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Theses and Dissertations

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Full-Text Articles in Statistics and Probability

Nonlinear Models In Multivariate Population Bioequivalence Testing, Bassam Dahman Nov 2009

Nonlinear Models In Multivariate Population Bioequivalence Testing, Bassam Dahman

Theses and Dissertations

In this dissertation a methodology is proposed for simultaneously evaluating the population bioequivalence (PBE) of a generic drug to a pre-licensed drug, or the bioequivalence of two formulations of a drug using multiple correlated pharmacokinetic metrics. The univariate criterion that is accepted by the food and drug administration (FDA) for testing population bioequivalence is generalized. Very few approaches for testing multivariate extensions of PBE have appeared in the literature. One method uses the trace of the covariance matrix as a measure of total variability, and another uses a pooled variance instead of the reference variance. The former ignores the correlation …

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Parameter Estimation For The Lognormal Distribution, Brenda Faith Ginos Nov 2009

Parameter Estimation For The Lognormal Distribution, Brenda Faith Ginos

Theses and Dissertations

The lognormal distribution is useful in modeling continuous random variables which are greater than or equal to zero. Example scenarios in which the lognormal distribution is used include, among many others: in medicine, latent periods of infectious diseases; in environmental science, the distribution of particles, chemicals, and organisms in the environment; in linguistics, the number of letters per word and the number of words per sentence; and in economics, age of marriage, farm size, and income. The lognormal distribution is also useful in modeling data which would be considered normally distributed except for the fact that it may be more …

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Joint Mixed-Effects Models For Longitudinal Data Analysis: An Application For The Metabolic Syndrome, John Thorp Iii Nov 2009

Joint Mixed-Effects Models For Longitudinal Data Analysis: An Application For The Metabolic Syndrome, John Thorp Iii

Theses and Dissertations

Mixed-effects models are commonly used to model longitudinal data as they can appropriately account for within and between subject sources of variability. Univariate mixed effect modeling strategies are well developed for a single outcome (response) variable that may be continuous (e.g. Gaussian) or categorical (e.g. binary, Poisson) in nature. Only recently have extensions been discussed for jointly modeling multiple outcome variables measures longitudinally. Many diseases processes are a function of several factors that are correlated. For example, the metabolic syndrome, a constellation of cardiovascular risk factors associated with an increased risk of cardiovascular disease and type 2 diabetes, is often …

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Deriving Optimal Composite Scores: Relating Observational/Longitudinal Data With A Primary Endpoint, Rhonda Ellis Sep 2009

Deriving Optimal Composite Scores: Relating Observational/Longitudinal Data With A Primary Endpoint, Rhonda Ellis

Theses and Dissertations

In numerous clinical/experimental studies, multiple endpoints are measured on each subject. It is often not clear which of these endpoints should be designated as of primary importance. The desirability function approach is a way of combining multiple responses into a single unitless composite score. The response variables may include multiple types of data: binary, ordinal, count, interval data. Each response variable is transformed to a 0 to1 unitless scale with zero representing a completely undesirable response and one representing the ideal value. In desirability function methodology, weights on individual components can be incorporated to allow different levels of importance to …

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A Sequential Algorithm To Identify The Mixing Endpoints In Liquids In Pharmaceutical Applications, Akriti Saxena Jul 2009

A Sequential Algorithm To Identify The Mixing Endpoints In Liquids In Pharmaceutical Applications, Akriti Saxena

Theses and Dissertations

The objective of this thesis is to develop a sequential algorithm to determine accurately and quickly, at which point in time a product is well mixed or reaches a steady state plateau, in terms of the Refractive Index (RI). An algorithm using sequential non-linear model fitting and prediction is proposed. A simulation study representing typical scenarios in a liquid manufacturing process in pharmaceutical industries was performed to evaluate the proposed algorithm. The data simulated included autocorrelated normal errors and used the Gompertz model. A set of 27 different combinations of the parameters of the Gompertz function were considered. The results …

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Estimating The Effect Of Disability On Medicare Expenditures, David Morris Burk Jul 2009

Estimating The Effect Of Disability On Medicare Expenditures, David Morris Burk

Theses and Dissertations

We consider the effect of disability status on Medicare expenditures. Disabled elderly historically have accounted for a significant portion of Medicare expenditures. Recent demographic trends exhibit a decline in the size of this population, causing some observers to predict declines in Medicare expenditures. There are, however, reasons to be suspicious of this rosy forecast. To better understand the effect of disability on Medicare expenditures, we develop and estimate a model using the generalized method of moments technique. We find that newly disabled elderly generally spend more than those who have been disabled for longer periods of time. Also, we find …

