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Novel Statistical Modeling Of Sleep Patterns In Drosophila Melanogaster, Luyang Wang 2019 Missouri University of Science and Technology

Novel Statistical Modeling Of Sleep Patterns In Drosophila Melanogaster, Luyang Wang

Doctoral Dissertations

”Sleep is one of the most important behaviors in animals, yet many aspects of sleep are not well understood. In humans, sleep has been shown to impact different aspects of health and cognitive performance. The fruit fly, Drosophila melanogaster, can be used as a model organism to investigate sleep patterns over an entire lifespan. The sleep-wake status can be recorded every minute over the life of individual flies, resulting in a wealth of data for identifying meaningful aspects of sleep. In this work, a framework based on statistical modeling methods is developed for sleep data collected on fruit flies …


Cramer Type Moderate Deviations For Random Fields And Mutual Information Estimation For Mixed-Pair Random Variables, Aleksandr Beknazaryan 2019 University of Mississippi

Cramer Type Moderate Deviations For Random Fields And Mutual Information Estimation For Mixed-Pair Random Variables, Aleksandr Beknazaryan

Electronic Theses and Dissertations

In this dissertation we first study Cramer type moderate deviation for partial sums of random fields by applying the conjugate method. In 1938 Cramer published his results on large deviations of sums of i.i.d. random variables after which a lot of research has been done on establishing Cramer type moderate and large deviation theorems for different types of random variables and for various statistics. In particular results have been obtained for independent non-identically distributed random variables for the sum of independent random to estimate the mutual information between two random variables. The estimates enjoy a central limit theorem under some …


Assessing The Performance And Merit Of The Random Survival Forest And Cox Models On A Pancreatic Cancer Data Set, Carl Edward Mueller 2019 Northern Illinois University

Assessing The Performance And Merit Of The Random Survival Forest And Cox Models On A Pancreatic Cancer Data Set, Carl Edward Mueller

Graduate Research Theses & Dissertations

Random Survival Forest (RSF) is one of the most powerful and easily applied machine learning models for survival data. RSF sacrifices some of the interpretability of the decision trees used to grow the forest in order to significantly reduce the bias and variance of the basic classification and regression tree (CART) paradigm. The lessened interpretability and higher computational intensity of RSF means that it may not always be the preferred method, even in settings where black-box methods are readily used. By contrast, the Cox Proportional Hazards (PH) model is incredibly flexible, resistant to overfitting, and transparently estimable. The tradeoff for …


Bayesian Functional Data Analysis Over Dependent Regions And Its Application For Identification Of Differentially Methylated Regions, Suvo Chatterjee 2019 Northern Illinois University

Bayesian Functional Data Analysis Over Dependent Regions And Its Application For Identification Of Differentially Methylated Regions, Suvo Chatterjee

Graduate Research Theses & Dissertations

Bayesian functional data analysis (BFDA) provides flexible statistical inferences under harsh circumstances such as a large volume of data, considerable measurement errors and missing observations. Considering a sequence of segments and functional data analysis on each segment, where neighboring segments can be dependent, demanding computation is indispensable and analysis is sometimes infeasible for large number of segments. We consider a utilization of BFDA to identify differentially methylated regions (DMRs). Out of numerous existing methodologies to detect DMRs, there still does not exist a standard approach to identify DMRs especially under the assumption of dependency among genomic regions. In this dissertation, …


Simulating And Modelling Opinion Dynamics, Jennifer Heermance 2019 Northern Illinois University

Simulating And Modelling Opinion Dynamics, Jennifer Heermance

Graduate Research Theses & Dissertations

The foundation of social media is conversation. Social media allows people to share ideas and opinions, as well as discuss those opinions. A point of intrigue for many social scientists is how those opinions change through interaction with others. What influences someone’s opinion? When is a person willing to adapt their opinion, and when does it remain the same? Is it possible to measure these opinion dynamics? Our overall goal is to develop a more comprehensive model for opinion dynamics. The first step of this process is to simulate data that can then be analyzed and used to develop a …


