Longitudinal Data Analysis and Time Series Commons^™

Hierarchical Vector Auto-Regressive Models And Their Applications To Multi-Subject Effective Connectivity, Cristina Gorrostieta, Mark Fiecas, Hernando Ombao, Erin Burke, Steven Cramer

Mark Fiecas

Tools And Methods To Optimize The Analysis Of Telescopic Performance Metrics On Sofia, Steven R. Wilson, Holger Jakob, Stefan Teufel, Zaheer Ali, Jeffrey Van Cleve, Brian Eney, Greg Perryman

STAR Program Research Presentations

SOFIA is an infrared observatory mounted on a modified 747 engineered to do infrared astronomy at 45000 feet. The telescope equipment contains a number of sensors and stabilizers that allow the telescope to capture images while mounted in a moving plane. We have developed methods to analyze the performance of the telescope assembly that will help improve the stabilization and image capturing performance of the observatory. Here we present reusable methods to analyze telescope performance data that will enable improvements in the quality of the scientific data that is produced by the SOFIA. This poster focuses on the multi-flight performance …

Nba Salaries: Assessing True Player Value, Michael Ghirardo

Statistics

This paper analyzes and calculates an advanced NBA statistic that is becoming more and more widely used in the NBA. The Adjusted plus-minus (APM) statistic measures a player’s contribution, independent of all other players on the court. The most appealing aspect to the APM is that it only attempts to capture how a team’s scoring margin changes with a particular player on and off the court. Scoring margin in basketball effects winning percentage greatly, so it only makes sense that players with high APM’s will increase their team’s scoring margin and, therefore, help win games. The APM statistic is not …

Emirical Assessment Of The Future Performance Of The S&P 500 Losers, Nicholas Powers

Statistics

In the Wall Street Journal in early 2013, there was an article posted by Andrew Bary that explored a trend in the previous 3 years of the S&P 500. The article pointed out that the average returns for the top 10 percentage decliners for 2009, 2010, and 2011 outperformed the S&P 500 for the first two weeks of the next year. These top 10 percentage decliners or losers well enough to bet on. This study looks to see if there is statistical evidence that the losers outperformed the S&P 500.

Geographic And Temporal Epidemiology Of Campylobacteriosis, Jennifer Weisent

Doctoral Dissertations

Campylobacteriosis is a leading cause of gastroenteritis in the United States. The focus of this research was to (i) analyze and predict spatial and temporal patterns and associations for campylobacteriosis risk and (ii) compare the utility of advanced modeling methods. Laboratory-confirmed Campylobacter case data, obtained from the Foodborne Diseases Active Surveillance Network were used in all investigations.

We compared the accuracy of forecasting techniques for campylobacteriosis risk in Minnesota, Oregon and Georgia and found that time series regression, decomposition, and Box-Jenkins Autoregressive Integrated Moving Averages reliably predict monthly risk of infection for campylobacteriosis. Decomposition provided the fastest, most accurate, user-friendly …

Seasonal Decomposition For Geographical Time Series Using Nonparametric Regression, Hyukjun Gweon

Electronic Thesis and Dissertation Repository

A time series often contains various systematic effects such as trends and seasonality. These different components can be determined and separated by decomposition methods. In this thesis, we discuss time series decomposition process using nonparametric regression. A method based on both loess and harmonic regression is suggested and an optimal model selection method is discussed. We then compare the process with seasonal-trend decomposition by loess STL (Cleveland, 1979). While STL works well when that proper parameters are used, the method we introduce is also competitive: it makes parameter choice more automatic and less complex. The decomposition process often requires that …

Analysis Of Continuous Longitudinal Data With Arma(1, 1) And Antedependence Correlation Structures, Sirisha Mushti

Mathematics & Statistics Theses & Dissertations

Longitudinal or repeated measure data are common in biomedical and clinical trials. These data are often collected on individuals at scheduled times resulting in dependent responses. Inference methods for studying the behavior of responses over time as well as methods to study the association with certain risk factors or covariates taking into account the dependencies are of great importance. In this research we focus our study on the analysis of continuous longitudinal data. To model the dependencies of the responses over time, we consider appropriate correlation structures generated by the stationary and non-stationary time-series models. We develop new estimation procedures …

Global Quantitative Assessment Of The Colorectal Polyp Burden In Familial Adenomatous Polyposis Using A Web-Based Tool, Patrick M. Lynch, Jeffrey S. Morris, William A. Ross, Miguel A. Rodriguez-Bigas, Juan Posadas, Rossa Khalaf, Diane M. Weber, Valerie O. Sepeda, Bernard Levin, Imad Shureiqi

Jeffrey S. Morris

Background: Accurate measures of the total polyp burden in familial adenomatous polyposis (FAP) are lacking. Current assessment tools include polyp quantitation in limited-field photographs and qualitative total colorectal polyp burden by video.

