Vital and Health Statistics Commons^™

Dynamic Prediction For Alternating Recurrent Events Using A Semiparametric Joint Frailty Model, Jaehyeon Yun

Statistical Science Theses and Dissertations

Alternating recurrent events data arise commonly in health research; examples include hospital admissions and discharges of diabetes patients; exacerbations and remissions of chronic bronchitis; and quitting and restarting smoking. Recent work has involved formulating and estimating joint models for the recurrent event times considering non-negligible event durations. However, prediction models for transition between recurrent events are lacking. We consider the development and evaluation of methods for predicting future events within these models. Specifically, we propose a tool for dynamically predicting transition between alternating recurrent events in real time. Under a flexible joint frailty model, we derive the predictive probability of …

Concerns With Taking The Covid-19 Vaccine, Kaela Bellamy, Robert S. Keyser

The Kennesaw Journal of Undergraduate Research

This IRB-approved descriptive study provides an overview of the concerns associated with receiving a COVID-19 vaccination within the Kennesaw State University community, an R2 university with over 41,000 students, and uses a survey to provide insight into how students, faculty, staff, and administrators are responding to the vaccinations for COVID-19, both available and unavailable, and their preferences. Our research findings indicate that: 1) Most of the population at Kennesaw State University intends to receive the vaccine, regardless of their concerns; 2) The majority of the participants who are either employed or provided an education by Kennesaw State University plan to …

Intervention Time Series Analysis Of Organ Donor Transplants In The Us, Supraja Malladi

Biology and Medicine Through Mathematics Conference

No abstract provided.

Anti-Vaxxers: Parents Fighting Science, Katie West

Symposium of Student Scholars

Immunizing children helps protect the health of our community, especially those people who cannot be immunized. Yet, since 1996 after a study was released that linked autism to vaccinations, there has been a trend of parents refusing to vaccinate their children. What are the demographics of the parents who believe their children are better off without vaccines? By knowing where these parents live and what decisions they make for their children’s education, counties and medical professionals can provide education and address their concerns.

My research involves data on 116,141 kindergarten classes from 2000-2015 in California. The two vaccine exemption options …

Modeling Covid-19 Spread In Small Colleges, Riti Bahl, Nicole Eikmeier, Alexandra Fraser, Matthew Junge, Felicia Keesing, Kukai Nakahata, Lily Reeves

Publications and Research

We develop an agent-based model on a network meant to capture features unique to COVID-19 spread through a small residential college. We find that a safe reopening requires strong policy from administrators combined with cautious behavior from students. Strong policy includes weekly screening tests with quick turnaround and halving the campus population. Cautious behavior from students means wearing facemasks, socializing less, and showing up for COVID-19 testing. We also find that comprehensive testing and facemasks are the most effective single interventions, building closures can lead to infection spikes in other areas depending on student behavior, and faster return of test …

Asymptotic Results For Empirical Processes In Informative Model Of Random Censorship From Both Sides, Abdurakhim Abdushukurov, Dilshod Mansurov

Bulletin of National University of Uzbekistan: Mathematics and Natural Sciences

In the paper, the empirical process in informative model of random censorship from both sides is investigated. For it, the limit Gaussian process with mean zero is founded. Under investigating of empirical process, the characterization properties of the considered informative model is used. The properties of the semiparametric estimator by using methods of numerical modeling are discussed.

Em Estimation For Zero- And K-Inflated Poisson Regression Model, Monika Arora, N. Rao Chaganty

Mathematics & Statistics Faculty Publications

Count data with excessive zeros are ubiquitous in healthcare, medical, and scientific studies. There are numerous articles that show how to fit Poisson and other models which account for the excessive zeros. However, in many situations, besides zero, the frequency of another count k tends to be higher in the data. The zero- and k-inflated Poisson distribution model (ZkIP) is appropriate in such situations The ZkIP distribution essentially is a mixture distribution of Poisson and degenerate distributions at points zero and k. In this article, we study the fundamental properties of this mixture distribution. Using stochastic representation, we …

Use Of Advanced Statistical Techniques To Predict All-Cause Mortality In The Systolic Blood Pressure Intervention Trial, William Kostis, Javier Cabrera, Chun Pang Lin, John Kostis, Jennifer Wellings, Stavros Zinonos, Jeanne Dobrzynski, Daniel Blickstein

