address this limitation, we developed a generalized EMG regression model with covariates by assigning parametric functional forms to some or all of the parameters in the EMG distribution that vary with values of the covariates. To further perform data-clustering on observation points, we propose a competing regression model where the error structure is assumed to be …

Finite Mixtures Of Mean-Parameterized Conway-Maxwell-Poisson Models, Dongying Zhan

Theses and Dissertations--Statistics

For modeling count data, the Conway-Maxwell-Poisson (CMP) distribution is a popular generalization of the Poisson distribution due to its ability to characterize data over- or under-dispersion. While the classic parameterization of the CMP has been well-studied, its main drawback is that it is does not directly model the mean of the counts. This is mitigated by using a mean-parameterized version of the CMP distribution. In this work, we are concerned with the setting where count data may be comprised of subpopulations, each possibly having varying degrees of data dispersion. Thus, we propose a finite mixture of mean-parameterized CMP distributions. An …

Methodologies And Computational Tools For Zero-Inflated Discrete Weibull Models, Peng Yeh

Theses and Dissertations--Statistics

Count data with excess zeros is common in many fields, such as ecology, healthcare, and insurance. Excess zeros data are often causing the inaccurate fit from the count models. While zero-inflated models have been developing for over two decades, one should also consider a more flexible model that can handle the excess zeros and further over- or under-dispersion. In this talk, we discuss zero-inflated discrete Weibull model and some novel computational contributions. The flexibility and competitiveness of the ZIDW model are illustrated by simulation studies and a real data analysis. We also investigate the performance of the proposed model through …

Striving For Appropriate Antibiotic Use: A Biomarker Initiative, And Outcomes Associated With Azithromycin Exposure, Amanda Gusovsky

Theses and Dissertations--Pharmacy

The introduction of antibiotics into clinical practice is considered the greatest medical breakthrough of the 20^thcentury. However, the use of antibiotics can contribute to the development of resistance. In the United States (U.S.), approximately 2.8 million people are infected with antibiotic-resistant bacteria each year, and more than 35,000 people die as a result. Moreover, some antibiotics are known to cause cardiac side effects including QT prolongation, hypotension, and ventricular arrythmias. The U.S. Centers for Disease Control and Prevention (CDC) defines appropriate antibiotic use as the effort to use “the right antibiotic, at the right dose, for the right …

Clustering Hospital Performance Using Group-Based Multi-Trajectory Modeling With Singular Bayesian Information Criterion, Gaixin Du

Theses and Dissertations--Epidemiology and Biostatistics

Hospital performance is complex and patient-experience oriented. Currently, the Centers for Medicare and Medicaid Services (CMS) evaluate hospitals yearly with a single score of one to five ("Star Rating") using composite measures from five domains. However, a single composite score cannot fully describe it, and alternative measures should be considered. Healthcare quality improvement needs long-term data to validate effectiveness. Group-based multi-trajectory modeling (GBMTM) estimates probabilities of latent group membership based on longitudinal profiles from multiple outcomes. We use GBMTM to identify groups of hospitals with similar performance in SAS PROC TRAJ.

We downloaded Medicare-eligible hospitals (N=5,111) that provided patient care …

Potential Alzheimer's Disease Plasma Biomarkers, Taylor Estepp

Theses and Dissertations--Epidemiology and Biostatistics

In this series of studies, we examined the potential of a variety of blood-based plasma biomarkers for the identification of Alzheimer's disease (AD) progression and cognitive decline. With the end goal of studying these biomarkers via mixture modeling, we began with a literature review of the methodology. An examination of the biomarkers with demographics and other health factors found evidence of minimal risk of confounding along the causal pathway from biomarkers to cognitive performance. Further study examined the usefulness of linear combinations of biomarkers, achieved via partial least squares (PLS) analysis, as predictors of various cognitive assessment scores and clinical …

Economics Of Maple Syrup Production In Kentucky, Bobby Thapa

Theses and Dissertations--Forestry and Natural Resources

Maple syrup production is traditionally associated with New England regions in the United States, but there is growing interest in expanding it to other regions with suitable environmental conditions, including Kentucky. This study presents an in-depth analysis of the potential production and economic impacts of maple syrup in Kentucky using a multi-method approach. First, the study applies a stochastic production model to assess the effects of climatic and tree variables on maple syrup yield. The results reveal that several variables, including the number of maple trees, taps, temperatures, tapping season length, and time, significantly affect maple syrup yield. Second, input-output …

Wilcoxon-Mann-Whitney Effects For Clustered Data: Informative Cluster Size, Changrui Liu

Theses and Dissertations--Statistics

In recent research, there has been a growing interest in understanding the impact of informative cluster size (ICS) on statistical inference for clustered data. In the non-parametric context, the problem for testing equality of distribution functions has been the main consideration. We are aiming to develop inferential procedures for the Wilcoxon-Mann-Whitney effect, also known as the non-parametric relative effect, involving two or more groups. Computationally, results from both simulated and real-world data have shown promising results that our proposed tests effectively account for ICS and they particularly outperform other methods in the literature designed for ignorable cluster sizes. The applications …

Expectile Neural Networks For Genetic Data Analysis Of Complex Diseases, Jinghang Lin, Xiaoran Tong, Chenxi Li, Qing Lu