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Zero-Inflated Censored Regression Models: An Application With Episode Of Care Data, Jonathan P. Prasad Jul 2009

Zero-Inflated Censored Regression Models: An Application With Episode Of Care Data, Jonathan P. Prasad

Theses and Dissertations

The objective of this project is to fit a sequence of increasingly complex zero-inflated censored regression models to a known data set. It is quite common to find censored count data in statistical analyses of health-related data. Modeling such data while ignoring the censoring, zero-inflation, and overdispersion often results in biased parameter estimates. This project develops various regression models that can be used to predict a count response variable that is affected by various predictor variables. The regression parameters are estimated with Bayesian analysis using a Markov chain Monte Carlo (MCMC) algorithm. The tests for model adequacy are discussed and …

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Meta-Analysis Using Bayesian Hierarchical Models In Organizational Behavior, Michael David Ulrich Jul 2009

Meta-Analysis Using Bayesian Hierarchical Models In Organizational Behavior, Michael David Ulrich

Theses and Dissertations

Meta-analysis is a tool used to combine the results from multiple studies into one comprehensive analysis. First developed in the 1970s, meta-analysis is a major statistical method in academic, medical, business, and industrial research. There are three traditional ways in which a meta-analysis is conducted: fixed or random effects, and using an empirical Bayesian approach. Derivations for conducting meta-analysis on correlations in the industrial psychology and organizational behavior (OB) discipline were reviewed by Hunter and Schmidt (2004). In this approach, Hunter and Schmidt propose an empirical Bayesian analysis where the results from previous studies are used as a prior. This …

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Modeling Temperature Reduction In Tendons Using Gaussian Processes Within A Dynamic Linear Model, Richard David Wyss Jul 2009

Modeling Temperature Reduction In Tendons Using Gaussian Processes Within A Dynamic Linear Model, Richard David Wyss

Theses and Dissertations

The time it takes an athlete to recover from an injury can be highly influenced by training procedures as well as the medical care and physical therapy received. When an injury occurs to the muscles or tendons of an athlete, it is desirable to cool the muscles and tendons within the body to reduce inflammation, thereby reducing the recovery time. Consequently, finding a method of treatment that is effective in reducing tendon temperatures is beneficial to increasing the speed at which the athlete is able to recover. In this project, Bayesian inference with Gaussian processes will be used to model …

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Comparing Bootstrap And Jackknife Variance Estimation Methods For Area Under The Roc Curve Using One-Stage Cluster Survey Data, Allison Dunning Jun 2009

Comparing Bootstrap And Jackknife Variance Estimation Methods For Area Under The Roc Curve Using One-Stage Cluster Survey Data, Allison Dunning

Theses and Dissertations

The purpose of this research is to examine the bootstrap and jackknife as methods for estimating the variance of the AUC from a study using a complex sampling design and to determine which characteristics of the sampling design effects this estimation. Data from a one-stage cluster sampling design of 10 clusters was examined. Factors included three true AUCs (.60, .75, and .90), three prevalence levels (50/50, 70/30, 90/10) (non-disease/disease), and finally three number of clusters sampled (2, 5, or 7). A simulated sample was constructed for each of the 27 combinations of AUC, prevalence and number of clusters. Estimates of …

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Xprime: A Method Incorporating Expert Prior Information Into Motif Exploration, Rachel Lynn Poulsen Apr 2009

Xprime: A Method Incorporating Expert Prior Information Into Motif Exploration, Rachel Lynn Poulsen

Theses and Dissertations

One of the primary goals of active research in molecular biology is to better understand the process of transcription regulation. An important objective in understanding transcription is identifying transcription factors that directly regulate target genes. Identifying these transcription factors is a key step toward eliminating genetic diseases or disease susceptibilities that are encoded inside deoxyribonucleic acid (DNA). There is much uncertainty and variation associated with transcription factor binding sites, requiring these sites to be represented stochastically. Although typically each transcription factor prefers to bind to a specific DNA word, it can bind to different variations of that DNA word. In …

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Detecting Near-Earth Objects Using Cross-Correlation With A Point Spread Function, Anthony P. O'Dell Mar 2009

Detecting Near-Earth Objects Using Cross-Correlation With A Point Spread Function, Anthony P. O'Dell

Theses and Dissertations

This thesis describes a process to help discover Near-Earth Objects (NEOs) of larger than 140 meters in diameter from ground based telescopes. The process involves using Nyquist sampling rate to take data from a ground-based telescope and measuring the atmospheric seeing parameter, r0, at the time of data collection. r0 is then used to create a point spread function (PSF) for a NEO at the visual magnitude limit of the telescope and exposure time. This PSF is cross-correlated with the Nyquist sampling rate image from the telescope to reduce the noise and therefore increase the detection probability of …