Department of Medicine Faculty Papers

Background: The Systolic Blood Pressure Intervention Trial (SPRINT) was conducted in patients with hypertension and additional risk for cardiovascular disease who were randomized to the intensive blood pressure group targeting systolic blood pressure (SBP) less than 120 mm Hg and to the standard group where the target was less than 140 mm Hg. Analyses were done in the matched group of participants with the same gender, same age (±2 years) and same SBP (±3 mm Hg) at three months of treatment regardless of initial randomization to intensive or standard group (shaded area in Figure 1). Methods and results: During 3.26 …

Improving The Quality And Design Of Retrospective Clinical Outcome Studies That Utilize Electronic Health Records, Oliwier Dziadkowiec, Jeffery Durbin, Vignesh Jayaraman Muralidharan, Megan Novak, Brendon Cornett

HCA Healthcare Journal of Medicine

Electronic health records (EHRs) are an excellent source for secondary data analysis. Studies based on EHR-derived data, if designed properly, can answer previously unanswerable clinical research questions. In this paper we will highlight the benefits of large retrospective studies from secondary sources such as EHRs, examine retrospective cohort and case-control study design challenges, as well as methodological and statistical adjustment that can be made to overcome some of the inherent design limitations, in order to increase the generalizability, validity and reliability of the results obtained from these studies.

Pattern Of Health Behavior And Its Association With Self-Rated Health: Evidence From The 2018 Behavioral Risk Factor Surveillance System In The United States, Linh Nguyen, Mamunur Rashid, M. Mazharul Islam

Student Research

Aim: To improve public health services, we need to keep policymakers updated with health-related issues. This study (1) examines the recent pattern of physical activities, smoking, alcohol consumption, and SRH, and (2) investigates the association between the behaviors and SRH status among US citizens.

Method: We extracted data from the latest state-based survey of the 2018 Behavioral Risk Factor Surveillance System (BRFSS), which provides a nationally representative sample of 437,436 American adults. We analyzed the data, mainly employing chi-square tests and logistic regression models.

Results: Physical inactivity and smoking are more common among participants with lower education and household income. …

Life And Death: Quantifying The Risk Of Heart Disease With Machine Learning, Jack Scott Glienke

Honors Program Theses

Coronary heart disease has long been a key area of focus in the discussion of public health. As such, numerous studies have been conducted throughout history with the sole intention of identifying risk factors leading to the onset of cardiovascular conditions. A plethora of statistical procedures can be used to identify an individual’s risk of developing heart disease, yet regression models tend to be the default tool used by researchers. Using the data obtained from the most influential cardiovascular study to date, the Framingham Heart Study, this analysis uses machine learning techniques to generate and test the predictive power of …

Personal Foul: How Head Trauma And The Insurance Industry Are Threatening Sports, Zachary Cooler

Senior Honors Theses

This thesis will investigate the growing problem of head trauma in contact sports like football, hockey, and soccer through medical studies, implications to the insurance industry, and ongoing litigation. The thesis will investigate medical studies that are finding more evidence to support the claim that contact sports players are more likely to receive head trauma symptoms such as memory loss, mood swings, and even Lou Gehrig’s disease in extreme cases. The thesis will also demonstrate that these medical symptoms and monetary losses from medical claims are convincing insurance companies to withdraw insurance coverage for sports leagues, which they are justifying …

Bayesian Methods For The Assessment Of Reporting Errors For Data-Sparse Population-Periods With Applications To Estimating Mortality, Emily Peterson

Doctoral Dissertations

Population level mortality data is often subject to substantial reporting errors due to misclassification of cause of death, misclassification of death status, or age reporting errors. Accuracy of error-prone data sources can be assessed by comparing such data to gold standard data for the same population-period. We present Bayesian methods for assessing the extent of reporting errors across different population-periods and generalizing those to settings where gold-standard data are lacking. Firstly, we investigate misclassification errors of maternal cause of death reporting in civil registration vital statistics data. We use a Bayesian hierarchical bivariate random-walk model to estimate country-year specific sensitivity …

Measuring Change: Prediction Of Early Onset Sepsis, Aric Schadler

Theses and Dissertations--Statistics

Sepsis occurs in a patient when an infection enters into the blood stream and spreads throughout the body causing a cascading response from the immune system. Sepsis is one of the leading causes of morbidity and mortality in today’s hospitals. This is despite published and accepted guidelines for timely and appropriate interventions for septic patients. The largest barrier to applying these interventions is the early identification of septic patients. Early identification and treatment leads to better outcomes, shorter lengths of stay, and financial savings for healthcare institutions. In order to increase the lead time in recognizing patients trending towards septicemia …