Biostatistics Faculty Publications

The genetic etiologies of common diseases are highly complex and heterogeneous. Classic methods, such as linear regression, have successfully identified numerous variants associated with complex diseases. Nonetheless, for most diseases, the identified variants only account for a small proportion of heritability. Challenges remain to discover additional variants contributing to complex diseases. Expectile regression is a generalization of linear regression and provides complete information on the conditional distribution of a phenotype of interest. While expectile regression has many nice properties, it has rarely been used in genetic research. In this paper, we develop an expectile neural network (ENN) method for genetic …

Estimating The Distribution Of Ratio Of Paired Event Times In Phase Ii Oncology Trials, Li Chen, Mark Burkard, Jianrong Wu, Jill M. Kolesar, Chi Wang

Markey Cancer Center Faculty Publications

With the rapid development of new anti-cancer agents which are cytostatic, new endpoints are needed to better measure treatment efficacy in phase II trials. For this purpose, Von Hoff (1998) proposed the growth modulation index (GMI), that is, the ratio between times to progression or progression-free survival times in two successive treatment lines. An essential task in studies using GMI as an endpoint is to estimate the distribution of GMI. Traditional methods for survival data have been used for estimating the GMI distribution because censoring is common for GMI data. However, we point out that the independent censoring assumption required …

A Pilot Study On The Impact Of The Bumptup® Mobile App On Physical Activity During And After Pregnancy, Rachel A. Tinius, Maire M. Blankenship, Allison M. Colao, Gregory S. Hawk, Madhawa Perera, Nancy E. Schoenberg

Statistics Faculty Publications

To combat maternal morbidity and mortality, interventions designed to increase physical activity levels during and after pregnancy are needed. Mobile phone-based interventions show considerable promise, and BumptUp® has been carefully developed to address the lack of exercise among pregnant and postpartum women. The primary goal of this pilot study was to test the potential efficacy of BumptUp® for improving physical activity among pregnant and postpartum women. A randomized controlled clinical trial was performed (N = 35) with women either receiving access to the mhealth app or an educational brochure. Physical activity and self-efficacy for exercise data were collected at baseline …

Biomonitoring Of Polybrominated Dioxins & Furans, Polychlorinated Dioxins & Furans, And Dioxin Like Polychlorinated Biphenyls In Vietnamese Female Electronic Waste Recyclers, Jenevieve S. Peecher, Arnold J. Schecter, Helen Lu, Hoang Trong Quynh, Arnold Stromberg, Jiaying Weng, Riley Crandall, Linda S. Birnbaum

Statistics Faculty Publications

Objective: E-waste is rising globally. This is a follow up to our study reporting metals/polybrominated diphenyl ethers (PBDE’s)/polychlorinated biphenyls (PCBs) in female e-waste recyclers. Here we report polybrominated, polychlorinated dioxins/furans, and dioxin-like polychlorinated biphenyls in these same workers. Methods: Female Vietnamese recyclers and non-recyclers recruited; blood samples collected. Polybrominated, polychlorinated dioxins/ furans, and dioxin-like polychlorinated biphenyls levels compared in recyclers, non-recyclers, and National Health and Nutrition Examination Surveys (NHANES). Results: Recyclers >non-recyclers: 12378-PBDD, 2378-TBDF, 12378-PCDF, 123478-HxCDF, 123678-HxCDF, 1234678-HpCDF, PCB-126. Non-recyclers >NHANES: 123478-HxCDF, 123678-HxCDF, 234678- HxCDF, PCB-126, PCB-169. NHANES >non-recyclers: 12378-PCDD, 123478-HxCDD, 123678-HxCDD, 123789-HxCDD, 1234678-HpCDD, 123789-HxCDF, 1234678-HpCDF, 1234789-HpCDF, OCDF, PCB-81, PCB-114, …

A Strategy To Identify Event Specific Hospitalizations In Large Health Claims Databases, Joshua Lambert, Harpal Sandhu, Emily Kean, Teenu Xavier, Aviv Brokman, Zachary Steckler, Lee Park, Arnold Stromberg

Statistics Faculty Publications

Background: Health insurance claims data offer a unique opportunity to study disease distribution on a large scale. Challenges arise in the process of accurately analyzing these raw data. One important challenge to overcome is the accurate classification of study outcomes. For example, using claims data, there is no clear way of classifying hospitalizations due to a specific event. This is because of the inherent disjointedness and lack of context that typically come with raw claims data.

Methods: In this paper, we propose a framework for classifying hospitalizations due to a specific event. We then tested this framework in …

Association Of Phosphate-Containing Versus Phosphate-Free Solutions On Ventilator Days In Patients Requiring Continuous Kidney Replacement Therapy, Melissa L. Thompson Bastin, Arnold J. Stromberg, Sethabhisha N. Nerusu, Lucas J. Liu, Kirby P. Mayer, Kathleen D. Liu, Sean M. Bagshaw, Ron Wald, Peter E. Morris, Javier A. Neyra

Statistics Faculty Publications

Background and objectives Hypophosphatemia is commonly observed in patients receiving continuous KRT. Patients who develop hypophosphatemia may be at risk of respiratory and neuromuscular dysfunction and therefore subject to prolongation of ventilator support. We evaluated the association of phosphate-containing versus phosphate-free continuous KRT solutions with ventilator dependence in critically ill patients receiving continuous KRT.

Design, setting, participants, & measurements Our study was a single-center, retrospective, pre-post cohort study of adult patients receiving continuous KRT and mechanical ventilation during their intensive care unit stay. Zeroinflated negative binomial regression with and without propensity score matching was used to model our primary outcome: …