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Measuring Skill Importance In Women's Soccer And Volleyball, Michelle L. Allan Mar 2009

Measuring Skill Importance In Women's Soccer And Volleyball, Michelle L. Allan

Theses and Dissertations

The purpose of this study is to demonstrate how to measure skill importance for two sports: soccer and volleyball. A division I women's soccer team filmed each home game during a competitive season. Every defensive, dribbling, first touch, and passing skill was rated and recorded for each team. It was noted whether each sequence of plays led to a successful shot. A hierarchical Bayesian logistic regression model is implemented to determine how the performance of the skill affects the probability of a successful shot. A division I women's volleyball team rated each skill (serve, pass, set, etc.) and recorded rally …

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Demonstration And Verification Of A Broad Spectrum Anomalous Dispersion Effects Tool For Index Of Refraction And Optical Turbulence Calculations, J. Jean Cohen Mar 2009

Demonstration And Verification Of A Broad Spectrum Anomalous Dispersion Effects Tool For Index Of Refraction And Optical Turbulence Calculations, J. Jean Cohen

Theses and Dissertations

An atmospheric optical turbulence strength model with a broad wavelength range of 355nm (ultraviolet) to 8.6m (radio frequencies) has been created at AFIT and implemented into the High Energy Laser End-to-End Operational Simulation tool (HELEEOS). This modeling and simulation tool is a first principles atmospheric propagation and characterization model. Within HELEEOS lies the High-Resolution Transmission Molecular Absorption (HITRAN) database, containing 1,734,469 spectral lines for 37 different molecules as of version 12.0 (2004). HITRAN affords HELEEOS incredible accuracy for electromagnetic (EM) propagation prediction. A full understanding of optical turbulence is needed to successfully predict EM radiation propagation, particularly within the application …

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Robust Sensitivity Analysis For The Joint Improvised Explosive Device Defeat Organization (Jieddo) Proposal Selection Model, Christina J. Willy Mar 2009

Robust Sensitivity Analysis For The Joint Improvised Explosive Device Defeat Organization (Jieddo) Proposal Selection Model, Christina J. Willy

Theses and Dissertations

Throughout Operations Iraqi Freedom and Enduring Freedom, the Department of Defense (DoD) faced challenges not experienced in our previous military operations. The enemy’s unwavering dedication to the use of improvised explosive devices (IEDs) against the coalition forces continues to challenge the day-to-day operations of the current war. The Joint Improvised Explosive Device Defeat Organization’s (JIEDDO) proposal solicitation process enables military and non-military organizations to request funding for the development of Counter-Improvised Explosive Device (C-IED) projects. Decision Analysis (DA) methodology serves as a tool to assist the decision maker (DM) in making an informed decision. This research applies Value Focused Thinking …

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Creating Multi Objective Value Functions From Non-Independent Values, Christopher D. Richards Mar 2009

Creating Multi Objective Value Functions From Non-Independent Values, Christopher D. Richards

Theses and Dissertations

Decisions are made every day and by everyone. As these decisions become more important, involve higher costs and affect a broader group of stakeholders it becomes essential to establish a more rigorous strategy than simply intuition or "going with your gut". In the past several decades, the concept of Value Focused Thinking (VFT) has gained much acclaim in assisting Decision Makers (DMs) in this very effort. By identifying and organizing what a DM values VFT is able to decompose the original problem and create a mathematical model to score and rank alternatives to be chosen. But what if the decision …

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Using Agent-Based Modeling To Evaluate Uas Behaviors In A Target-Rich Environment, Joseph A. Van Kuiken Mar 2009

Using Agent-Based Modeling To Evaluate Uas Behaviors In A Target-Rich Environment, Joseph A. Van Kuiken

Theses and Dissertations

The trade-off between accuracy and speed is a re-occurring dilemma in many facets of military performance evaluation. This is an especially important issue in the world of ISR. One of the most progressive areas of ISR capabilities has been the utilization of Unmanned Aircraft Systems (UAS). Many people believe that the future of UAS lies in smaller vehicles flying in swarms. We use the agent-based System Effectiveness and Analysis Simulation (SEAS) to create a simulation environment where different configurations of UAS vehicles can process targets and provide output that allows us to gain insight into the benefits and drawbacks of …

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Characterizing The Statistical Properties And Global Distribution Of Dansgaard-Oeschger Events, Andrea Michelle Thomas Mar 2009

Characterizing The Statistical Properties And Global Distribution Of Dansgaard-Oeschger Events, Andrea Michelle Thomas

