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Articles 1 - 28 of 28
Full-Text Articles in Physical Sciences and Mathematics
Extending The Information Partition Function: Modeling Interaction Effects In Highly Multivariate, Discrete Data, Paul C. Cannon
Extending The Information Partition Function: Modeling Interaction Effects In Highly Multivariate, Discrete Data, Paul C. Cannon
Theses and Dissertations
Because of the huge amounts of data made available by the technology boom in the late twentieth century, new methods are required to turn data into usable information. Much of this data is categorical in nature, which makes estimation difficult in highly multivariate settings. In this thesis we review various multivariate statistical methods, discuss various statistical methods of natural language processing (NLP), and discuss a general class of models described by Erosheva (2002) called generalized mixed membership models. We then propose extensions of the information partition function (IPF) derived by Engler (2002), Oliphant (2003), and Tolley (2006) that will allow …
Clustering Methods For Delineating Regions Of Spatial Stationarity, Jared M. Collings
Clustering Methods For Delineating Regions Of Spatial Stationarity, Jared M. Collings
Theses and Dissertations
This paper seeks to further investigate data extracted by the use of Functional Magnetic Resonance Imaging (FMRI) as it is applied to brain tissue and how it measures blood flow to certain areas of the brain following the application of a stimulus. As a precursor to detailed spatial analysis of this kind of data, this paper develops methods of grouping data based on the necessary conditions for spatial statistical analysis. The purpose of this paper is to examine and develop methods that can be used to delineate regions of stationarity. One of the major assumptions used in spatial estimation is …
Modeling Transition Probabilities For Loan States Using A Bayesian Hierarchical Model, Rebecca Lee Monson
Modeling Transition Probabilities For Loan States Using A Bayesian Hierarchical Model, Rebecca Lee Monson
Theses and Dissertations
A Markov Chain model can be used to model loan defaults because loans move through delinquency states as the borrower fails to make monthly payments. The transition matrix contains in each location a probability that a borrower in a given state one month moves to the possible delinquency states the next month. In order to use this model, it is necessary to know the transition probabilities, which are unknown quantities. A Bayesian hierarchical model is postulated because there may not be sufficient data for some rare transition probabilities. Using a hierarchical model, similarities between types or families of loans can …
Accounting For Additional Heterogeneity: A Theoretic Extension Of An Extant Economic Model, Bradley John Barney
Accounting For Additional Heterogeneity: A Theoretic Extension Of An Extant Economic Model, Bradley John Barney
Theses and Dissertations
The assumption in economics of a representative agent is often made. However, it is a very rigid assumption. Hall and Jones (2004b) presented an economic model that essentially provided for a representative agent for each age group in determining the group's health level function. Our work seeks to extend their theoretical version of the model by allowing for two representative agents for each age—one for each of “Healthy” and “Sick” risk-factor groups—to allow for additional heterogeneity in the populace. The approach to include even more risk-factor groups is also briefly discussed. While our “extended” theoretical model is not applied directly …
Applying Bayesian Ordinal Regression To Icap Maladaptive Behavior Subscales, Edward P. Johnson
Applying Bayesian Ordinal Regression To Icap Maladaptive Behavior Subscales, Edward P. Johnson
Theses and Dissertations
This paper develops a Bayesian ordinal regression model for the maladaptive subscales of the Inventory for Client and Agency Planning (ICAP). Because the maladaptive behavior section of the ICAP contains ordinal data, current analysis strategies combine all the subscales into three indices, making the data more interval in nature. Regular MANOVA tools are subsequently used to create a regression model for these indices. This paper uses ordinal regression to analyze each original scale separately. The sample consists of applicants for aid from Utah's Division of Services for Persons with Disabilities. Each applicant fills out the Scales of Independent Behavior"”Revised (SIB-R) …
An Adaptive Bayesian Approach To Bernoulli-Response Clinical Trials, Andrew W. Stacey
An Adaptive Bayesian Approach To Bernoulli-Response Clinical Trials, Andrew W. Stacey
Theses and Dissertations
