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Articles 91 - 120 of 144
Full-Text Articles in Statistics and Probability
Skill Evaluation In Women's Volleyball, Lindsay Walker Florence
Skill Evaluation In Women's Volleyball, Lindsay Walker Florence
Theses and Dissertations
The Brigham Young University Women's Volleyball Team recorded and rated all skills (pass, set, attack, etc.) and recorded rally outcomes (point for BYU, rally continues, point for opponent) for the entire 2006 home volleyball season. Only sequences of events occurring on BYU's side of the net were considered. Events followed one of these general patterns: serve-outcome, pass-set-attack-outcome, or block-dig-set-attack-outcome. These sequences of events were assumed to be first-order Markov chains where the quality of each contact depended only explicitly on the quality of the previous contact but not on contacts further removed in the sequence. We represented these sequences in …
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 …
Using Box-Scores To Determine A Position's Contribution To Winning Basketball Games, Gilbert W. Fellingham, C. Shane Reese, Garritt L. Page
Using Box-Scores To Determine A Position's Contribution To Winning Basketball Games, Gilbert W. Fellingham, C. Shane Reese, Garritt L. Page
Faculty Publications
While it is generally recognized that the relative importance of different skills is not constant across different positions on a basketball team, quantification of the differences has not been well studied. 1163 box scores from games in the National Basketball Association during the 1996-97 season were used to study the relationship of skill performance by position and game outcome as measured by point differentials. A hierarchical Bayesian model was fit with individual players viewed as a draw from a population of players playing a particular position: point guard, shooting guard, small forward, power forward, center, and bench. Posterior distributions for …
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 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 …
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 …
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 …
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 …
Life Data Analysis Of Repairable Systems: A Case Study On Brigham Young University Media Rooms, Stephen Oluaku Manortey
Life Data Analysis Of Repairable Systems: A Case Study On Brigham Young University Media Rooms, Stephen Oluaku Manortey
Theses and Dissertations
It is an undisputable fact that most systems, upon consistence usage are bound to fail in the performance of their intended functions at a point in time. When this occurs, various strategies are set in place to restore them back to a satisfactory performance. This may include replacing the failed component with a new one, swapping parts, resetting adjustable parts to mention but a few. Any such system is referred to as a repairable system. There is the need to study these systems and use statistical models to predict their failing time and be able to set modalities in place …
A Comparison Of Microarray Analyses: A Mixed Models Approach Versus The Significance Analysis Of Microarrays, Nathan Wallace Stephens
A Comparison Of Microarray Analyses: A Mixed Models Approach Versus The Significance Analysis Of Microarrays, Nathan Wallace Stephens
Theses and Dissertations
DNA microarrays are a relatively new technology for assessing the expression levels of thousands of genes simultaneously. Researchers hope to find genes that are differentially expressed by hybridizing cDNA from known treatment sources with various genes spotted on the microarrays. The large number of tests involved in analyzing microarrays has raised new questions in multiple testing. Several approaches for identifying differentially expressed genes have been proposed. This paper considers two: (1) a mixed models approach, and (2) the Signiffcance Analysis of Microarrays.
