Physical Sciences and Mathematics Commons^™

Location And Capacity Modeling Of Network Interchanges, Aldo D. Fabregas

USF Tampa Graduate Theses and Dissertations

Network design decisions, especially those pertaining to urban infrastructure, are made by a central authority or network leader, and taking into consideration the network users or followers. These network decision problems are formulated as non-linear bi-level programming problems. In this work, a continuous network design problem (CNDP) and discrete network design problem (DNDP) bi-level optimization programs are proposed and solved in the context of transportation planning. The solution strategy involved reformulation and linearization as a single-level program by introducing the optimality conditions of the lower level problem into the upper level problem. For the CNDP, an alternative linearization algorithm (modified …

Uncontrolled Hypertension And Associated Factors In Hypertensive Patients At The Primary Healthcare Center Luis H. Moreno, Panama: A Feasibility Study, Roderick Ramon Chen Camano

USF Tampa Graduate Theses and Dissertations

Background: According to the World Health Organization (WHO), hypertension is a major risk factor for cardiovascular disease (CVD), renal impairment, peripheral vascular disease, and blindness. In Panama, a recent study estimated the prevalence of hypertension at 38.5% in the two main provinces of the country, with a rate of uncontrolled hypertension of 47.2%.

Objectives: The aims of this study were to assess the feasibility of the study design and to describe the characteristics of the hypertensive population and the physician's adherence to Panamanian antihypertensive protocols and their relationship with uncontrolled hypertension.

Methods: This is a cross-sectional study of adult hypertensive …

Multiple Calibrations In Integrative Data Analysis: A Simulation Study And Application To Multidimensional Family Therapy, Kristin Wynn Hall

USF Tampa Graduate Theses and Dissertations

A recent advancement in statistical methodology, Integrative Data Analyses (IDA Curran & Hussong, 2009) has led researchers to employ a calibration technique as to not violate an independence assumption. This technique uses a randomly selected, simplified correlational structured subset, or calibration, of a whole data set in a preliminary stage of analysis. However, a single calibration estimator suffers from instability, low precision and loss of power. To overcome this limitation, a multiple calibration (MC; Greenbaum et al., 2013; Wang et al., 2013) approach has been developed to produce better estimators, while still removing a level of dependency in the data …

A Latent Mixture Approach To Modeling Zero-Inflated Bivariate Ordinal Data, Rajendra Kadel

USF Tampa Graduate Theses and Dissertations

Multivariate ordinal response data, such as severity of pain, degree of disability, and satisfaction with a healthcare provider, are prevalent in many areas of research including public health, biomedical, and social science research. Ignoring the multivariate features of the response variables, that is, by not taking the correlation between the errors across models into account, may lead to substantially biased estimates and inference. In addition, such multivariate ordinal outcomes frequently exhibit a high percentage of zeros (zero inflation) at the lower end of the ordinal scales, as compared to what is expected under a multivariate ordinal distribution. Thus, zero inflation …

Statistical Topics Applied To Pressure And Temperature Readings In The Gulf Of Mexico, Malena Kathleen Allison

USF Tampa Graduate Theses and Dissertations

The field of statistical research in weather allows for the application of old and new methods, some of which may describe relationships between certain variables better such as temperatures and pressure. The objective of this study was to apply a variety of traditional and novel statistical methods to analyze data from the National Data Buoy Center, which records among other variables barometric pressure, atmospheric temperature, water temperature and dew point temperature. The analysis included attempts to better describe and model the data as well as to make estimations for certain variables. The following statistical methods were utilized: linear regression, non-response …

Effectiveness Of Propensity Score Methods In A Multilevel Framework: A Monte Carlo Study, Aarti P. Bellara

USF Tampa Graduate Theses and Dissertations

Propensity score analysis has been used to minimize the selection bias in observational studies to identify causal relationships. A propensity score is an estimate of an individual's probability of being placed in a treatment group given a set of covariates. Propensity score analysis aims to use the estimate to create balanced groups, akin to a randomized experiment. This study used Monte Carlo methods to examine the appropriateness of using propensity score methods to achieve balance between groups on observed covariates and reproduce treatment effect estimates in multilevel studies. Specifically, this study examined the extent to which four different propensity score …

The Positive Illusory Bias And Adhd Symptoms: A New Measurement Approach, Sarah A. Fefer

USF Tampa Graduate Theses and Dissertations

The purpose of this study was to investigate perceptions of academic and social competence among adolescents with a continuum of inattentive and hyperactive/impulsive symptoms. Past literature suggests that children with Attention-Deficit/Hyperactivity Disorder (ADHD) display self-perceptions that are overly positive compared to external indicators of competence, a phenomenon that is referred to as the positive illusory bias (PIB; Owens, Goldfine, Evangelista, Hoza, & Kaiser, 2007). The PIB is well supported among children with ADHD, and recent research suggests that the PIB persists into adolescence. To date, research on the PIB has relied on difference scores (i.e., an indicator of competence is …

A Monte Carlo Approach To Change Point Detection In A Liver Transplant, Alexia Melissa Makris

