Statistics and Probability Commons^™

Curds And Whey: Little Miss Muffit's Contribution To Multivariate Linear Regression, John Cameron Kidd

Undergraduate Honors Capstone Projects

A common multivariate statistical problem is the prediction of two or more response variables using two or more predictor variables. The simplest model for this situation is the multivariate linear regression model. The standard least squares estimation for this model involves regressing each response variable separately on all the predictor variables. Breiman and Friedman [1] show how to take advantage of correlations among the response variables to increase the predictive accuracy for each of the response variable with an algorithm they call Curds and Whey. In this report, I describe an implementation of the Curds and Whey algorithm in …

Variable Selection In Nonparametric And Semiparametric Regression Models, Liangjun Su, Yonghui Zhang

Research Collection School Of Economics

This chapter reviews the literature on variable selection in nonparametric and semiparametric regression models via shrinkage. We highlight recent developments on simultaneous variable selection and estimation through the methods of least absolute shrinkage and selection operator (Lasso), smoothly clipped absolute deviation (SCAD) or their variants, but restrict our attention to nonparametric and semiparametric regression models. In particular, we consider variable selection in additive models, partially linear models, functional/varying coefficient models, single index models, general nonparametric regression models, and semiparametric/nonparametric quantile regression models.

Creating A User Satisfaction Index From A Parsimonious Survey Instrument, Brian Barthel

All Graduate Theses, Dissertations, and Other Capstone Projects

In this paper we present a comprehensive method for creating a user satisfaction index using a survey instrument. First we construct a parsimonious survey instrument, using the PageRank Centrality, to measure attributes of user satisfaction. Then confirmatory factor analysis is applied to extract ``weights'' on the questions that are used in a linear model of computing the user satisfaction index. Throughout the paper an analysis of an existing data set is implemented to illustrate the proposed method. In addition the validity of the confirmatory factor model is tested using bootstrap sampling.

An Analysis Of The Educational Value And Impact Of A Dual, Versus Single, Robotic Surgical Console In The Training Of Obgyn Residents, Joseph E. Patruno Md, Hubert K. Huang Ms, Med, Michelle W. Huang Md, Thomas Hutchinson Md, Martin A. Martino Md

Department of Obstetrics & Gynecology

No abstract provided.

Participation In Perinatal Interventional Research: Which Characteristics Matter?, Hai-Yen T. Nguyen Md, Joanne Quiñones Md, Msce, Daniel G. Kiefer Md, Anita Kurt Phd, Rn, Felisa Saldutti, John C. Smulian Md, Mph

Department of Obstetrics & Gynecology

No abstract provided.

Revising Common Core Georgia Performance Standards Statistics Lesson Plans To Better Align With Statistical Practice, Rachel Bonilla

College of Graduate Studies: Theses & Dissertations

In this thesis, lesson plans provided by the Georgia Department of Education are revised to give students better exposure and practice working with real-life data. Three learning tasks and a performance task are presented covering a unit lesson on statistical regression. The development of Georgia statistics curriculum standards are reviewed and presented.

Cusum Generalized Variance Charts, Yuxiang Li

College of Graduate Studies: Theses & Dissertations

The commonly recommended charts for monitoring the mean vector are affected by a shit in the covariance matrix. As in the univariate case, a chart for monitoring for a change in the covariance matrix should be examined first before examining the chart used to monitor for a change in the mean vector.

A New Method For The Comparison Of Survival Distributions, Jaymie Shanahan

Theses and Dissertations

The assessment of overall homogeneity of time-to-event curves is a key element in survival analysis in biomedical research. The currently commonly used testing methods, e.g. log-rank test, Wilcoxon test, and Kolmogorov-Smirnov test, may have a significant loss of statistical testing power under certain circumstances. In this thesis we replicate a testing method (Lin & Xu, 2009) that is robust for the comparison of the overall homogeneity of survival curves based on the absolute difference of the area under the survival curves using normal approximation by Greenwood's formula, and propose a new weight component to their test statistic. The weight component …

