Statistics and Probability Commons^™

Estimating The Reproductive Numbers For The 2008-2009 Cholera Outbreaks In Zimbabwe, Zindoga Mukandavire, Shu Liao, Jin Wang, Holly Gaff, David L. Smith, J. Glenn Morris Jr.

Biological Sciences Faculty Publications

Cholera remains an important global cause of morbidity and mortality, capable of causing periodic epidemic disease. Beginning in August 2008, a major cholera epidemic occurred in Zimbabwe, with 98,585 reported cases and 4,287 deaths. The dynamics of such outbreaks, particularly in nonestuarine regions, are not well understood. We explored the utility of mathematical models in understanding transmission dynamics of cholera and in assessing the magnitude of interventions necessary to control epidemic disease. Weekly data on reported cholera cases were obtained from the Zimbabwe Ministry of Health and Child Welfare (MoHCW) for the period from November 13, 2008 to July 31, …

Statistical Analysis And Mechanistic Modeling Of Water Quality: Hillsborough Bay, Florida, Keith Hackett

USF Tampa Graduate Theses and Dissertations

Nutrient pollution has been identified as a significant threat to U.S. coastal and estuarine water quality. Though coastal and estuarine waters need nutrients to maintain a healthy, productive ecosystem, excess nutrients can lead to eutrophication. There are significant potential negative consequences associated with eutrophication, including loss of habitat, loss of economic activity, and direct threats to human health. Hillsborough Bay experienced eutrophication in the 1960s and 1970s due to a rapidly growing population and associated increases in nutrient pollution. These eutrophic conditions led to more frequent phytoplankton and macroalgae blooms and declines in seagrasses. To address these problems, a series …

Modeling Endogenous Treatment Eects With Heterogeneity: A Bayesian Nonparametric Approach, Xuequn Hu

USF Tampa Graduate Theses and Dissertations

This dissertation explores the estimation of endogenous treatment effects in the presence of heterogeneous responses. A Bayesian Nonparametric approach is taken to model the heterogeneity in treatment effects. Specifically, I adopt the Dirichlet Process Mixture (DPM) model to capture the heterogeneity and show that DPM often outperforms Finite Mixture Model (FMM) in providing more flexible function forms and thus better model fit. Rather than fixing the number of components in a mixture model, DPM allows the data and prior knowledge to determine the number of components in the data, thus providing an automatic mechanism for model selection.

Two DPM models …

Gender Differences In Lung Cancer Treatment And Survival, Margaret Anne Kowski

USF Tampa Graduate Theses and Dissertations

The objectives of this research were to test treatment and survival differences between women and men with lung cancer as there is minimal investigation in the literature. Three research questions were developed with statistical testing for gender differences based on similar cancer type, stage, treatment assignment and survival. Data for 44,863 primary lung cancer cases were collected from eight U.S. state-based cancer registries to investigate the research questions. The lung cancer incidence data included the morphological cell-types of adenocarcinoma (AC); squamous cell carcinoma (SCC); large cell carcinoma (LCC) and small cell carcinoma (SCC). Stage, grade, treatment type, as well as, …

Parametric And Bayesian Modeling Of Reliability And Survival Analysis, Carlos A. Molinares

USF Tampa Graduate Theses and Dissertations

The objective of this study is to compare Bayesian and parametric approaches to determine the best for estimating reliability in complex systems. Determining reliability is particularly important in business and medical contexts. As expected, the Bayesian method showed the best results in assessing the reliability of systems.

In the first study, the Bayesian reliability function under the Higgins-Tsokos loss function using Jeffreys as its prior performs similarly as when the Bayesian reliability function is based on the squared-error loss. In addition, the Higgins-Tsokos loss function was found to be as robust as the squared-error loss function and slightly more efficient. …

Meta-Analysis Of Single-Case Data: A Monte Carlo Investigation Of A Three Level Model, Corina M. Owens

USF Tampa Graduate Theses and Dissertations

Numerous ways to meta-analyze single-case data have been proposed in the literature, however, consensus on the most appropriate method has not been reached. One method that has been proposed involves multilevel modeling. This study used Monte Carlo methods to examine the appropriateness of Van den Noortgate and Onghena's (2008) raw data multilevel modeling approach to the meta-analysis of single-case data. Specifically, the study examined the fixed effects (i.e., the overall average baseline level and the overall average treatment effect) and the variance components (e.g., the between person within study variance in the average baseline level, the between study variance in …

