Biostatistics Commons^™

Semiparametric And Nonparametric Methods For Comparing Biomarker Levels Between Groups, Yuntong Li

Theses and Dissertations--Statistics

Comparing the distribution of biomarker measurements between two groups under either an unpaired or paired design is a common goal in many biomarker studies. However, analyzing biomarker data is sometimes challenging because the data may not be normally distributed and contain a large fraction of zero values or missing values. Although several statistical methods have been proposed, they either require data normality assumption, or are inefficient. We proposed a novel two-part semiparametric method for data under an unpaired setting and a nonparametric method for data under a paired setting. The semiparametric method considers a two-part model, a logistic regression for …

Estimation Of The Treatment Effect With Bayesian Adjustment For Covariates, Li Xu

Theses and Dissertations--Statistics

The Bayesian adjustment for confounding (BAC) is a Bayesian model averaging method to select and adjust for confounding factors when evaluating the average causal effect of an exposure on a certain outcome. We extend the BAC method to time-to-event outcomes. Specifically, the posterior distribution of the exposure effect on a time-to-event outcome is calculated as a weighted average of posterior distributions from a number of candidate proportional hazards models, weighing each model by its ability to adjust for confounding factors. The Bayesian Information Criterion based on the partial likelihood is used to compare different models and approximate the Bayes factor. …

Spatial And Temporal Genetic Structure Of Winter-Run Steelhead (Oncorhynchus Mykiss) Returning To The Mad River, California, Steven R. Fong

Cal Poly Humboldt theses and projects

Distinct populations of steelhead in the wild are in decline. The propagation of steelhead in hatcheries has been used to boost population numbers for recreational fisheries and for use in conservation. However, hatchery breeding practices of steelhead can result in changes in genetic structure. I investigated the genetic structure of winter-run steelhead (Oncorhynchus mykiss) returning to the Mad River, California, where a hatchery has been used enhance production for recreational fisheries since 1971. Genetic variability in Mad River steelhead was evaluated using 96 single nucleotide polymorphisms (SNPs) among 4203 individuals, including the Mad River and nearby locations, and …

Short-Term Effects Of Ambient Ozone, Pm2. 5, And Meteorological Factors On Covid-19 Confirmed Cases And Deaths In Queens, New York., Atin Adhikari, Jingjing Yin

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

The outbreak of coronavirus disease 2019 (COVID-19), caused by the virus SARS-CoV-2, has been rapidly increasing in the United States. Boroughs of New York City, including Queens county, turn out to be the epicenters of this infection. According to the data provided by the New York State Department of Health, most of the cases of new COVID-19 infections in New York City have been found in the Queens county where 42,023 people have tested positive, and 3221 people have died as of 20 April 2020. Person-to-person transmission and travels were implicated in the initial spread of the outbreaks, but factors …

Molecular Typing Of Rickettsia Akari, Marina E. Eremeeva

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Rickettsia akari is an obligate intracellular bacterium that causes smallpox rickettsia. Rickettsia akari is an atypical member of the rickettsia spotted fever (SFG) group because it circulates in gamasid mites; however, only limited data are available regarding the degree of genetic diversity of R. akari isolates. We examined 13 isolates of R. akari isolated from humans, rodents, and ticks in the United States, the countries of the former USSR, and the former Yugoslavia for the period from 1946 to 2003 for diversity in the composition of tandem repeats (TR) and intergenic regions (IGR). Using the Tandem Repeat Finder software (http://tandem.bu.edu) …

Bayesian Kinetic Modeling For Tracer-Based Metabolomic Data, Xu Zhang

Theses and Dissertations--Statistics

Kinetic modeling of the time dependence of metabolite concentrations including the unstable isotope labeled species is an important approach to simulate metabolic pathway dynamics. It is also essential for quantitative metabolic flux analysis using tracer data. However, as the metabolic networks are complex including extensive compartmentation and interconnections, the parameter estimation for enzymes that catalyze individual reactions needed for kinetic modeling is challenging. As the pa- rameter space is large and multi-dimensional while kinetic data are comparatively sparse, the estimation procedure (especially the point estimation methods) often en- counters multiple local maximum such that standard maximum likelihood methods may yield …

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 …

Accounting For The Uncertainty Due To Chemicals Below The Detection Limit In Mixture Analysis, Paul M. Hargarten