Traditional clinical trials have been inefficient in their methods of dose finding and dose allocation. In this paper a four-parameter logistic equation is used to model the outcome of Bernoulli-response clinical trials. A Bayesian adaptive design is used to fit the logistic equation to the dose-response curve of Phase II and Phase III clinical trials. Because of inherent restrictions in the logistic model, symmetric candidate densities cannot be used, thereby creating asymmetric jumping rules inside the Markov chain Monte Carlo algorithm. An order restricted Metropolis-Hastings algorithm is implemented to account for these limitations. Modeling clinical trials in a Bayesian framework …
Development Of Informative Priors In Microarray Studies, Kassandra M. Fronczyk
Development Of Informative Priors In Microarray Studies, Kassandra M. Fronczyk
Theses and Dissertations
Microarrays measure the abundance of DNA transcripts for thousands of gene sequences, simultaneously facilitating genomic comparisons across tissue types or disease status. These experiments are used to understand fundamental aspects of growth and development and to explore the underlying genetic causes of many diseases. The data from most microarray studies are found in open-access online databases. Bayesian models are ideal for the analysis of microarray data because of their ability to integrate prior information; however, most current Bayesian analyses use empirical or flat priors. We present a Perl script to build an informative prior by mining online databases for similar …
Statistical Considerations In Designing For Biomarker Detection, Trenton C. Pulsipher
Statistical Considerations In Designing For Biomarker Detection, Trenton C. Pulsipher
Theses and Dissertations
The purpose of this project is to develop a statistical method for use in rapid detection of biological agents using portable gas chromatography mass spectrometry (GC/MS) devices. Of particular interest is 2,6-pyridinedicarboxylic acid (dipicolinic acid, or DPA), a molecule that is present at high concentrations in spores of Clostridium and Bacillus, the latter of which includes the threat organism Bacillus anthracis, or anthrax. Dipicolinic acid may be useful as a first-step discriminator of the biological warfare agent B. anthracis. The results of experiments with B. anthracis Sterne strain and Bacillus thuringiensis spores lead to a conceptual model for the chemical …
A Modified Cluster-Weighted Approach To Nonlinear Time Series, Mark Ballatore Lyman
A Modified Cluster-Weighted Approach To Nonlinear Time Series, Mark Ballatore Lyman
Theses and Dissertations
In many applications involving data collected over time, it is important to get timely estimates and adjustments of the parameters associated with a dynamic model. When the dynamics of the model must be updated, time and computational simplicity are important issues. When the dynamic system is not linear the problem of adaptation and response to feedback are exacerbated. A linear approximation of the process at various levels or “states” may approximate the non-linear system. In this case the approximation is linear within a state and transitions from state to state over time. The transition probabilities are parametrized as a Markov …
A Comparative Simulation Study Of Robust Estimators Of Standard Errors, Natalie Johnson
A Comparative Simulation Study Of Robust Estimators Of Standard Errors, Natalie Johnson
Theses and Dissertations
The estimation of standard errors is essential to statistical inference. Statistical variability is inherent within data, but is usually of secondary interest; still, some options exist to deal with this variability. One approach is to carefully model the covariance structure. Another approach is robust estimation. In this approach, the covariance structure is estimated from the data. White (1980) introduced a biased, but consistent, robust estimator. Long et al. (2000) added an adjustment factor to White's estimator to remove the bias of the original estimator. Through the use of simulations, this project compares restricted maximum likelihood (REML) with four robust estimation …
Sensitivity To Distributional Assumptions In Estimation Of The Odp Thresholding Function, Wendy Jill Bunn
Sensitivity To Distributional Assumptions In Estimation Of The Odp Thresholding Function, Wendy Jill Bunn
Theses and Dissertations
Recent technological advances in fields like medicine and genomics have produced high-dimensional data sets and a challenge to correctly interpret experimental results. The Optimal Discovery Procedure (ODP) (Storey 2005) builds on the framework of Neyman-Pearson hypothesis testing to optimally test thousands of hypotheses simultaneously. The method relies on the assumption of normally distributed data; however, many applications of this method will violate this assumption. This thesis investigates the sensitivity of this method to detection of significant but nonnormal data. Overall, estimation of the ODP with the method described in this thesis is satisfactory, except when the nonnormal alternative distribution has …
Temporally Correlated Dirichlet Processes In Pollution Receptor Modeling, Matthew J. Heaton
Temporally Correlated Dirichlet Processes In Pollution Receptor Modeling, Matthew J. Heaton
Theses and Dissertations
