Likelihood-Based Methods For Analysis Of Copy Number Variation Using Next Generation Sequencing Data.,
2017
University of Louisville
Likelihood-Based Methods For Analysis Of Copy Number Variation Using Next Generation Sequencing Data., Udika Iroshini Bandara
Electronic Theses and Dissertations
A Copy Number Variation (CNV) detection problem is considered using Circular Binary Segmentation (CBS) procedures, including newly developed procedures based on likelihood ratio tests with the parametric bootstrap for models based on discrete distributions for count data (Poisson and negative binomial) and a widely-used DNAcopy package. Results from the literature concerning maximum likelihood estimation for the negative binomial distribution are reviewed. The Newton-Raphson method is used to find the root of the derivative of the profile log likelihood function when applicable, and it is proven that this method converges to the true Maximum Likeihood Estimate (MLE), if the starting point …
Estimation Of The Three Key Parameters And The Lead Time Distribution In Lung Cancer Screening.,
2017
University of Louisville
Estimation Of The Three Key Parameters And The Lead Time Distribution In Lung Cancer Screening., Ruiqi Liu
Electronic Theses and Dissertations
This dissertation contains three research projects on cancer screening probability modeling. Cancer screening is the primary technique for early detection. The goal of screening is to catch the disease early before clinical symptoms appear. In these projects, the three key parameters and lead time distribution were estimated to provide a statistical point of view on the effectiveness of cancer screening programs. In the first project, cancer screening probability model was used to analyze the computed tomography (CT) scan group in the National Lung Screening Trial (NLST) data. Three key parameters were estimated using Bayesian approach and Markov Chain Monte Carlo …
A Characterization Of A Value Added Model And A New Multi-Stage Model For Estimating Teacher Effects Within Small School Systems,
2017
University of Nebraska-Lincoln
A Characterization Of A Value Added Model And A New Multi-Stage Model For Estimating Teacher Effects Within Small School Systems, Julie M. Garai
Department of Statistics: Dissertations, Theses, and Student Research
At both the national and state level there is increasing pressure to develop metrics to determine if school systems are meeting educational objectives. All states mandate some form of assessment by standardized tests. One method currently used to model student test scores is Value Added Modeling (VAM), which models student scores as a product of classroom and school environments. One VAM approach is the Tennessee Value Added Assessment System (TVAAS) which models student gains from year to year. Teacher effects are included in this layered model, which estimates the teacher’s added value to a student score through best linear unbiased …
Using Mountain Snowpack To Predict Summer Water Availability In Semiarid Mountain Watersheds,
2017
Boise State University
Using Mountain Snowpack To Predict Summer Water Availability In Semiarid Mountain Watersheds, Rebecca Dawn Garst
Boise State University Theses and Dissertations
In the mountainous landscapes of the western United States, water resources are dominated by snowpack. As temperatures rise in spring and summer, the melting snow produces an increase in river flow levels. Reservoirs are used during this increase to retain surplus water, which is released to supplement growing season water supply once the peak flows decrease to below water demands. Once there is no longer surplus natural flow of water, the water accounting changes – referred to as the day of allocation (DOA), and water previously retained within the reservoir is used to supplement the lower flow levels. The amount …
First-In-Human Clinical Trial Of Oral Onc201 In Patients With Refractory Solid Tumors,
2017
Rutgers Cancer Institute of New Jersey
First-In-Human Clinical Trial Of Oral Onc201 In Patients With Refractory Solid Tumors, Mark N. Stein, Joseph R. Bertino, Howard L. Kaufman, Tina M. Mayer, Rebecca A. Moss, Ann W. Silk, Nancy Chan, Jyoti Malhotra, Loma Rodriguez, Joseph Aisner, Robert Aiken, Bruce G. Haffty, Robert S. Dipaola, Tracie Saunders, Andrew Zloza, Sherri Damare, Yasmeen Beckett, Bangning Yu, Saltanat Najmi, Christian Gabel, Sioghan Dickerson, Ling Zheng, Wafik S. El-Deiry, Joshua E. Allen, Martin Stogniew, Wolfgang Oster, Janice M. Mehnert
Internal Medicine Faculty Publications
Purpose: ONC201 is a small-molecule selective antagonist of the G protein–coupled receptor DRD2 that is the founding member of the imipridone class of compounds. A first-in-human phase I study of ONC201 was conducted to determine its recommended phase II dose (RP2D).