Theses and Dissertations

Ice core records from Greenland have shown times of rapid warming during the most recent glacial period, called Dansgaard-Oeschger (D-O) events. D-O events are important to our understanding of both past climate systems and modern climate volatility. In this paper, we present new approaches for statistically evaluating the existence of cyclicity in D-O events and the possible lagged correlation between the Greenland and Antarctica temperature records. Specifically, we consider permutation testing and bootstrapping methodologies for assessing the cyclicity of D-O events and the correlation between the Greenland and Antarctica records. We find that there is not enough evidence to conclude …

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Tolerance Intervals In Random-Effects Models, Kakotan Sanogo Dec 2008

Tolerance Intervals In Random-Effects Models, Kakotan Sanogo

Theses and Dissertations

In the pharmaceutical setting, it is often necessary to establish the shelf life of a drug product and sometimes suitable to assess the risk of product failure at the desired expiry period. The current statistical methodology use confidence intervals for the predicted mean to establish the expiry period and prediction intervals for a predicted new assay value or a tolerance interval for a proportion of the population for use in a risk assessment. A major concern is that most methodology treat a homogeneous subpopulation, say batch, either as a fixed effect and therefore uses a fixed-effects regression model (Graybill, 1976) …

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Parameter Estimation For The Beta Distribution, Claire Elayne Bangerter Owen Nov 2008

Parameter Estimation For The Beta Distribution, Claire Elayne Bangerter Owen

Theses and Dissertations

The beta distribution is useful in modeling continuous random variables that lie between 0 and 1, such as proportions and percentages. The beta distribution takes on many different shapes and may be described by two shape parameters, alpha and beta, that can be difficult to estimate. Maximum likelihood and method of moments estimation are possible, though method of moments is much more straightforward. We examine both of these methods here, and compare them to three more proposed methods of parameter estimation: 1) a method used in the Program Evaluation and Review Technique (PERT), 2) a modification of the two-sided power …

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Applications Of The Bivariate Gamma Distribution In Nutritional Epidemiology And Medical Physics, Jolene Barker Sep 2008

Applications Of The Bivariate Gamma Distribution In Nutritional Epidemiology And Medical Physics, Jolene Barker

Theses and Dissertations

In this thesis the utility of a bivariate gamma distribution is explored. In the field of nutritional epidemiology a nutrition density transformation is used to reduce collinearity. This phenomenon will be shown to result due to the independent variables following a bivariate gamma model. In the field of radiation oncology paired comparison of variances is often performed. The bivariate gamma model is also appropriate for fitting correlated variances. A method for simulating bivariate gamma random variables is presented. This method is used to generate data from several bivariate gamma models and the asymptotic properties of a test statistic, suggested for …

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Application Of Optimization Techniques To Spectrally Modulated, Spectrally Encoded Waveform Design, Todd W. Beard Sep 2008

Application Of Optimization Techniques To Spectrally Modulated, Spectrally Encoded Waveform Design, Todd W. Beard

Theses and Dissertations

A design process is demonstrated for a coexistent scenario containing Spectrally Modulated, Spectrally Encoded (SMSE) and Direct Sequence Spread Spectrum (DSSS) signals. Coexistent SMSE-DSSS designs are addressed under both perfect and imperfect DSSS code tracking conditions using a non-coherent delay-lock loop (DLL). Under both conditions, the number of SMSE subcarriers and subcarrier spacing are the optimization variables of interest. For perfect DLL code tracking conditions, the GA and RSM optimization processes are considered independently with the objective function being end-to-end DSSS bit error rate. A hybrid GA-RSM optimization process is used under more realistic imperfect DLL code tracking conditions. In …

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Variable Selection In Competing Risks Using The L1-Penalized Cox Model, Xiangrong Kong Sep 2008

Variable Selection In Competing Risks Using The L1-Penalized Cox Model, Xiangrong Kong

Theses and Dissertations

One situation in survival analysis is that the failure of an individual can happen because of one of multiple distinct causes. Survival data generated in this scenario are commonly referred to as competing risks data. One of the major tasks, when examining survival data, is to assess the dependence of survival time on explanatory variables. In competing risks, as with ordinary univariate survival data, there may be explanatory variables associated with the risks raised from the different causes being studied. The same variable might have different degrees of influence on the risks due to different causes. Given a set of …

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A Confidence Paradigm For Classification Systems, Nathan J. Leap Sep 2008