Understanding the effect of human-induced pollution on the environment is an important precursor to promoting public health and environmental stability. One aspect of understanding pollution is understanding pollution sources. Various methods have been used and developed to understand pollution sources and the amount of pollution those sources emit. Multivariate receptor modeling seeks to estimate pollution source profiles and pollution emissions from concentrations of pollutants such as particulate matter (PM) in the air. Previous approaches to multivariate receptor modeling make the following two key assumptions: (1) PM measurements are independent and (2) source profiles are constant through time. Notwithstanding these assumptions, …
Separate And Joint Analysis Of Longitudinal And Survival Data, Deepthi Rajeev
Separate And Joint Analysis Of Longitudinal And Survival Data, Deepthi Rajeev
Theses and Dissertations
Chemotherapy is a method used to treat cancer but it has a number of side-effects. Research conducted by the Department of Chemical Engineering at BYU involves a new method of administering chemotherapy using ultrasound waves and water-soluble capsules. The goal is to reduce the side-effects by localizing the delivery of the medication. As part of this research, a two-factor experiment was conducted on rats to test if the water-soluble capsules and ultrasound waves by themselves have an effect on tumor growth or patient survival. Our project emphasizes the usage of Bayesian Hierarchical Models and Win-BUGS to jointly model the survival …
A Multivariate Magnitude Robust Control Chart For Mean Shift Detection And Change Point Estimation, Ryan M. Harrell
A Multivariate Magnitude Robust Control Chart For Mean Shift Detection And Change Point Estimation, Ryan M. Harrell
Theses and Dissertations
Statistical control charts are often used to detect a change in an otherwise stable process. This process may contain several variables affecting process stability. The goal of any control chart is to detect an out-of-control state quickly and provide insight on when the process actually changed. This reduces the off-line time the quality engineer spends assigning causality. In this research, a multivariate magnitude robust chart (MMRC) was developed using a change point model and a likelihood-ratio approach. Here the process is considered in-control until one or more normally distributed process variables permanently and suddenly shifts to out-of-control, stable value. Using …
A Simulation-Based Approach For Evaluating Gene Expression Analyses, Carly Ruth Pendleton
A Simulation-Based Approach For Evaluating Gene Expression Analyses, Carly Ruth Pendleton
Theses and Dissertations
Microarrays enable biologists to measure differences in gene expression in thousands of genes simultaneously. The data produced by microarrays present a statistical challenge, one which has been met both by new modifications of existing methods and by completely new approaches. One of the difficulties with a new approach to microarray analysis is validating the method's power and sensitivity. A simulation study could provide such validation by simulating gene expression data and investigating the method's response to changes in the data; however, due to the complex dependencies and interactions found in gene expression data, such a simulation would be complicated and …
Refinement Of An Instrument To Assess Readiness For Knowledge Management, Landon C. Bailey
Refinement Of An Instrument To Assess Readiness For Knowledge Management, Landon C. Bailey
Theses and Dissertations
Academics and practitioners have described knowledge as a primary source for competitive advantage for organizations; however, many attempts at instituting knowledge management programs to increase organizational competitiveness do not succeed. Instituting knowledge management programs generally requires organizations to make significant changes and the concept of readiness has long been believed to be an important precondition for successful organizational change. By linking previous research in enablers for knowledge management and organizational change, it is possible to adapt an established organizational change readiness instrument to measure readiness for knowledge management. This study culminates in the development and field-testing of the resultant knowledge …
The Effect Of Birth Order On Infant Injury, Heather L. Van Duker
The Effect Of Birth Order On Infant Injury, Heather L. Van Duker
Theses and Dissertations
Pediatric injury is both common and expensive. Finding ways to prevent pediatric injury is a major public health concern. Many studies have investigated various aspects of pediatric injury, and some suggest that birth order may be an important risk factor for pediatric injury. This study further examined the relationship of birth order with pediatric injury, specifically studying the association of birth order with emergency department-attended infant injury while adjusting for other important family and individual covariates. Data for analysis included Utah birth certificate, death certificate, and hospital emergency department datasets, which were probabilistically linked to obtain complete demographic and injury …