Experimental Design: This open-label study treated 10 patients during dose escalation with histologically confirmed advanced solid tumors. Patients received ONC201 orally once every 3 weeks, defined as one cycle, at doses from 125 to 625 mg using an accelerated titration design. An additional 18 patients were treated at the RP2D in an expansion phase to collect additional safety, …
Bayesian Approach On Short Time-Course Data Of Protein Phosphorylation, Casual Inference For Ordinal Outcome And Causal Analysis Of Dietary And Physical Activity In T2dm Using Nhanes Data.,
2017
University of Louisville
Bayesian Approach On Short Time-Course Data Of Protein Phosphorylation, Casual Inference For Ordinal Outcome And Causal Analysis Of Dietary And Physical Activity In T2dm Using Nhanes Data., You Wu
Electronic Theses and Dissertations
This dissertation contains three different projects in proteomics and causal inferences. In the first project, I apply a Bayesian hierarchical model to assess the stability of phosphorylated proteins under short-time cold ischemia. This study provides inference on the stability of these phosphorylated proteins, which is valuable when using these proteins as biomarkers for a disease. in the second project, I perform a comparative study of different confounding-adjusted to estimate the treatment effect when the outcome variable is ordinal using observational data. The adjusted U-statistics method is compared with other methods such as ordinal logistic regression, propensity score based stratification and …
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 …
Prediction Of Stress Increase In Unbonded Tendons Using Sparse Principal Component Analysis,
2017
Utah State University
Prediction Of Stress Increase In Unbonded Tendons Using Sparse Principal Component Analysis, Eric Mckinney
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
While internal and external unbonded tendons are widely utilized in concrete structures, the analytic solution for the increase in unbonded tendon stress, Δ���, is challenging due to the lack of bond between strand and concrete. Moreover, most analysis methods do not provide high correlation due to the limited available test data. In this thesis, Principal Component Analysis (PCA), and Sparse Principal Component Analysis (SPCA) are employed on different sets of candidate variables, amongst the material and sectional properties from the database compiled by Maguire et al. [18]. Predictions of Δ��� are made via Principal Component Regression models, and the method …
Impact Of Home Visit Capacity On Genetic Association Studies Of Late-Onset Alzheimer's Disease,
2017
University of Kentucky
Impact Of Home Visit Capacity On Genetic Association Studies Of Late-Onset Alzheimer's Disease, David W. Fardo, Laura E. Gibbons, Shubhabrata Mukherjee, M. Maria Glymour, Wayne Mccormick, Susan M. Mccurry, James D. Bowen, Eric B. Larson, Paul K. Crane
Biostatistics Faculty Publications
INTRODUCTION—Findings for genetic correlates of late-onset Alzheimer's disease (LOAD) in studies that rely solely on clinic visits may differ from those with capacity to follow participants unable to attend clinic visits.
METHODS—We evaluated previously identified LOAD-risk single nucleotide variants in the prospective Adult Changes in Thought study, comparing hazard ratios (HRs) estimated using the full data set of both in-home and clinic visits (n = 1697) to HRs estimated using only data that were obtained from clinic visits (n = 1308). Models were adjusted for age, sex, principal components to account for ancestry, and additional health indicators.