A Confidence Paradigm For Classification Systems, Nathan J. Leap

Theses and Dissertations

There is no universally accepted methodology to determine how much confidence one should have in a classifier output. This research proposes a framework to determine the level of confidence in an indication from a classifier system where the output is or can be transformed into a posterior probability estimate. This is a theoretical framework that attempts to unite the viewpoints of the classification system developer (or engineer) and the classification system user (or war-fighter). The paradigm is based on the assumptions that the system confidence acts like, or can be modeled as a value and that indication confidence can be …

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Generalized Random Walks, Their Trees, And The Transformation Method Of Option Pricing, Thomas Gordon Stewart Aug 2008

Generalized Random Walks, Their Trees, And The Transformation Method Of Option Pricing, Thomas Gordon Stewart

Theses and Dissertations

The random walk is a powerful model. Chemistry, Physics, and Finance are just a few of the disciplines that model with the random walk. It is clear from its varied uses that despite its simplicity, the simple random walk it very flexible. There is one major drawback, however, to the simple random walk and the geometric random walk. The limiting distribution is either normal, lognormal, or a levy process with infinite variance. This thesis introduces an new random walk aimed at overcoming this drawback. Because the simple random walk and the geometric random walk are special cases of the proposed …

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Assessing Multivariate Heritability Through Nonparametric Methods, Benjamin Alan Carper Jul 2008

Assessing Multivariate Heritability Through Nonparametric Methods, Benjamin Alan Carper

Theses and Dissertations

The similarities between generations of living subjects are often quantified by heritability. By distinguishing genotypic variation, or variation due to parental pairings, from phenotypic variation, or normal intraspecies variation, the heritability of traits can be estimated. Due to the multivariate nature of many traits, such as size and shape, computation of heritability can be difficult. Also, assessment of the variation of the heritability estimate is extremely difficult. This study uses nonparametric methods, namely the randomization test and the bootstrap, to obtain both a measure of the extremity of the observed heritability and an assessment of the uncertainty.

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Ordinal Regression To Evaluate Student Ratings Data, Emily Brooke Bell Jul 2008

Ordinal Regression To Evaluate Student Ratings Data, Emily Brooke Bell

Theses and Dissertations

Student evaluations are the most common and often the only method used to evaluate teachers. In these evaluations, which typically occur at the end of every term, students rate their instructors on criteria accepted as constituting exceptional instruction in addition to an overall assessment. This presentation explores factors that influence student evaluations using the teacher ratings data of Brigham Young University from Fall 2001 to Fall 2006. This project uses ordinal regression to model the probability of an instructor receiving a good, average, or poor rating. Student grade, instructor status, class level, student gender, total enrollment, term, GE class status, …

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A Naive, Robust And Stable State Estimate, Todd Gordon Remund Jun 2008

A Naive, Robust And Stable State Estimate, Todd Gordon Remund

Theses and Dissertations

A naive approach to filtering for feedback control of dynamic systems that is robust and stable is proposed. Simulations are run on the filters presented to investigate the robustness properties of each filter. Each simulation with the comparison of the filters is carried out using the usual mean squared error. The filters to be included are the classic Kalman filter, Krein space Kalman, two adjustments to the Krein filter with input modeling and a second uncertainty parameter, a newly developed filter called the Naive filter, bias corrected Naive, exponentially weighted moving average (EWMA) Naive, and bias corrected EWMA Naive filter.

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Statistical Methods For Image Registration And Denoising, Matthew D. Sambora Jun 2008

Statistical Methods For Image Registration And Denoising, Matthew D. Sambora

Theses and Dissertations

This dissertation describes research into image processing techniques that enhance military operational and support activities. The research extends existing work on image registration by introducing a novel method that exploits local correlations to improve the performance of projection-based image registration algorithms. The dissertation also extends the bounds on image registration performance for both projection-based and full-frame image registration algorithms and extends the Barankin bound from the one-dimensional case to the problem of two-dimensional image registration. It is demonstrated that in some instances, the Cramer-Rao lower bound is an overly-optimistic predictor of image registration performance and that under some conditions, the …

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Optimal Interest Rate For A Borrower With Estimated Default And Prepayment Risk, Scott T. Howard May 2008

Optimal Interest Rate For A Borrower With Estimated Default And Prepayment Risk, Scott T. Howard

Theses and Dissertations

Today's mortgage industry is constantly changing, with adjustable rate mortgages (ARM), loans originated to the so-called "subprime" market, and volatile interest rates. Amid the changes and controversy, lenders continue to originate loans because the interest paid over the loan lifetime is profitable. Measuring the profitability of those loans, along with return on investment to the lender is assessed using Actuarial Present Value (APV), which incorporates the uncertainty that exists in the mortgage industry today, with many loans defaulting and prepaying. The hazard function, or instantaneous failure rate, is used as a measure of probability of failure to make a payment. …

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