Professionalism In The Air Force: A Comparative Analysis Of Commissioned Officers With Non-Commissioned Officers, Edward K. Boyd
Professionalism In The Air Force: A Comparative Analysis Of Commissioned Officers With Non-Commissioned Officers, Edward K. Boyd
Theses and Dissertations
Decades ago, military sociologists predicted a rising trend among officers away from traditional institutional military values and toward more economically-based occupational values due to the effects of the transition from a conscription-based military to an all-volunteer force. Subsequent empirical research resulted in data that supports such predictions. More recent researchers have suggested that in addition to the all-volunteer force, an increase on technology may also accelerate the trend toward occupationalism and away from traditional institutional military values and the warrior ethos that typically define successful military organizations. The officer corps may be particularly vulnerable to occupationalism due to increased technical …
Corporate Entrepreneurship Assessment Instrument (Ceai): Refinement And Validation Of A Survey Measure, Michael S. Cates
Corporate Entrepreneurship Assessment Instrument (Ceai): Refinement And Validation Of A Survey Measure, Michael S. Cates
Theses and Dissertations
The study of corporate entrepreneurship has established itself as a valuable area of research for both public and private-sector organizations. The measurement instrument known as the Corporate Entrepreneurship Assessment Index (CEAI) has been designed to tap the climate-related organizational factors that represent and potentially encourage corporate entrepreneurship. This study is an attempt to refine the CEAI. The core constructs of the CEAI are redefined, the items are tested for content validity, the factor structure is analyzed, and the CEAI is correlated to other known measures to validate the CEAI. Through this testing, the CEAI was refined and found to be …
Improved Hyperspectral Image Testing Using Synthetic Imagery And Factorial Designed Experiments, Joseph P. Bellucci
Improved Hyperspectral Image Testing Using Synthetic Imagery And Factorial Designed Experiments, Joseph P. Bellucci
Theses and Dissertations
The goal of any remote sensing system is to gather data about the geography it is imaging. In order to gain knowledge of the earth's landscape, post-processing algorithms are developed to extract information from the collected data. The algorithms can be intended to classify the various ground covers in a scene, identify specific targets of interest, or detect anomalies in an image. After the design of an algorithm comes the difficult task of testing and evaluating its performance. Traditionally, algorithms are tested using sets of extensively ground truthed test images. However, the lack of well characterized test data sets and …
An Evaluation Of Organizational And Experience Factors Affecting The Perceived Transfer Of U.S. Air Force Basic Combat Skills Training, Shirley D. Crow
An Evaluation Of Organizational And Experience Factors Affecting The Perceived Transfer Of U.S. Air Force Basic Combat Skills Training, Shirley D. Crow
Theses and Dissertations
The United States Air Force is in a state of transformation. Due to ongoing operations in Iraq and Afghanistan, the focus of Basic Military Training is shifting to basic combat skills, or the skills needed to survive and operate in a hostile environment. In this study, basic combat skills training was evaluated using a number of training factors that potentially affect trainees’ perception of training transfer, or their ability to apply the skills they learned in training on the job or in a hostile environment. The analysis used structural equation modeling to evaluate the paths between each of the factors …
Graphical And Bayesian Analysis Of Unbalanced Patient Management Data, Emily Stewart Righter
Graphical And Bayesian Analysis Of Unbalanced Patient Management Data, Emily Stewart Righter
Theses and Dissertations
The International Normalizing Ratio (INR) measures the speed at which blood clots. Healthy people have an INR of about one. Some people are at greater risk of blood clots and their physician prescribes a target INR range, generally 2-3. The farther a patient is above or below their prescribed range, the more dangerous their situation. A variety of point-of-care (POC) devices has been developed to monitor patients. The purpose of this research was to develop innovative graphics to help describe a highly unbalanced dataset and to carry out Bayesian analyses to determine which of five devices best manages patients. An …
Predicting Argentine Jet Fuel Prices, Juan A. Salaverry
Predicting Argentine Jet Fuel Prices, Juan A. Salaverry
Theses and Dissertations