Theses and Dissertations

Humans are exposed to multiple chemicals every day. Epidemiological studies have shown that chemical mixtures are associated with cancers, allergies, neurodevelopmental disorders, and other adverse health effects. To assess these associations, investigators are increasingly using chemical mixture approaches like weighted quantile sum (WQS) regression. In these studies, the research objectives are to determine whether a mixture of correlated chemicals is associated with an adverse health outcome and to identify the important chemicals. However, as experimental equipment measures each exposure to a chemical-specific detection limit, the exposures are unknown between zero and the detection limit. Indeed, the number of exposures below …

Distribution Of Human Exposure To Ozone During Commuting Hours In Connecticut Using The Cellular Device Network, Owais Gilani, Simon Urbanek, Michael J. Kane

Faculty Journal Articles

Epidemiologic studies have established associations between various air pollutants and adverse health outcomes for adults and children. Due to high costs of monitoring air pollutant concentrations for subjects enrolled in a study, statisticians predict exposure concentrations from spatial models that are developed using concentrations monitored at a few sites. In the absence of detailed information on when and where subjects move during the study window, researchers typically assume that the subjects spend their entire day at home, school, or work. This assumption can potentially lead to large exposure assignment bias. In this study, we aim to determine the distribution of …

Lifestyle Factors And Social Determinants As Predictors Of Weight/Body Mass Index, Uthman Alhaji Baba

Walden Dissertations and Doctoral Studies

Obesity is a major public health concern that includes the risk of developing cardiovascular disease and premature death in adults. Previous studies have established the relationship between gender, educational level, household income and respondents’ weight but additional research is needed to factor the nature of education in relation to gender differences, diet, and other important behavioral mediators such as social determinants. The purpose of this quantitative cross-sectional study is to determine the extent to which frequency of physical activity, household income, social determinants of health (money for balanced meals, finances at the end of month, and poor mental health), respondent …

Estimating Response Status In Sequential Multiple Assignment (Smar)-Like Trials, Keighly Bradbrook

Theses and Dissertations

Sequential, multiple assignment, randomized trials (SMARTs) allow investigators to develop and compare experimental treatment regimens in which individuals are successively randomized to different treatments based on some set of predetermined rules. The rules used to make decisions on when and how to switch treatments are based on a chosen set of tailoring variables. Although not always true, intermediate response is commonly used as the primary tailoring variable as it is often predictive of future treatment success. As such, successful implementation depends on identifying patients who respond to treatment, though in some situations such mechanisms may not exist. Further, patient-level covariates …

The Analysis Of Neural Heterogeneity Through Mathematical And Statistical Methods, Kyle Wendling

Theses and Dissertations

Diversity of intrinsic neural attributes and network connections is known to exist in many areas of the brain and is thought to significantly affect neural coding. Recent theoretical and experimental work has argued that in uncoupled networks, coding is most accurate at intermediate levels of heterogeneity. I explore this phenomenon through two distinct approaches: a theoretical mathematical modeling approach and a data-driven statistical modeling approach.

Through the mathematical approach, I examine firing rate heterogeneity in a feedforward network of stochastic neural oscillators utilizing a high-dimensional model. The firing rate heterogeneity stems from two sources: intrinsic (different individual cells) and network …

Rickettsialpox – A Rare But Not Extinct Disease: A Review Of The Literature And New Directions, Marina Eremeeva, Kamalich Muniz-Rodriguez

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Smallpox rickettsia is an urban zoonosis caused by Rickettsia akari. To date, R. akari is the only characterized representative of the group of spotted fevers transmitted by the gamasid mite Liponyssoides sanguineus, which is common among peridomic rodents. This disease was first described in New York in 1946, and a few years later a similar outbreak occurred in the Ukrainian SSR. Numerous serological studies and diagnostics of sporadic cases of smallpox rickettsiosis suggest its widespread occurrence on the planet; however, the current geography and incidence of smallpox rickettsiosis is unknown. Smallpox rickettsiosis is characterized by the classic clinical triad of …

Multiple Imputation Using Influential Exponential Tilting In Case Of Non-Ignorable Missing Data, Kavita Gohil

College of Graduate Studies: Theses & Dissertations

Modern research strategies rely predominantly on three steps, data collection, data analysis, and inference. In research, if the data is not collected as designed, researchers may face challenges of having incomplete data, especially when it is non-ignorable. These situations affect the subsequent steps of evaluation and make them difficult to perform. Inference with incomplete data is a challenging task in data analysis and clinical trials when missing data related to the condition under the study. Moreover, results obtained from incomplete data are prone to biases. Parameter estimation with non-ignorable missing data is even more challenging to handle and extract useful …

Nonparametric Misclassification Simulation And Extrapolation Method And Its Application, Congjian Liu