Objective: To develop global quantitative tools of the FAP colorectal adenoma burden.

Design: A single-arm, phase II trial.

Patients: Twenty-seven patients with FAP.

Intervention: Treatment with celecoxib for 6 months, with before-treatment and after-treatment videos posted to an intranet with an interactive site for scoring.

Main Outcome Measurements: Global adenoma counts and sizes (grouped into categories: less than 2 mm, 2-4 mm, and greater than 4 mm) were …

Bayesian Inferences For Beta Semiparametric Mixed Models To Analyze Longitudinal Neuroimaging Data, Xiaofeng Wang, Yingxing Li

Xiaofeng Wang

Diffusion tensor imaging (DTI) is a quantitative magnetic resonance imaging technique that measures the three-dimensional diffusion of water molecules within tissue through the application of multiple diffusion gradients. This technique is rapidly increasing in popularity for studying white matter properties and structural connectivity in the living human brain. The major measure derived from the DTI process is known as fractional anisotropy, a continuous measure restricted on the interval (0,1). Motivated from a DTI study of multiple sclerosis, we use a beta semiparametric mixed-effect regression model for the longitudinal neuroimaging data. This work extends the generalized additive model methodology with beta …

State Level Earned Income Tax Credit’S Effects On Race And Age: An Effective Poverty Reduction Policy, Anthony J. Barone

CMC Senior Theses

In this paper, I analyze the effectiveness of state level Earned Income Tax Credit programs on improving of poverty levels. I conducted this analysis for the years 1991 through 2011 using a panel data model with fixed effects. The main independent variables of interest were the state and federal EITC rates, minimum wage, gross state product, population, and unemployment all by state. I determined increases to the state EITC rates provided only a slight decrease to both the overall white below-poverty population and the corresponding white childhood population under 18, while both the overall and the under-18 black population for …

The Psychological Impacts Of False Positive Ovarian Cancer Screening: Assessment Via Mixed And Trajectory Modeling, Amanda T. Wiggins

Theses and Dissertations--Epidemiology and Biostatistics

Ovarian cancer (OC) is the fifth most common cancer among women and has the highest mortality of any cancer of the female reproductive system. The majority (61%) of OC cases are diagnosed at a distant stage. Because diagnoses occur most commonly at a late-stage and prognosis for advanced disease is poor, research focusing on the development of effective OC screening methods to facilitate early detection in high-risk, asymptomatic women is fundamental in reducing OC-specific mortality. Presently, there is no screening modality proven efficacious in reducing OC-mortality. However, transvaginal ultrasonography (TVS) has shown value in early detection of OC. TVS presents …

A Comparison Of Periodic Autoregressive And Dynamic Factor Models In Intraday Energy Demand Forecasting, Thomas Mestekemper, Goeran Kauermann, Michael Smith

Michael Stanley Smith

We suggest a new approach for forecasting energy demand at an intraday resolution. Demand in each intraday period is modeled using semiparametric regression smoothing to account for calendar and weather components. Residual serial dependence is captured by one of two multivariate stationary time series models, with dimension equal to the number of intraday periods. These are a periodic autoregression and a dynamic factor model. We show the benefits of our approach in the forecasting of district heating demand in a steam network in Germany and aggregate electricity demand in the state of Victoria, Australia. In both studies, accounting for weather …

Constructing And Evaluating An Autoregressive House Price Index, Chaitra Nagaraja, Lawrence Brown

Chaitra H Nagaraja

No abstract provided.

Bayesian Approaches To Copula Modelling, Michael S. Smith

Michael Stanley Smith

Copula models have become one of the most widely used tools in the applied modelling of multivariate data. Similarly, Bayesian methods are increasingly used to obtain efficient likelihood-based inference. However, to date, there has been only limited use of Bayesian approaches in the formulation and estimation of copula models. This article aims to address this shortcoming in two ways. First, to introduce copula models and aspects of copula theory that are especially relevant for a Bayesian analysis. Second, to outline Bayesian approaches to formulating and estimating copula models, and their advantages over alternative methods. Copulas covered include Archimedean, copulas constructed …

Quantifying Temporal Correlations: A Test-Retest Evaluation Of Functional Connectivity In Resting-State Fmri, Mark Fiecas, Hernando Ombao, Dan Van Lunen, Richard Baumgartner, Alexandre Coimbra, Dai Feng

Mark Fiecas

There have been many interpretations of functional connectivity and proposed measures of temporal correlations between BOLD signals across different brain areas. These interpretations yield from many studies on functional connectivity using resting-state fMRI data that have emerged in recent years. However, not all of these studies used the same metrics for quantifying the temporal correlations between brain regions. In this paper, we use a public-domain test–retest resting-state fMRI data set to perform a systematic investigation of the stability of the metrics that are often used in resting-state functional connectivity (FC) studies. The fMRI data set was collected across three different …