Cellulose Nanofiber-Reinforced Impact Modified Polypropylene: Assessing Material Properties From Fused Layer Modeling And Injection Molding Processing, 2017 University of maine
Cellulose Nanofiber-Reinforced Impact Modified Polypropylene: Assessing Material Properties From Fused Layer Modeling And Injection Molding Processing, Jordan Elliott Sanders
Electronic Theses and Dissertations
The purpose of this research was to investigate the use of cellulose nanofibers (CNF) compounded into an impact modified polypropylene (IMPP) matrix. A IMPP was used because it shrinks less than a PP homopolymer during FLM processing. An assessment of material properties from fused layer modeling (FLM), an additive manufacturing (AM) method, and injection molding (IM) was conducted. Results showed that material property measurements in neat PP were statistically similar between IM and FLM for density, strain at yield and flexural stiffness. Additionally, PP plus the coupling agent maleic anhydride (MA) showed statistically similar results in comparison of IM and …
Making Models With Bayes, 2017 California State University, San Bernardino
Making Models With Bayes, Pilar Olid
Electronic Theses, Projects, and Dissertations
Bayesian statistics is an important approach to modern statistical analyses. It allows us to use our prior knowledge of the unknown parameters to construct a model for our data set. The foundation of Bayesian analysis is Bayes' Rule, which in its proportional form indicates that the posterior is proportional to the prior times the likelihood. We will demonstrate how we can apply Bayesian statistical techniques to fit a linear regression model and a hierarchical linear regression model to a data set. We will show how to apply different distributions to Bayesian analyses and how the use of a prior affects …
Variational Bayes Estimation Of Discrete-Margined Copula Models With Application To Ime Series, 2017 Melbourne Business School
Variational Bayes Estimation Of Discrete-Margined Copula Models With Application To Ime Series, Ruben Loaiza-Maya, Michael S. Smith
Michael Stanley Smith
On The Estimation Of Penetrance In The Presence Of Competing Risks With Family Data, 2017 The University of Western Ontario
On The Estimation Of Penetrance In The Presence Of Competing Risks With Family Data, Daniel Prawira
Electronic Thesis and Dissertation Repository
In family studies, we are interested in estimating the penetrance function of the event of interest in the presence of competing risks. Failure to account for competing risks may lead to bias in the estimation of the penetrance function. In this thesis, three statistical challenges are addressed: clustering, missing data, and competing risks. We proposed the cause-specific model with shared frailty and ascertainment correction to account for clustering and competing risks along with ascertainment of families into study. Multiple imputation is used to account for missing data. The simulation study showed good performance of our proposed model in estimating the …
A Cross-Sectional Exploration Of Household Financial Reactions And Homebuyer Awareness Of Registered Sex Offenders In A Rural, Suburban, And Urban County., 2017 University of Louisville
A Cross-Sectional Exploration Of Household Financial Reactions And Homebuyer Awareness Of Registered Sex Offenders In A Rural, Suburban, And Urban County., John Charles Navarro
Electronic Theses and Dissertations
As stigmatized persons, registered sex offenders betoken instability in communities. Depressed home sale values are associated with the presence of registered sex offenders even though the public is largely unaware of the presence of registered sex offenders. Using a spatial multilevel approach, the current study examines the role registered sex offenders influence sale values of homes sold in 2015 for three U.S. counties (rural, suburban, and urban) located in Illinois and Kentucky within the social disorganization framework. Homebuyers were surveyed to examine whether awareness of local registered sex offenders and the homebuyer’s community type operate as moderators between home selling …
Burden Of Atopic Dermatitis In The United States: Analysis Of Healthcare Claims Data In The Commercial, Medicare, And Medi-Cal Databases, 2017 STATinMED Research/SIMR, Inc.
Burden Of Atopic Dermatitis In The United States: Analysis Of Healthcare Claims Data In The Commercial, Medicare, And Medi-Cal Databases, Sulena Shrestha, Raymond Miao, Li Wang, Jingdong Chao, Huseyin Yuce, Wenhui Wei
Publications and Research
Comparative data on the burden of atopic dermatitis (AD) in adults relative to the general population are limited. We performed a large-scale evaluation of the burden of disease among US adults with AD relative to matched non-AD controls, encompassing comorbidities, healthcare resource utilization (HCRU), and costs, using healthcare claims data. The impact of AD disease severity on these outcomes was also evaluated.