Development Of A Data-Driven Patient Engagement Score Using Finite Mixture Models, Eric Bae 2019 South Dakota State University

Development Of A Data-Driven Patient Engagement Score Using Finite Mixture Models, Eric Bae

Electronic Theses and Dissertations

Patient activation measure (PAM) is widely adopted by health care providers to access individual's knowledge, skill, and confidence for managing one's health and healthcare. Patient activation measure (PAM), licensed by Insignia Health, is widely adopted by health care providers to access individual's knowledge, skill, and confidence for managing one's health and healthcare. Multiple studies corroborate the effectiveness of activation measure in predicting most health behaviors, including preventive behaviors, healthy behaviors, self-management behaviors, and health information seeking. However, PAM is heavily dependent on subjective patient-reported data, which are often incomplete. The purpose of this study is to develop an objective statistical …


Quasilinearization And Boundary Value Problems At Resonance For Caputo Fractional Differential Equations, Saleh S. Almuthaybiri, Paul W. Eloe, Jeffrey T. Neugebauer 2019 Qassim University

Quasilinearization And Boundary Value Problems At Resonance For Caputo Fractional Differential Equations, Saleh S. Almuthaybiri, Paul W. Eloe, Jeffrey T. Neugebauer

Mathematics Faculty Publications

The quasilinearization method is applied to a boundary value problem at resonance for a Caputo fractional differential equation. The method of upper and lower solutions is first employed to obtain the uniqueness of solutions of the boundary value problem at resonance. The shift argument is applied to show the existence of solutions. The quasilinearization algorithm is then developed and sequences of approximate solutions are constructed that converge monotonically and quadratically to the unique solution of the boundary value problem at resonance. Two applications are provided to illustrate the main results.


Robust And Adaptive Design Approaches For Stepped Wedge Cluster Randomized Trials, Jijia Wang 2019 Southern Methodist University

Robust And Adaptive Design Approaches For Stepped Wedge Cluster Randomized Trials, Jijia Wang

Statistical Science Theses and Dissertations

The stepped wedge (SW) cluster randomized design has been increasingly employed by pragmatic trials in health services research. In this study, based on the GEE approach, I present a closed-form sample size that is applicable to both closed-cohort and cross-sectional SW trials with outcomes from the exponential family. On the other hand, I proposed a Bayesian adaptive design for cross-sectional SW cluster randomized trials. It is more adaptable than traditional designs because it allows early termination of the trial when interim data indicate that the intervention is sufficient efficacious or inefficacious. A decision to terminate or continue the trial will …


Estimation And Variable Selection In High-Dimensional Settings With Mismeasured Observations, Michael Byrd 2019 Southern Methodist University

Estimation And Variable Selection In High-Dimensional Settings With Mismeasured Observations, Michael Byrd

Statistical Science Theses and Dissertations

Understanding high-dimensional data has become essential for practitioners across many disciplines. The general increase in ability to collect large amounts of data has prompted statistical methods to adapt for the rising number of possible relationships to be uncovered. The key to this adaptation has been the notion of sparse models, or, rather, models where most relationships between variables are assumed to be negligible at best. Driving these sparse models have been constraints on the solution set, yielding regularization penalties imposed on the optimization procedure. While these penalties have found great success, they are typically formulated with strong assumptions on the …


Modeling Stochastically Intransitive Relationships In Paired Comparison Data, Ryan Patrick Alexander McShane 2019 Southern Methodist University

Modeling Stochastically Intransitive Relationships In Paired Comparison Data, Ryan Patrick Alexander Mcshane

Statistical Science Theses and Dissertations

If the Warriors beat the Rockets and the Rockets beat the Spurs, does that mean that the Warriors are better than the Spurs? Sophisticated fans would argue that the Warriors are better by the transitive property, but could Spurs fans make a legitimate argument that their team is better despite this chain of evidence?