RESULTS …
Development Of Lower Rio Grande River Water Quality Transportation Numerical Model For Bi-National River Management,
2017
The University of Texas Rio Grande Valley
Development Of Lower Rio Grande River Water Quality Transportation Numerical Model For Bi-National River Management, Jose O. Gonzalez
Theses and Dissertations
Traditionally, water quality modelling has focused on modelling individual water bodies. However, water quality management problems must be analyzed at the larger scale to include influences from various water bodies that are interconnected. This paper provides a study on the hydrologic and quality transportation calculation by developing a hydrodynamic (unsteady state) channel routing model using a water-balanced approach. A one dimension Lagrangian river model was developed and applied to the 210 plus miles for the lower Rio Grande River Basin from the Falcon Dam to the head water of Brownsville that pours onto the Gulf of Mexico. This model can …
Imputation For Random Forests,
2017
Utah State University
Imputation For Random Forests, Joshua Young
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
This project introduces two new methods for imputation of missing data in random forests. The new methods are compared against other frequently used imputation methods, including those used in the randomForest package in R. To test the effectiveness of these methods, missing data are imputed into datasets that contain two missing data mechanisms including missing at random and missing completely at random. After imputation, random forests are run on the data and accuracies for the predictions are obtained. Speed is an important aspect in computing; the speeds for all the tested methods are also compared.
One of the new methods …
Tree-Based Regression For Interval-Valued Data,
2017
Utah State University
Tree-Based Regression For Interval-Valued Data, Chih-Ching Yeh
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
Regression methods for interval-valued data have been increasingly studied in recent years. As most of the existing works focus on linear models, it is important to note that many problems in practice are nonlinear in nature and therefore development of nonlinear regression tools for intervalvalued data is crucial. In this project, we propose a tree-based regression method for interval-valued data, which is well applicable to both linear and nonlinear problems. Unlike linear regression models that usually require additional constraints to ensure positivity of the predicted interval length, the proposed method estimates the regression function in a nonparametric way, so the …
Novel Bayesian Adaptive Clinical Trial Designs In Early Phases,
2017
The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences
Novel Bayesian Adaptive Clinical Trial Designs In Early Phases, Haitao Pan
Dissertations and Theses (Open Access)
Early phase, or phase I and phase II, trials are the first step in testing new medicines that have been developed in the lab. The main goal of phase I clinical trials is to establish the recommended dose of new drugs for phase II trials. For the cytotoxic drugs, the goal is to find maximum tolerated dose (MTD). The guiding principle for dose escalation in phase I trials is to avoid exposing too many patients to subtherapeutic doses while preserving safety and maintaining rapid accrual. Therefore, dose escalation methods, especially Bayesian designs, are recommended to be used in phase I …
A Tail-Based Test For Differential Expression Analysis And Pathway Analysis In Rna-Sequencing Data,
2017
The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences
A Tail-Based Test For Differential Expression Analysis And Pathway Analysis In Rna-Sequencing Data, Jiong Chen
Dissertations and Theses (Open Access)
RNA sequencing data have been abundantly generated in biomedical research for biomarker discovery and pathway analysis. Such data at the exon-level are usually heavily tailed and correlated. Conventional statistical tests based on the mean or median difference for differential expression likely suffer from low power when the between-group difference occurs mostly in the upper or lower tail of the distribution of gene expression. We propose a tail-based test to make comparisons between groups in terms of a specific distribution area rather than a single location. The proposed test, which is derived from quantile regression, adjusts for covariates and accounts for …
Implant Treatment In The Predoctoral Clinic: A Retrospective Database Study Of 1091 Patients,
2017
Marquette University
Implant Treatment In The Predoctoral Clinic: A Retrospective Database Study Of 1091 Patients, Soni Prasad, Christopher Hambrook, Eric Reigle, Katherine Sherman, Naveen K. Bansal, Arthur F. Hefti
Mathematics, Statistics and Computer Science Faculty Research and Publications
Purpose: This retrospective study was conducted at the Marquette University School of Dentistry to (1) characterize the implant patient population in a predoctoral clinic, (2) describe the implants inserted, and (3) provide information on implant failures.