Why Is An Einstein Ring Blue?, Jonathan Blackledge

Articles

Albert Einstein predicted the existence of `Einstein rings' as a consequence of his general theory of relativity. The phenomenon is a direct result of the idea that if a mass warps space-time then light (and other electromagnetic waves) will be `lensed' by the strong gravitational field produced by a large cosmological body such as a galaxy. Since 1998, when the first complete Einstein ring was observed, many more complete or partially complete Einstein rings have been observed in the radio and infrared spectra, for example, and by the Hubble Space Telescope in the optical spectrum. However, in the latter case, …

Computational Network Analysis Of The Anatomical And Genetic Organizations In The Mouse Brain, Shuiwang Ji

Computer Science Faculty Publications

Motivation: The mammalian central nervous system (CNS) generates high-level behavior and cognitive functions. Elucidating the anatomical and genetic organizations in the CNS is a key step toward understanding the functional brain circuitry. The CNS contains an enormous number of cell types, each with unique gene expression patterns. Therefore, it is of central importance to capture the spatial expression patterns in the brain. Currently, genome-wide atlas of spatial expression patterns in the mouse brain has been made available, and the data are in the form of aligned 3D data arrays. The sheer volume and complexity of these data pose significant challenges …

Neurological And Cardiovascular Outcomes After Cardiac Arrest At Six Regional Interventional Cardiology Centers In The United States 2007-2011, David B. Seder Md, Nainesh Patel Md, John Mcpherson Md, Paul W. Mcmullan Md, Karl B. Kern Md, Barbara Unger Rn, J Browning, Sudip Nanda Md, Facp, Melkon Hacobian Md, Michael B. Kelley Md, Niklas Nielsen Md, Phd, Michael R. Mooney Md

Department of Medicine

No abstract provided.

Death By Boredom: The Role Of Visual Processing Theory In Written Evaluation Communication, Stephanie D. H. Evergreen

Dissertations

Evaluation reporting is an educational act and, as such, should be communicated using principles that support cognition. This study drew upon visual processing theory and theory-based graphic design principles to develop the Evaluation Report Layout Checklist intended to guide report development and support cognition in the readers of evaluation reports. It was then reviewed by an expert panel and applied by a group of raters to a set of evaluation reports obtained from the Informal Science Education evaluation website with maximum variability sampling. Results showed fairly high exact percent agreement and strong to very strong correlation with the author’s ratings. …

Summative Confidence, Paul Cristian Gugiu

Dissertations

Often the singular goal of an evaluation is to render a summative conclusion of merit, worth or feasibility that is based on multiple streams of multidimensional data. Exacerbating this difficulty, conducting evaluations in real-world settings often necessitates implementation of less than ideal study designs. This reality gets further complicated by the standard method for estimating the precision of results via the confidence interval (CI). Traditional CIs offer a limited approach for understanding the precision of a summative conclusion. This dissertation develops and presents a unified approach for the construction of a CI for a summative conclusion (SC).

This study derived …

Robust Adaptive Scheme For Linear Mixed Models, Gabriel Asare Okyere

Dissertations

If the underlying distribution of a statistical model is known then a procedure which maximizes power and efficiency can be selected. For example, if the distribution of errors is known to be normal in a linear model then inference based on least squares maximizes power and efficiency. More generally, if this distribution is known then a ranked based inference based on the appropriate rank score function has maximum efficiency. In practice, though, this distribution is not known. Adaptive schemes are procedures which hopefully select appropriate methods to optimize the analysis.

Hogg (1974) presented an adaptive rank-based scheme for testing in …

Robust Nonparametric Methods For Regression To The Mean Model, Therawat Wisadrattanapong

Dissertations

Regression to the mean is a statistical phenomenon that often confounds treatment effects in experiments. Consider an experiment involving a treatment, in which a response is measured (baseline) on a subject then a treatment is applied and a second measurement is taken. Then under many bivariate models for the pair of responses (including the bivariate normal), the predicted response of the second measurement will regress to the mean. In experiments where the second response is only taken for a select sample, say above a cutoff value, then this regression to the mean effect may mistakenly be thought of as a …

Geriatric Experience Following Cardiac Arrest At Six Interventional Cardiology Centers In The United States 2007-2011, David B. Seder Md, Nainesh Patel Md, John A. Mcpherson Md, Paul W. Mcmullan Md, Karl B. Kern Md, Barbara T. Unger Rn, J Browning, Sudip Nanda Md, Facp, Melkon Hacobian Md, Michael B. Kelley Md, Niklas Nielsen Md, Phd, Michael R. Mooney Md

Department of Medicine

No abstract provided.