College of Graduate Studies: Theses & Dissertations

The misclassification simulation extrapolation (MC-SIMEX) method proposed by Küchenho et al. is a general method of handling categorical data with measurement error. It consists of two steps, the simulation and extrapolation steps. In the simulation step, it simulates observations with varying degrees of measurement error. Then parameter estimators for varying degrees of measurement error are obtained based on these observations. In the extrapolation step, it uses a parametric extrapolation function to obtain the parameter estimators for data with no measurement error. However, as shown in many studies, the parameter estimators are still biased as a result of the parametric extrapolation …

Generalization Of Kullback-Leibler Divergence For Multi-Stage Diseases: Application To Diagnostic Test Accuracy And Optimal Cut-Points Selection Criterion, Chen Mo

College of Graduate Studies: Theses & Dissertations

The Kullback-Leibler divergence (KL), which captures the disparity between two distributions, has been considered as a measure for determining the diagnostic performance of an ordinal diagnostic test. This study applies KL and further generalizes it to comprehensively measure the diagnostic accuracy test for multi-stage (K > 2) diseases, named generalized total Kullback-Leibler divergence (GTKL). Also, GTKL is proposed as an optimal cut-points selection criterion for discriminating subjects among different disease stages. Moreover, the study investigates a variety of applications of GTKL on measuring the rule-in/out potentials in the single-stage and multi-stage levels. Intensive simulation studies are conducted to compare the performance …

Adjusting For Dropout In Randomized Controlled Clinical Trials, Katharine Stromberg

Theses and Dissertations

Dropout is a common issue in randomized controlled clinical trials and can negatively impact the internal validity of a study and potentially bias the treatment effect. When subjects discontinue study participation, they are not being given the opportunity to gain from the investigational therapy as if they had remained in the study, defeating one of the main purposes of clinical trials, providing treatment. Specifically in unblinded studies, such as the wait-list control (WLC) design, dropout is often due to group membership. Subjects allocated to the control group often dropout at higher rates than in the treatment group. Adaptive designs have …

Sex And Age Differences In Prevalence And Risk Factors For Prediabetes In Mexican-Americans, Kristina Vatcheva, Belinda M. Reininger, Susan P. Fisher-Hoch, Joseph B. Mccormick

School of Mathematical & Statistical Sciences Faculty Publications

AIMS:

Over 1/3 of Americans have prediabetes, while 9.4% have type 2 diabetes. The aim of our study was to estimate the prevalence of prediabetes in Mexican Americans, with known 28.2% prevalence of type 2 diabetes, by age and sex and to identify critical socio-demographic and clinical factors associated with prediabetes.

METHODS:

Data were collected between 2004 and 2017 from the Cameron County Hispanic Cohort in Texas. Weighted crude and sex- and age- stratified prevalences were calculated. Survey weighted logistic regression analyses were conducted to identify risk factors for prediabetes.

RESULTS:

The prevalence of prediabetes (32%) was slightly higher than …

Social Ecological Factors Affecting Substance Abuse In Ghana (West Africa) Using Photovoice, Ahmed Kabore, Evans Afriyie-Gyawu, James Awuah, Andrew R. Hansen, Ashley Walker, Melissa Hester, Moussa Aziz Wonadé Sié, Dhruv Medarametla, Nicolas Meda

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Introduction: substance abuse is an important public health issue affecting West Africa; however, there is currently a dearth of literature on the actions needed to address it. The aim of this study was to assess the risks and protective factors of substance abuse in Ghana, West Africa, using the photovoice method.

Methods: this study recruited and trained 10 participants in recovery from substance abuse and undergoing treatment in the greater Accra region of Ghana on the photovoice methodology. Each participant received a disposable camera to take pictures that represented the risk and protective factors pertinent to substance abuse …

Generalized Matrix Decomposition Regression: Estimation And Inference For Two-Way Structured Data, Yue Wang, Ali Shojaie, Tim Randolph, Jing Ma

UW Biostatistics Working Paper Series

Analysis of two-way structured data, i.e., data with structures among both variables and samples, is becoming increasingly common in ecology, biology and neuro-science. Classical dimension-reduction tools, such as the singular value decomposition (SVD), may perform poorly for two-way structured data. The generalized matrix decomposition (GMD, Allen et al., 2014) extends the SVD to two-way structured data and thus constructs singular vectors that account for both structures. While the GMD is a useful dimension-reduction tool for exploratory analysis of two-way structured data, it is unsupervised and cannot be used to assess the association between such data and an outcome of interest. …