We first explore the nature of intransitive (rock-scissors-paper) relationships with a graph theoretic approach to the method of paired comparisons framework popularized by Kendall and Smith (1940). Then, we focus on the setting where all pairs of items, teams, players, or objects have been compared to …


Spatial Boundary Detection And Estimation Of Jet Stream As A Key Factor For Tornado Environments, Mingzeng Sun 2019 University at Albany, State University of New York

Spatial Boundary Detection And Estimation Of Jet Stream As A Key Factor For Tornado Environments, Mingzeng Sun

Legacy Theses & Dissertations (2009 - 2024)

Understanding the impact of spatial patterns and processing features on health is a key element in public health and epidemiology fields. This thesis investigates these fundamental tasks using two approaches: high dimensional Kolmogorov-Zurbenko Adaptive smoothing and spatial boundary identification by rolling variation algorithm.


The Effect Of Maternal Dietary Habits During Pregnancy On Neonate Leptin Methylation Patterns And Gestational Age, Sean Fitzpatrick 2019 University at Albany, State University of New York

The Effect Of Maternal Dietary Habits During Pregnancy On Neonate Leptin Methylation Patterns And Gestational Age, Sean Fitzpatrick

Legacy Theses & Dissertations (2009 - 2024)

The health of a newborn baby is inextricably linked to the health status of its mother and in turn the mother’s diet during pregnancy. Leptin (LEP) is an adipokine hormone involved in metabolism regulation and has been linked fetal development through the hypothalamic-pituitary-adrenal axis (HPA). Prior work suggests that gestational epigenetic alterations the LEP gene may be sensitive to adverse exposures during pregnancy, which in turn could explain variation in neonate outcomes. However, no prior work has examined this possibility explicitly. The objective of this study was to investigate the association between dietary patterns of mothers during pregnancy and their …


Depression, Sensation-Seeking Behavior And Violence As Mediators Of The Association Between Childhood Adversity And Substance Use Disorder, Calvin Wong 2019 University at Albany, State University of New York

Depression, Sensation-Seeking Behavior And Violence As Mediators Of The Association Between Childhood Adversity And Substance Use Disorder, Calvin Wong

Legacy Theses & Dissertations (2009 - 2024)

Background:


Evaluating The Impacts Of Antidepressant Use On The Risk Of Dementia, Ran Duan 2019 University of Kentucky

Evaluating The Impacts Of Antidepressant Use On The Risk Of Dementia, Ran Duan

Theses and Dissertations--Epidemiology and Biostatistics

Dementia is a clinical syndrome caused by neurodegeneration or cerebrovascular injury. Patients with dementia suffer from deterioration in memory, thinking, behavior and the ability to perform everyday activities. Since there are no cures or disease-modifying therapies for dementia, there is much interest in identifying modifiable risk factors that may help prevent or slow the progression of cognitive decline. Medications are a common focus of this type of research.

Importantly, according to a report from the Centers for Disease Control and Prevention (CDC), 19.1% of the population aged 60 and over report taking antidepressants during 2011-2014, and this number tends to …


Pawnee Dam Inflow Design Flood (Idf) Update And Stage-Frequency Curve Development Using Rmcrfa, Jennifer P. Christensen, Joshua J. Melliger 2019 United States Army Corps of Engineers, Omaha, Nebraska

Pawnee Dam Inflow Design Flood (Idf) Update And Stage-Frequency Curve Development Using Rmcrfa, Jennifer P. Christensen, Joshua J. Melliger

United States Geological Survey: Water Reports and Publications

Pawnee Dam is one of the ten Salt Creek Dams designed and built in the 1960s to mitigate flooding in Lincoln, Nebraska. This short paper illustrates the update of the Pawnee Dam inflow design flood (IDF) through calibration to recent high flow events and the development of its stage-frequency or hydrologic loading curve with the U.S. Army Corps of Engineers’ Risk Management Center Reservoir Frequency Analysis (RMC-RFA) model. The IDF update follows Engineering Regulation 1110-8-2, Inflow Design Flood for Dams and Reservoirs, including unit hydrograph peaking and two antecedent pool elevations. Background information on the original design of the dam …