A Logistic Regression Analysis Of Utah Colleges Exit Poll Response Rates Using Sas Software, Clint W. Stevenson
A Logistic Regression Analysis Of Utah Colleges Exit Poll Response Rates Using Sas Software, Clint W. Stevenson
Theses and Dissertations
In this study I examine voter response at an interview level using a dataset of 7562 voter contacts (including responses and nonresponses) in the 2004 Utah Colleges Exit Poll. In 2004, 4908 of the 7562 voters approached responded to the exit poll for an overall response rate of 65 percent. Logistic regression is used to estimate factors that contribute to a success or failure of each interview attempt. This logistic regression model uses interviewer characteristics, voter characteristics (both respondents and nonrespondents), and exogenous factors as independent variables. Voter characteristics such as race, gender, and age are strongly associated with response. …
Sources Of Variability In A Proteomic Experiment, Scott Daniel Crawford
Sources Of Variability In A Proteomic Experiment, Scott Daniel Crawford
Theses and Dissertations
The study of proteomics holds the hope for detecting serious diseases earlier than is currently possible by analyzing blood samples in a mass spectrometer. Unfortunately, the statistics involved in comparing a control group to a diseased group are not trivial, and these difficulties have led others to incorrect decisions in the past. This paper considers a nested design that was used to quantify and identify the sources of variation in the mass spectrometer at BYU, so that correct conclusions can be drawn from blood samples analyzed in proteomics. Algorithms were developed which detect, align, correct, and cluster the peaks in …
Understanding Brigham Young University's Technology Teacher Education Program's Sucess In Attracting And Retaining Female Students, Katrina M. Cox
Understanding Brigham Young University's Technology Teacher Education Program's Sucess In Attracting And Retaining Female Students, Katrina M. Cox
Theses and Dissertations
The purpose of the study was to attempt to understand why Brigham Young University Technology Teacher Education program has attracted and retained a high number of females. This was done through a self-created survey composed of four forced responses, distributed among the Winter 2006 semester students. Likert-scale questions were outlined according to the five theoretical influences on women in technology, as established by Welty and Puck (2001) and two of the three relationships of academia, as established by Haynie III (1999), as well as three free response questions regarding retention and attraction within the major. Findings suggested strong positive polarity …
Computation Of Weights For Probabilistic Record Linkage Using The Em Algorithm, G. John Bauman
Computation Of Weights For Probabilistic Record Linkage Using The Em Algorithm, G. John Bauman
Theses and Dissertations
Record linkage is the process of combining information about a single individual from two or more records. Probabilistic record linkage gives weights to each field that is compared. The decision of whether the records should be linked is then determined by the sum of the weights, or “Score”, over all fields compared. Using methods similar to the simple versus simple most powerful test, an optimal record linkage decision rule can be established to minimize the number of unlinked records when the probability of false positive and false negative errors are specified. The weights needed for probabilistic record linkage necessitate linking …
Food Shelf Life: Estimation And Experimental Design, Ross Allen Andrew Larsen
Food Shelf Life: Estimation And Experimental Design, Ross Allen Andrew Larsen
Theses and Dissertations
Shelf life is a parameter of the lifetime distribution of a food product, usually the time until a specified proportion (1-50%) of the product has spoiled according to taste. The data used to estimate shelf life typically come from a planned experiment with sampled food items observed at specified times. The observation times are usually selected adaptively using ‘staggered sampling.’ Ad-hoc methods based on linear regression have been recommended to estimate shelf life. However, other methods based on maximizing a likelihood (MLE) have been proposed, studied, and used. Both methods assume the Weibull distribution. The observed lifetimes in shelf life …
Bayesian And Positive Matrix Factorization Approaches To Pollution Source Apportionment, Jeff William Lingwall
Bayesian And Positive Matrix Factorization Approaches To Pollution Source Apportionment, Jeff William Lingwall
Theses and Dissertations
The use of Positive Matrix Factorization (PMF) in pollution source apportionment (PSA) is examined and illustrated. A study of its settings is conducted in order to optimize them in the context of PSA. The use of a priori information in PMF is examined, in the form of target factor profiles and pulling profile elements to zero. A Bayesian model using lognormal prior distributions for source profiles and source contributions is fit and examined.
Modeling The Performance Of A Baseball Player's Offensive Production, Michael Ross Smith
Modeling The Performance Of A Baseball Player's Offensive Production, Michael Ross Smith
Theses and Dissertations
This project addresses the problem of comparing the offensive abilities of players from different eras in Major League Baseball (MLB). We will study players from the perspective of an overall offensive summary statistic that is highly linked with scoring runs, or the Berry Value. We will build an additive model to estimate the innate ability of the player, the effect of the relative level of competition of each season, and the effect of age on performance using piecewise age curves. Using Hierarchical Bayes methodology with Gibbs sampling, we model each of these effects for each individual. The results of the …
Correlating Factors Between Student Participation And Student Learning Via A Service Learning Project In Secondary Education: A Case Study, Shawn V. Jensen
Correlating Factors Between Student Participation And Student Learning Via A Service Learning Project In Secondary Education: A Case Study, Shawn V. Jensen
Theses and Dissertations
In this study a service-learning project was conducted with secondary students in a construction technology based course. Three research questions were considered; (1) does service learning projects help to engage student participation, (2) can students learn the course curriculum while participating in a service learning project, and (3) is there a correlation between student participation and student learning as it pertains to service learning projects? The data was collected through surveys, observations, interviews, and evaluations. The researcher concluded the following from the study; 92% of the students were actively participating in the two week service project, 76% of the students …