Materials and Methods: The study cohort included 1091 patients who received 1918 dental implants between 2004 and 2012, and had their implants restored by a crown or a fixed dental prosthesis. Data were collected from patient records, entered in a database, and summarized in tables and figures. Contingency tables were prepared and analyzed by a chi-squared test. The cumulative survival probability of implants was …
A Linear-Linear Growth Model With Individual Change Point And Its Application To Ecls-K Data,
2017
University of Arkansas, Fayetteville
A Linear-Linear Growth Model With Individual Change Point And Its Application To Ecls-K Data, Ping Zhang
Graduate Theses and Dissertations
The latent growth curve model with piecewise functions is a useful analytics tool to investigate the growth trajectory consisted of distinct phases of development in observed variables. An interesting feature of the growth trajectory is the time point that the trajectory changes from one phase to another one. In this thesis, we propose a simple computational pipeline to locate the change point under the linear-linear piecewise model and apply it to the longitudinal study of reading and math ability in early childhood (from kindergarten to eighth grade). In the first step, we conduct the hypothesis testing to filter out the …
A Comparison Of Five Statistical Methods For Predicting Stream Temperature Across Stream Networks,
2017
Utah State University
A Comparison Of Five Statistical Methods For Predicting Stream Temperature Across Stream Networks, Maike F. Holthuijzen
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
The health of freshwater aquatic systems, particularly stream networks, is mainly influenced by water temperature, which controls biological processes and influences species distributions and aquatic biodiversity. Thermal regimes of rivers are likely to change in the future, due to climate change and other anthropogenic impacts, and our ability to predict stream temperatures will be critical in understanding distribution shifts of aquatic biota. Spatial statistical network models take into account spatial relationships but have drawbacks, including high computation times and data pre-processing requirements. Machine learning techniques and generalized additive models (GAM) are promising alternatives to the SSN model. Two machine learning …
Environmentally-Driven Variation In The Population Dynamics Of Gulf Menhaden (Brevoortia Patronus),
2017
University of Southern Mississippi
Environmentally-Driven Variation In The Population Dynamics Of Gulf Menhaden (Brevoortia Patronus), Grant D. Adams
Master's Theses
Gulf Menhaden (Brevoortia patronus) is an abundant forage fish distributed throughout the Northern Gulf of Mexico (NGOM). Gulf Menhaden support the second largest fishery, by weight, in the United States and represent a key linkage between upper and lower trophic levels. Variation in the population dynamics can, therefore, pose consequences for the ecology and economy in the NGOM. Here we aim to understand variation in the individual and population dynamics of Gulf Menhaden throughout ontogeny and how such variation relates to environmental processes. We utilized a suite of fishery-dependent and –independent, remote sensing, modeled, and in situ data …
Genomic And Physiological Approaches To Improve Drought Tolerance In Soybean,
2017
University of Arkansas, Fayetteville
Genomic And Physiological Approaches To Improve Drought Tolerance In Soybean, Avjinder Kaler
Graduate Theses and Dissertations
Drought stress is a major global constraint for crop production, and improving crop tolerance to drought is of critical importance. Direct selection of drought tolerance among genotypes for yield is limited because of low heritability, polygenic control, epistasis effects, and genotype by environment interactions. Crop physiology can play a major role for improving drought tolerance through the identification of traits associated with drought tolerance that can be used as indirect selection criteria in a breeding program. Carbon isotope ratio (δ13C, associated with water use efficiency), oxygen isotope ratio (δ18O, associated with transpiration), canopy temperature (CT), canopy wilting, and canopy coverage …
Bayesian Model Averaging With Change Points To Assess The Impact Of Vaccination And Public Health Interventions.,
2017
George Washington University
Bayesian Model Averaging With Change Points To Assess The Impact Of Vaccination And Public Health Interventions., Esra Kürüm, Joshua L Warren, Cynthia Schuck-Paim, Roger Lustig, Joseph A Lewnard, Rodrigo Fuentes, Christian A W Bruhn, Robert J Taylor, Lone Simonsen, Daniel M Weinberger
Global Health Faculty Publications
Background: Pneumococcal conjugate vaccines (PCVs) prevent invasive pneumococcal disease and pneumonia. However, some low-and middle-income countries have yet to introduce PCV into their immunization programs due, in part, to lack of certainty about the potential impact. Assessing PCV benefits is challenging because specific data on pneumococcal disease are often lacking, and it can be difficult to separate the effects of factors other than the vaccine that could also affect pneumococcal disease rates.
Methods: We assess PCV impact by combining Bayesian model averaging with change-point models to estimate the timing and magnitude of vaccine-associated changes, while controlling for seasonality and other …