On Cluster Robust Models, José Bayoán Santiago Calderón 2019 Claremont Graduate University

On Cluster Robust Models, José Bayoán Santiago Calderón

CGU Theses & Dissertations

Cluster robust models are a kind of statistical models that attempt to estimate parameters considering potential heterogeneity in treatment effects. Absent heterogeneity in treatment effects, the partial and average treatment effect are the same. When heterogeneity in treatment effects occurs, the average treatment effect is a function of the various partial treatment effects and the composition of the population of interest. The first chapter explores the performance of common estimators as a function of the presence of heterogeneity in treatment effects and other characteristics that may influence their performance for estimating average treatment effects. The second chapter examines various approaches …


A Geographic Study Of Lung And Bronchus Cancer Rates In Kentucky, Gabriel Njoh Dikong 2019 Walden University

A Geographic Study Of Lung And Bronchus Cancer Rates In Kentucky, Gabriel Njoh Dikong

Walden Dissertations and Doctoral Studies

The average age-adjusted incidence and mortality rates of lung and bronchus cancer is 55% and 56% higher in Kentucky than the national averages in the United States, respectively. Populations with low income and educational attainment, and those who live close to the mining regions across Kentucky are more affected by the high prevalence and resulting mortality rates of lung and bronchus cancer. This study was conducted because of the high incidence of lung and bronchus cancer and resulting mortality rates in the state of Kentucky that may not be caused solely by social and demographic factors. The theoretical foundation for …


A Geographic Study Of Lung And Bronchus Cancer Rates In Kentucky, Gabriel Njoh Dikong 2019 Walden University

A Geographic Study Of Lung And Bronchus Cancer Rates In Kentucky, Gabriel Njoh Dikong

Walden Dissertations and Doctoral Studies

The average age-adjusted incidence and mortality rates of lung and bronchus cancer is 55% and 56% higher in Kentucky than the national averages in the United States, respectively. Populations with low income and educational attainment, and those who live close to the mining regions across Kentucky are more affected by the high prevalence and resulting mortality rates of lung and bronchus cancer. This study was conducted because of the high incidence of lung and bronchus cancer and resulting mortality rates in the state of Kentucky that may not be caused solely by social and demographic factors. The theoretical foundation for …


Quantifying Human Biological Age: A Machine Learning Approach, Syed Ashiqur Rahman 2019 West Virginia University

Quantifying Human Biological Age: A Machine Learning Approach, Syed Ashiqur Rahman

Graduate Theses, Dissertations, and Problem Reports (ETD)

Quantifying human biological age is an important and difficult challenge. Different biomarkers and numerous approaches have been studied for biological age prediction, each with its advantages and limitations. In this work, we first introduce a new anthropometric measure (called Surface-based Body Shape Index, SBSI) that accounts for both body shape and body size, and evaluate its performance as a predictor of all-cause mortality. We analyzed data from the National Health and Human Nutrition Examination Survey (NHANES). Based on the analysis, we introduce a new body shape index constructed from four important anthropometric determinants of body shape and body size: body …


An Overview And Evaluation Of Synthetc: A Statistical Model For Extra-Tropical Cyclones, Rafael Uryayev 2019 CUNY City College

An Overview And Evaluation Of Synthetc: A Statistical Model For Extra-Tropical Cyclones, Rafael Uryayev

Dissertations and Theses

Extratropical cyclones (ETCs) are the most common weather phenomena affecting the United States, Canada, and Europe. They can pose serious hazards over large swaths of area. In this thesis, a statistical model of ETCs, called SynthETC, is discussed. The model accounts for the for genesis, track path, termination, and intensity of statistically generated ETCs. Genesis is modeled as a Poisson process, whose mean is determined by climate and historical information. Tracks are modeled as a regression-mean determined by climate and historical information plus a stochastic component. Lysis is modeled using logistic regression, with climate states as covariates. Intensity is modeled …


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