Post-Resuscitation Care Practices Following Cardiac Arrest At Six Regional Interventional Cardiology Centers In The United States 2007-2011, David B. Seder Md, Nainesh Patel Md, John A. Mcpherson Md, Paul W. Mcmullan Md, Karl B. Kern Md, Barbara T. Unger Rn, J Browning, Sudip Nanda Md, Facp, Melkon Hacobian Md, Michael B. Kelley Md, Niklas Nielsen Md, Phd, Michael R. Mooney Md

Department of Medicine

No abstract provided.

Evaluation Of Common Inherited Variants In Mitochondrial-Related And Microrna-Related Genes As Novel Risk Factors For Ovarian Cancer, Jennifer Permuth Wey

USF Tampa Graduate Theses and Dissertations

Epithelial ovarian cancer (EOC) is a leading cause of morbidity and mortality among women in the United States, and the etiology is incompletely understood. Common, low penetrant genetic variants such as single nucleotide polymorphisms (SNPs) likely contribute to a significant proportion of EOC. We examined whether SNPs in two understudied yet biologically important types of genes, mitochondrial-related and miRNA-related genes, may contribute to EOC susceptibility using data from a large, homogeneous study population of 1,815 EOC cases and 1,900 controls (frequency-matched on age-group and race/ethnicity) genotyped through stage 1 of an ongoing genome-wide association study. Inter-individual variation in genes involved …

Dna Methylation And Its Association With Prenatal Exposures And Pregnancy Outcomes, Jennifer Straughen

USF Tampa Graduate Theses and Dissertations

Altered DNA methylation may lead to suboptimal fetal programming, increasing the risk of adverse pregnancy outcomes such as small for gestational age (SGA); however, few studies have examined the associations between DNA methylation, prenatal exposures, and fetal outcomes. Cross-sectional data from a larger, ongoing study were used to assess the impact of prenatal smoking on gene specific methylation of umbilical cord blood derived DNA and to investigate the association between gene-specific methylation and risk of SGA. The association between gene-specific DNA methylation and birthweight was also assessed. Maternal and infant covariates were abstracted from medical records, cigarette smoke exposure was …

Oracle And Multiple Robustness Properties Of Survey Calibration Estimator In Missing Response Problem, Kwun Chuen Gary Chan

UW Biostatistics Working Paper Series

In the presence of missing response, reweighting the complete case subsample by the inverse of nonmissing probability is both intuitive and easy to implement. However, inverse probability weighting is not efficient in general and is not robust against misspecification of the missing probability model. Calibration was developed by survey statisticians for improving efficiency of inverse probability weighting estimators when population totals of auxiliary variables are known and when inclusion probability is known by design. In missing data problem we can calibrate auxiliary variables in the complete case subsample to the full sample. However, the inclusion probability is unknown in general …

Modification And Improvement Of Empirical Likelihood For Missing Response Problem, Kwun Chuen Gary Chan

UW Biostatistics Working Paper Series

An empirical likelihood (EL) estimator was proposed by Qin and Zhang (2007) for a missing response problem under a missing at random assumption. They showed by simulation studies that the finite sample performance of EL estimator is better than some existing estimators. However, the empirical likelihood estimator does not have a uniformly smaller asymptotic variance than other estimators in general. We consider several modifications to the empirical likelihood estimator and show that the proposed estimator dominates the empirical likelihood estimator and several other existing estimators in terms of asymptotic efficiencies. The proposed estimator also attains the minimum asymptotic variance among …

Modification And Improvement Of Empirical Liklihood For Missing Response Problem, Gary Chan

UW Biostatistics Working Paper Series

An empirical likelihood (EL) estimator was proposed by Qin and Zhang (2007) for a missing response problem under a missing at random assumption. They showed by simulation studies that the finite sample performance of EL estimator is better than some existing estimators. However, the empirical likelihood estimator does not have a uniformly smaller asymptotic variance than other estimators in general. We consider several modifications to the empirical likelihood estimator and show that the proposed estimator dominates the empirical likelihood estimator and several other existing estimators in terms of asymptotic efficiencies. The proposed estimator also attains the minimum asymptotic variance among …