USF Tampa Graduate Theses and Dissertations

Patient survival post liver transplant (LT) is important to both the patient and the center's accreditation, but over the years physicians have noticed that distant patients struggle with post LT care. I hypothesized that patient's distance from the transplant center had a detrimental effect on post LT survival. I suspected Hepatitis C (HCV) and Hepatocellular Carcinoma (HCC) patients would deteriorate due to their recurrent disease and there is a need for close monitoring post LT. From the current literature it was not clear if patients' distance from a transplant center affects outcomes post LT. Firozvi et al. (Firozvi AA, 2008) …

Age Dependent Analysis And Modeling Of Prostate Cancer Data, Nana Osei Mensa Bonsu

USF Tampa Graduate Theses and Dissertations

Growth rate of prostate cancer tumor is an important aspect of understanding the natural history of prostate cancer. Using real prostate cancer data from the SEER database with tumor size as a response variable, we have clustered the cancerous tumor sizes into age groups to enhance its analytical behavior. The rate of change of the response variable as a function of age is given for each cluster. Residual analysis attests to the quality of the analytical model and the subject estimates. In addition, we have identified the probability distribution that characterize the behavior of the response variable and proceeded with …

Bayesian Estimation Of Panel Data Fractional Response Models With Endogeneity: An Application To Standardized Test Rates, Lawrence Kessler

USF Tampa Graduate Theses and Dissertations

In this paper I propose Bayesian estimation of a nonlinear panel data model with a fractional dependent variable (bounded between 0 and 1). Specifically, I estimate a panel data fractional probit model which takes into account the bounded nature of the fractional response variable. I outline estimation under the assumption of strict exogeneity as well as when allowing for potential endogeneity. Furthermore, I illustrate how transitioning from the strictly exogenous case to the case of endogeneity only requires slight adjustments. For comparative purposes I also estimate linear specifications of these models and show how quantities of interest such as marginal …

Tracking Atlantic Hurricanes Using Statistical Methods, Elizabeth Caitlin Miller

USF Tampa Graduate Theses and Dissertations

Creating an accurate hurricane location forecasting model is of the utmost importance because of the safety measures that need to occur in the days and hours leading up to a storm's landfall. Hurricanes can be incredibly deadly and costly, but if people are given adequate warning, many lives can be spared. This thesis seeks to develop an accurate model for predicting storm location based on previous location, previous wind speed, and previous pressure. The models are developed using hurricane data from 1980-2009.

Statistical Analysis And Modeling Of Brain Tumor Data: Histology And Regional Effects, Keshav Prasad Pokhrel

USF Tampa Graduate Theses and Dissertations

Comprehensive statistical models for non-normally distributed cancerous tumor sizes are

of prime importance in epidemiological studies, whereas a long term forecasting models

can facilitate in reducing complications and uncertainties of medical progress. The statistical

forecasting models are critical for a better understanding of the disease and supply

appropriate treatments. In addition such a model can be used for the allocations of budgets,

planning, control and evaluations of ongoing efforts of prevention and early detection of

the diseases.

In the present study, we investigate the effects of age, demography, and race on primary

brain tumor sizes using quantile regression methods to …

Optimization In Non-Parametric Survival Analysis And Climate Change Modeling, Iuliana Teodorescu

USF Tampa Graduate Theses and Dissertations

Many of the open problems of current interest in probability and statistics involve complicated data

sets that do not satisfy the strong assumptions of being independent and identically distributed. Often,

the samples are known only empirically, and making assumptions about underlying parametric

distributions is not warranted by the insufficient information available. Under such circumstances,

the usual Fisher or parametric Bayes approaches cannot be used to model the data or make predictions.

However, this situation is quite often encountered in some of the main challenges facing statistical,

data-driven studies of climate change, clinical studies, or financial markets, to name a few. …

Statistical Analysis And Modeling Of Prostate Cancer, Yiu Ming Chan

USF Tampa Graduate Theses and Dissertations

The objective of the present study is to address some important questions related to prostate cancer treatments and survivorship among White and African American men. It is commonly understood that the risk of developing prostate cancer is higher in African American men than the other races. However, using parametric analysis, this study demonstrates that this perception is a "myth" not a "reality". The study further identifies the existence of racial/ethnic disparities by comparing the average mean tumor size, the median of survival time, and the survival function between White and African American men. These results underline the necessity of understanding …

Measuring Technical Efficiency Of The Japanese Professional Football (Soccer) League (J1 And J2), Dan Zhao

USF Tampa Graduate Theses and Dissertations

This is the first paper to measure the efficiency of the Japan Professional Football League clubs both the first and the second divisions. In Chapter 1, a non-parametric method Data Envelopment Development (DEA) is used and the data covers six seasons from 2005 to 2010. The input variables are payroll, cost besides payroll, and total assets. The output variables are attendance, revenue, and points awarded. I use different output combinations in order to check the sensitivity of the efficiency of the clubs after the original composition. This is also the first research to include more than one division of the …