Statistical Methods On Risk Management Of Extreme Events, 2017 University of Massachusetts Amherst
Statistical Methods On Risk Management Of Extreme Events, Zijing Zhang
Doctoral Dissertations
The goal of the dissertation is the investigation of financial risk analysis methodologies, using the schemes for extreme value modeling as well as techniques from copula modeling. Extreme value theory is concerned with probabilistic and statistical questions re- lated to unusual behavior or rare events. The subject has a rich mathematical theory and also a long tradition of applications in a variety of areas. We are interested in its application in risk management, with a focus on estimating and forcasting the Value-at-Risk of financial time series data. Extremal data are inherently scarce, thus making inference challenging. In order to obtain …
Failure Of Care Acquisition: Identifying Risk Factors In American Health Disparities, 2017 DePauw University
Failure Of Care Acquisition: Identifying Risk Factors In American Health Disparities, Nicholas Downing, Mamunur Rashid
Student Research
We examined the effects of various demographic and socioeconomic risk factors that influence an adult's decision not to obtain medical care in the United States utilizing data from the 2015 National Health Interview Survey (NHIS). Bivariate analysis and multivariate logistic regression revealed that family income, insurance status and whether one worries about paying medical bills make individuals nearly 80% less likely to obtain care than their counterparts. This study provides evidence that certain risk factors, especially those directly related to one's socioeconomic status, may put individuals at greater risk for failure to obtain care. Interventions in policy may be needed …
An Investigation Of The Accuracy Of Parallel Analysis For Determining The Number Of Factors In A Factor Analysis, 2017 Western Kentucky University
An Investigation Of The Accuracy Of Parallel Analysis For Determining The Number Of Factors In A Factor Analysis, Mandy Matsumoto
Mahurin Honors College Capstone Experience/Thesis Projects
Exploratory factor analysis is an analytic technique used to determine the number of factors in a set of data (usually items on a questionnaire) for which the factor structure has not been previously analyzed. Parallel analysis (PA) is a technique used to determine the number of factors in a factor analysis. There are a number of factors that affect the results of a PA: the choice of the eigenvalue percentile, the strength of the factor loadings, the number of variables, and the sample size of the study. Although PA is the most accurate method to date to determine which factors …
Marketing The Mountain State: A Large N Study Of User Engagement On Twitter, 2017 Illinois State University
Marketing The Mountain State: A Large N Study Of User Engagement On Twitter, Kirk Richardson
Capstone Projects – Politics and Government
Much of the evolving research on the use of social media in destination marketing emphasizes how information diffusion influences the reputational image of place. The present study uses Twitter data to focus on the relative differences in user engagement across discrete account types. Specifically, this is done to examine how the official destination marketing organization of Montana—the Montana Office of Tourism (MTOT)—performs relative to other account types. Several regression analyses conducted on Twitter data associated with an ongoing MTOT place branding campaign reveal that tweets sent from ‘official’ accounts are more likely to be retweeted, and are estimated to receive …
Modelling Cash Crop Growth In Tn, 2017 University of Tennessee
Modelling Cash Crop Growth In Tn, Spencer Weston
Chancellor’s Honors Program Projects
No abstract provided.
Detecting And Evaluating Therapy Induced Changes In Radiomics Features Measured From Non-Small Cell Lung Cancer To Predict Patient Outcomes, 2017 The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences
Detecting And Evaluating Therapy Induced Changes In Radiomics Features Measured From Non-Small Cell Lung Cancer To Predict Patient Outcomes, Xenia J. Fave
Dissertations & Theses (Open Access)
The purpose of this study was to investigate whether radiomics features measured from weekly 4-dimensional computed tomography (4DCT) images of non-small cell lung cancers (NSCLC) change during treatment and if those changes are prognostic for patient outcomes or dependent on treatment modality. Radiomics features are quantitative metrics designed to evaluate tumor heterogeneity from routine medical imaging. Features that are prognostic for patient outcome could be used to monitor tumor response and identify high-risk patients for adaptive treatment. This would be especially valuable for NSCLC due to the high prevalence and mortality of this disease.
A novel process was designed to …
Performance Of Imputation Algorithms On Artificially Produced Missing At Random Data, 2017 East Tennessee State University
Performance Of Imputation Algorithms On Artificially Produced Missing At Random Data, Tobias O. Oketch
Electronic Theses and Dissertations
Missing data is one of the challenges we are facing today in modeling valid statistical models. It reduces the representativeness of the data samples. Hence, population estimates, and model parameters estimated from such data are likely to be biased.