The Experiences Of Ncaa Student-Athletes With An Eating Disorder Or Disordered Eating, Rachel E. Taylor

Electronic Theses and Dissertations

The purpose of this study was to explore the experiences of student-athletes who had an eating disorder or disordered eating (ED/DE) while competing for the National Collegiate Athletic Association (NCAA). Integrating criticism and connoisseurship and critical evocative portraiture, four post-collegiate women who participated in cross country and track, who were either clinically diagnosed with an ED/DE or who self-diagnosed, participated in two interviews to describe their experiences with and the impact of ED/DE on their athletic pursuits, academic pursuits, as well as their relationships with coaches, teammates, and family. The analysis of these interviews showed the complexity of this topic. …

Three Essays On Health Economics And Policy Evaluation, Shishir Shakya

Graduate Theses, Dissertations, and Problem Reports

This dissertation consists of three essays on the U.S. Health care policy. Each paragraph below refers to the three abstracts for the three chapters in this dissertation, respectively. I provide quantitative evidence on how much Prescription Drug Monitoring Programs (PDMPs) affects the retail opioid prescribing behaviors. Using the American Community Survey (ACS), I retrieve county-level high dimensional panel data set from 2010 to 2017. I employ three separate identification strategies: difference-in-difference, double selection post-LASSO, and spatial difference-in-difference. I compare how the retail opioid prescribing behaviors of counties, that are mandatory for prescribers to check the PDMP before prescribing controlled substances …

A Mathematical Model For Malaria With Age-Heterogeneous Biting Rate, Sho Kawakami

All Graduate Theses, Dissertations, and Other Capstone Projects

We propose a mathematical model for malaria with age-heterogeneous biting rate from mosquitos. The existence of the model, the local behavior of the disease free equilibrium are explored. Furthermore the model is extended to an optimal control problem and the corresponding adjoint equations and optimality conditions are derived. Age dependent parameter values are estimated and numerical simulations are carried out for the model. The new model better accounts for difference in biting rates of mosquitos to different age groups, and improvements in stability to the explicit algorithm. The optimal control is also shown to depend on the age distribution of …

Detecting Differentially Co-Expressed Gene Modules Via The Edge-Count Test, Anne Gratius Lin

Graduate Theses and Dissertations

Background

Gene expression profiling by microarray has been used to uncover molecular variations in many different diseases. Complementary to conventional differential expression analysis, differential co-expression analysis can identify gene markers from the systematic and granular level. There are three aspects for differential co-expression network analysis, including the network global topological comparison, differential co-expression cluster identification, and differential co-expressed genes and gene pair identification. To date, most of the methods available still rely on Pearson’s correlation coefficient despite its nonlinear insensitivity.

Results

Here we present an approach that is robust to nonlinearity by using the edge-count test for differential co-expression analysis. …

Identifying Risk Factors Related To Premature Birth Through Binary Logistic And Proportional Odds Ordinal Logistic Regression, Clayton Elwood

Electronic Theses and Dissertations

Premature birth has been identified as the single greatest cause of death worldwide in children under the age of five. This thesis will implement binary logistic regression and proportional odds ordinal logistic regression to predict different levels of premature birth and identify associated risk factors. The models will be built from the Center for Disease Control and Prevention's 2014 Vital Statistics Natality Birth Data containing nearly 4 million live births within the United States. Odds ratios and confidence intervals on risk factors were produced utilizing binary logistic regression.

Sickle Cell Disease Complications: Prevalence And Resource Utilization, Nirmish Shah, Menaka Bhor, Lin Xi, Jincy Paulose, Huseyin Yuce

Publications and Research

Objectives: This study evaluated the prevalence rate of vaso-occlusive crisis (VOC) episodes, rates of uncomplicated and complicated VOC episodes, and the primary reasons for emergency room (ER) visits and inpatient admissions for sickle cell disease (SCD) patients.

Methods: The Medicaid Analytic extracts database was used to identify adult SCD patients using claims from 01JUL2009-31DEC2012. The date of the first observed SCD claim was designated as the index date. Patients were required to have continuous medical and pharmacy benefits for .6 months baseline and .12 months follow-up period. Patient demographics, baseline clinical characteristics, the rate of uncomplicated and complicated VOC (VOC …