Oil distillates are considered important elements to accomplish the missions of the Argentine Air Force (AAF). Of all oil products consumed by the AAF, jet fuel is the resource with highest demand and at the end of the day the most expensive support item procured by the Argentine Air Force. Accurate predictions of Argentine jet fuel prices are necessary to improve AAF financial and logistics planning. This thesis presents a systematic, statistical regression approach to forecast Argentine jet fuel prices. The application of this methodology has allowed us to obtain a very useful model that utilizes information available on the …
A Meta-Analysis Of Questionaire Response Rates In Military Samples, Michael R. Parrish
A Meta-Analysis Of Questionaire Response Rates In Military Samples, Michael R. Parrish
Theses and Dissertations
The purpose of this research was to examine if factors related to questionnaire response rate in the general public also affect response rate in military-only samples. Very little research pertaining to this specific group was located during the literature review. Four response rate factors taken from studies conducted in the general public were selected for this research topic: questionnaire length, questionnaire delivery mode (postal, e-mail, web-based, direct administration, and mixed mode), use of advance notices, and use of follow-up reminders. Data were gathered for a meta-analysis of 73 previously published studies which utilized a survey or questionnaire to collect data …
Analysis Using Smoothing Via Penalized Splines As Implemented In Lme() In R, John R. Howell
Analysis Using Smoothing Via Penalized Splines As Implemented In Lme() In R, John R. Howell
Theses and Dissertations
Spline smoothers as implemented in common mixed model software provide a familiar framework for estimating semi-parametric and non-parametric models. Following a review of literature on splines and mixed models, details for implementing mixed model splines are presented. The examples use an experiment in the health sciences to demonstrate how to use mixed models to generate the smoothers. The first example takes a simple one-group case, while the second example fits an expanded model using three groups simultaneously. The second example also demonstrates how to fit confidence bands to the three-group model. The examples use mixed model software as implemented in …
Selecting The Best Linear Mixed Model Using Predictive Approaches, Jun Wang
Selecting The Best Linear Mixed Model Using Predictive Approaches, Jun Wang
Theses and Dissertations
The linear mixed model is widely implemented in the analysis of longitudinal data. Inference techniques and information criteria are available and well-studied for goodness-of-fit within the linear mixed model setting. Predictive approaches such as R-squared, PRESS, and CCC are available for the linear mixed model but require more research (Edward, 2005). This project used simulation to investigate the performance of R-squared, PRESS, CCC, Pseudo F-test and information criterion for goodness-of-fit within the linear mixed model framework. Marginal and conditional approaches for these predictive statistics were studied under different variance-covariance structures. For compound symmetry structure, the success rates for all 17 …
An Adaptive Dose Finding Design (Dosefind) Using A Nonlinear Dose Response Model, James Michael Davenport
An Adaptive Dose Finding Design (Dosefind) Using A Nonlinear Dose Response Model, James Michael Davenport
Theses and Dissertations
First-in-man (FIM) Phase I clinical trials are part of the critical path in the development of a new compound entity (NCE). Since FIM clinical trials are the first time that an NCE is dosed in human subjects, the designs used in these trials are unique and geared toward patient safety. We develop a method for obtaining the desired response using an adaptive non-linear approach. This method is applicable for studies in which MTD, NOEL,NOAEL, PK, PD effects or other such endpoints are evaluated to determine the desired dose. The method has application whenever a measurable PD marker is an indicator …
Phase Ii Trials Powered To Detect Activity In Tumor Subsets With Retrospective (Or Prospective) Use Of Predictive Markers, Grishma S. Sheth
Phase Ii Trials Powered To Detect Activity In Tumor Subsets With Retrospective (Or Prospective) Use Of Predictive Markers, Grishma S. Sheth
Theses and Dissertations
Classical phase II trial designs assume a patient population with a homogeneous tumor type and yield an estimate of a stochastic probability of tumor response. Clinically, however, oncology is moving towards identifying patients who are likely to respond to therapy using tumor subtyping based upon predictive markers. Such designs are called targeted designs (Simon, 2004). For a given phase I1 trial predictive markers may be defined prospectively (on the basis of previous results) or identified retrospectively on the basis of analysis of responding and non-responding tumors. For the prospective case we propose two Phase I1 targeted designs in which a) …