However, the missing data problem is an area under study, and alternative better statistical procedures have been presented to mitigate its shortcomings. In this paper, we review causes of missing data, and various methods of handling missing data. Our main focus is evaluating various multiple imputation (MI) methods from the multiple imputation of chained equation (MICE) package in the statistical software …
Network Exploration Of Correlated Multivariate Protein Data For Alzheimer's Disease Association, 2017 University of Missouri-St. Louis
Network Exploration Of Correlated Multivariate Protein Data For Alzheimer's Disease Association, Matthew J. Lane
Theses
Alzheimer Disease (AD) is difficult to diagnose by using genetic testing or other traditional methods. Unlike diseases with simple genetic risk components, there exists no single marker determining as to whether someone will develop AD. Furthermore, AD is highly heterogeneous and different subgroups of individuals develop the disease due to differing factors. Traditional diagnostic methods using perceivable cognitive deficiencies are often too little too late due to the brain having suffered damage from decades of disease progression. In order to observe AD at early stages prior to the observation of cognitive deficiencies, biomarkers with greater accuracy are required. By using …
Statistically Analyzing Assembly Line Processing Times Through Incorporation Of Product Variation, 2017 Murray State University
Statistically Analyzing Assembly Line Processing Times Through Incorporation Of Product Variation, Kyle Rehr, Matthew Farr
Scholars Week
Timing methods and performance metrics are important in the heavily industrialized world we live in. Industrial plants use metrics to measure quality of production, help make decisions, and drive the strategy of the organization. However, there are many factors to be considered when measuring performance based on a metric; of which we will be analyzing the importance of product variation. We will be analyzing assembly line timings, whilst controlling for product variance, to show the importance differences between products makes in one’s ability to predict performance. In addition, we will be analyzing the current “statistical” methods used by an industrial …
The Interactions Of Relationships, Interest, And Self-Efficacy In Undergraduate Physics, 2017 Florida International University
The Interactions Of Relationships, Interest, And Self-Efficacy In Undergraduate Physics, Remy Dou
FIU Electronic Theses and Dissertations
This collected papers dissertation explores students’ academic interactions in an active learning, introductory physics settings as they relate to the development of physics self-efficacy and interest. The motivation for this work extends from the national call to increase participation of students in the pursuit of science, technology, engineering, and mathematics (STEM) careers. Self-efficacy and interest are factors that play prominent roles in popular, evidence-based, career theories, including the Social cognitive career theory (SCCT) and the identity framework. Understanding how these constructs develop in light of the most pervasive characteristic of the active learning introductory physics classroom (i.e., peer-to-peer interactions) has …
Disability In Long-Term Care Residents Explained By Prevalent Geriatric Syndromes, Not Long-Term Care Home Characteristics: A Cross-Sectional Study, 2017 University of Toronto
Disability In Long-Term Care Residents Explained By Prevalent Geriatric Syndromes, Not Long-Term Care Home Characteristics: A Cross-Sectional Study, Natasha E. Lane, Walter P. Wodchis, Cynthia M. Boyd, Thérèse A. Stukel
Dartmouth Scholarship
Self-care disability is dependence on others to conduct activities of daily living, such as bathing, eating and dressing. Among long-term care residents, self-care disability lowers quality of life and increases health care costs. Understanding the correlates of self-care disability in this population is critical to guide clinical care and ongoing research in Geriatrics. This study examines which resident geriatric syndromes and chronic conditions are associated with residents’ self-care disability and whether these relationships vary across strata of age, sex and cognitive status. It also describes the proportion of variance in residents’ self-care disability that is explained by residents’ geriatric syndromes …
The Finney County, Kansas Community Assessment Process: Fact Book, 2017 Kansas State University
The Finney County, Kansas Community Assessment Process: Fact Book, Debra J. Bolton Phd, Shannon L. Dick M.S.
Dr. Debra Bolton
This multi-lingual/multi-cultural study was called, Community Assets Processt, by the groups that “commissioned” it: Finnup Foundation, Finney County K-State Research & Extension, Western Kansas Community Foundation, Finney County United Way, Finney County Health Department, United Methodist Community Health Center (UMMAM), Center for Children and Families, Garden City Recreation Commission, and the Garden City Cultural Relations Board, because we intend for this to be an ongoing discussion. An objective, for those promoting the study, was to connect foundation, state, and federal funding with activities or services that addressed the true needs of people living in Finney County. The group was looking …
Informational Index And Its Applications In High Dimensional Data, 2017 University of Kentucky
Informational Index And Its Applications In High Dimensional Data, Qingcong Yuan
Theses and Dissertations--Statistics
We introduce a new class of measures for testing independence between two random vectors, which uses expected difference of conditional and marginal characteristic functions. By choosing a particular weight function in the class, we propose a new index for measuring independence and study its property. Two empirical versions are developed, their properties, asymptotics, connection with existing measures and applications are discussed. Implementation and Monte Carlo results are also presented.
We propose a two-stage sufficient variable selections method based on the new index to deal with large p small n data. The method does not require model specification and especially focuses …
Effect Of Correlations On Type 1 Error Rates Of Some Multivariate Normality Tests, 2017 Ladoke Akintola University of Technology,Ogbomoso. Oyo State,Nigeria
Effect Of Correlations On Type 1 Error Rates Of Some Multivariate Normality Tests, Gbenga Sunday Solomon, Kayode Ayinde, Nurudeen Abiodun Alao
Conference on Applied Statistics in Agriculture
Normality assumption of multivariate data is a prerequisite to the use of multivariate statistical data analysis methods before inference could be valid and reliable. Tests developed to validate this assumption including Doornik-Harsen (DH), Shapiro-Francia (SF), Mardia Skewness (MS), Mardia Skewness for small sample (MSS) and Kurtosis (MK), Skewness (S) and Kurtosis(K), Shapiro-Wilk(SW), Royston (R), Desgagne-Micheaux (DM), Henze-Zirkler (HZ), Energy (E), Gel-Gastwirth (GG) and Bontemps-Meddahi (BM) tests often result into different conclusions. These differences can be misleading. Consequently, this paper examined the effect of correlations on the Type 1 error rates of multivariate tests of normality. Monte Carlo experiments were conducted …