Protein Identification Using Bayesian Stochastic Search, Christina Nicole Lewis

Theses and Dissertations

Current methods for protein identification in tandem mass spectrometry (MS/MS) involve database searches or de novo peptide sequencing, with database searches being the standard method. With database searches, issues arise when the species is not in the database. Shortcomings of de novo peptide sequencing and database searches include chemical noise, overly complex fragments, and incomplete b and y ion sequences. Here we present a Bayesian approach to identifying peptides. Our model uses prior information about the average relative abundances of bond cleavages and the prior probability of any particular amino acid sequence. The proposed likelihood function is composed of two …

Modeling Mixed Unfolding/Monotone Dichotomous Item Exams, Na Yang

Theses and Dissertations

Item response theory (IRT) is widely applied to analyze educational and psychological assessments. Readily available IRT implementations allow for two common types of models: monotone models used for dominance scales (Guttman 1950; Rasch 1960/1980; Birnbaum 1968; Mokken 1971) and unfolding models used for proximity scales (Coombs, 1964; Andrich, 1996; Roberts, Donoghue and Laughlin, 2000).

When an exam contains items following both types of models, there is currently no method to distinguish the item types, estimate their characteristics, or estimate the examinee characteristics. Thus, there is no existing methodology to simultaneously analyze items like ``At a minimum, I am in favor …

Permutation Testing For Covariance Matrices, With Applications In Shape Analysis, Blake Cassidy Hill

Theses and Dissertations

In many applications, it is of interest to compare covariance structures. In this work, we propose hypothesis tests for comparing covariance matrices for data in different groups, especially in shape analysis. The main motivation for the work is comparing covariance matrices of the size and shapes of damaged versus undamaged DNA molecules. A practical motivation behind analyzing the differences between these DNA covariance matrices is to compare the variation between the two groups during situations where the molecules are repairing. The testing methods proposed in this dissertation consist of three types of permutation testing methods for differences in covariance structures. …

Advanced Methodology Developments In Mixture Cure Models, Chao Cai

Theses and Dissertations

Modern medical treatments have substantially improved cure rates for many chronic diseases and have generated increasing interest in appropriate statistical models to handle survival data with non-negligible cure fractions. The mixture cure models are designed to model such data set, which assume that studied population is a mixture of being cured and uncured. In this dissertation, I will develop two programs named smcure and NPHMC in R. The first program aims to facilitate estimating two popular mixture cure models: the proportional hazards (PH) mixture cure model and accelerated failure time (AFT) mixture cure model. The second program focuses on designing …

Initiation And Continuation Of Randomized Trials After The Publication Of A Trial Stopped Early For Benefit Asking The Same Study Question: Stopit-3 Study Design, Gabriela J. Prutsky, Juan Domecq, Patricia J. Erwin, Matthias Briel, Victor M. Montori, Elie A. Akl, Joerg J. Meerpohl, Dirk Bassler, Stefan Schandelmaier, Stephen D. Walter, Qi Zhou, Pablo Coello, Lorenzo Moja, Martin Walter, Kristian Thorlund, Paul Glasziou, Regina Kunz, Ignacio Ferreira-Gonzalez, Jason Busse, Xin Sun, Annette Kristiansen, Benjamin Kasenda, Osama Qasim-Agha, Gennaro Pagano, Hector Pardo-Hernandez, Gerard Urrutia, Mohammad Murad, Gordon Guyatt

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

Randomized control trials (RCTs) stopped early for benefit (truncated RCTs) are increasingly common and, on average, overestimate the relative magnitude of benefit by approximately 30%. Investigators stop trials early when they consider it is no longer ethical to enroll patients in a control group. The goal of this systematic review is to determine how investigators of ongoing or planned RCTs respond to the publication of a truncated RCT addressing a similar question.

Methods/design

We will conduct systematic reviews to update the searches of 210 truncated RCTs to identify similar trials ongoing at the time of publication, or started …

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 …

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 …

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 …

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.