Longitudinal Data Analysis and Time Series Commons^™

Multi-State Models For Natural History Of Disease, Amy Laird, Rebecca A. Hubbard, Lurdes Y. T. Inoue

UW Biostatistics Working Paper Series

Longitudinal studies are a useful tool for investigating the course of chronic diseases. Many chronic diseases can be characterized by a set of health states. We can improve our understanding of the natural history of the disease by modeling the sequence of visited health states and the duration in each state. However, in most applications, subjects are observed only intermittently. This observation scheme creates a major modeling challenge: the transition times are not known exactly, and in some cases the path through the health states is not known.

In this manuscript we review existing approaches for modeling multi-state longitudinal data. …

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 …

Errata And Comments For: Generalized Estimating Equations, 2nd Ed, Joseph M. Hilbe, James W. Hardin

Joseph M Hilbe

Errata and Comments for Hardin & Hilbe, Generalized Estimating Equations, 2nd ed (published 10 Dec, 2012)

Modelling Locally Changing Variance Structured Time Series Data By Using Breakpoints Bootstrap Filtering, Rajan Lamichhane

Mathematics & Statistics Theses & Dissertations

Stochastic processes have applications in many areas such as oceanography and engineering. Special classes of such processes deal with time series of sparse data. Studies in such cases focus in the analysis, construction and prediction in parametric models. Here, we assume several non-linear time series with additive noise components, and the model fitting is proposed in two stages. The first stage identifies the density using all the clusters information, without specifying any prior knowledge of the underlying distribution function of the time series. The effect of covariates is controlled by fitting the linear regression model with serially correlated errors. In …

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.

Discovering Exoplanets Through Hidden Markov Model Analysis, Jon Drobny

Rose-Hulman Undergraduate Research Publications

The goal for the project is to develop a Hidden Markov Model for the detection and characterization of extrasolar planets through the analysis of light curves.

Targeted Maximum Likelihood Estimation For Dynamic And Static Longitudinal Marginal Structural Working Models, Maya L. Petersen, Joshua Schwab, Susan Gruber, Nello Blaser, Michael Schomaker, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

This paper describes a targeted maximum likelihood estimator (TMLE) for the parameters of longitudinal static and dynamic marginal structural models. We consider a longitudinal data structure consisting of baseline covariates, time-dependent intervention nodes, intermediate time-dependent covariates, and a possibly time dependent outcome. The intervention nodes at each time point can include a binary treatment as well as a right-censoring indicator. Given a class of dynamic or static interventions, a marginal structural model is used to model the mean of the intervention specific counterfactual outcome as a function of the intervention, time point, and possibly a subset of baseline covariates. Because …

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 …

Joint Outcome Modeling Using Shared Frailties With Application To Temporal Streamflow Data, Lihua Li

Electronic Thesis and Dissertation Repository

Recently there has been tremendous interest in the development of tools for joint analysis of longitudinal data and time-to-event data. This has gained emphasis particularly in clinical studies, where longitudinal measurements on a response may be recorded along with a time-to-event outcome. Joint analysis of multiple outcomes beyond longitudinal and survival have also been considered, for example, joint analysis of a variety of generalized linear models including continuous and count data, or continuous and binomial data. With joint analysis of multiple outcomes, the interest may be analysis of one outcome conditional on the others, or, more typically, analysis of all …

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 …

Putting Artists On The Map: A Five Part Study Of Greater Cleveland Artists' Location Decisions - Part 3: Attitudinal Analysis - Artist Housing And Space Survey, Mark Salling, Gregory Soltis, Charles Post, Sharon Bliss, Ellen Cyran

Ellen Cyran

A series of reports detailing the residential and work space location preferences of Cuyahoga county's artists.

Putting Artists On The Map: A Five Part Study Of Greater Cleveland Artists' Location Decisions - Part 2: Profiles Of Artist Neighborhoods, Mark Salling, Gregory Soltis, Charles Post, Sharon Bliss, Ellen Cyran

Ellen Cyran

A series of reports detailing the residential and work space location preferences of Cuyahoga county's artists.

Putting Artists On The Map: A Five Part Study Of Greater Cleveland Artists' Location Decisions - Part 1: Summary Report, Mark Salling, Gregory Soltis, Charles Post, Sharon Bliss, Ellen Cyran

Ellen Cyran

A series of reports detailing the residential and work space location preferences of Cuyahoga county's artists.

Foreign-Born Population In Selected Ohio Cities, 1870 To 2000 A Brief Descriptive Report, Mark Salling, Ellen Cyran

Ellen Cyran

No abstract provided.

Putting Artists On The Map: A Five Part Study Of Greater Cleveland Artists' Location Decisions - Part 5: Properties Analysis - Artist Housing Characteristics, Mark Salling, Gregory Soltis, Charles Post, Sharon Bliss, Ellen Cyran

Ellen Cyran

A series of reports detailing the residential and work space location preferences of Cuyahoga county's artists.

Foreign Migration To The Cleveland-Akron-Lorain Metropolitan Area From 1995 To 2000, Mark Salling, Ellen Cyran

Ellen Cyran

This report is one of a series on migration to and from the region using the five percent Public Use Microdata Sample (PUMS) of the 2000 Census of Population and Housing and provides a description of foreign migrants moving to the Cleveland-Akron-Lorain (CAL) Consolidated Metropolitan Area (CMSA) from 1995 to 2000.* The report identifies the countries of origin of migrants and compares the demographic, socioeconomic, and housing characteristics of the foreign migrants to the CAL with other groups, including foreign migrants to Ohio and the nation, and, at times, to domestic migrants to and from the CAL.

Putting Artists On The Map: A Five Part Study Of Greater Cleveland Artists' Location Decisions - Part 4: Predictive Analysis - Regression Modeling, Mark Salling, Gregory Soltis, Charles Post, Sharon Bliss, Ellen Cyran

Ellen Cyran

A series of reports detailing the residential and work space location preferences of Cuyahoga county's artists.

Using The Census Bureau's Public Use Microdata For Migration Analysis, Mark Salling, Ellen Cyran

Ellen Cyran

Using the Census Bureau's Public Use Microdata for Migration Analysis, Proceedings of the annual conference of the Urban and Regional Information Systems Association, Vancouver, BC, Canada, September 2006, pp.336-348.

Is Obesity Socially Contagious?, Ciani Jean Sparks

Statistics

The main objective of this paper is to analyze three different articles that discuss whether obesity could be socially contagious. According to the World Health Organization in 2013, obesity is the fifth leading risk for deaths around the world. This disease has dramatically increased in the last decade, which has led scientists to believe there are other factors contributing to the epidemic besides genetics. The first article I analyzed, written by Nicholas Christakis and James Fowler, provided a logistic regression model to estimate the odds of a person becoming obese. The model included the explanatory variables: age, sex, education, smoking …

A Study Of Mexican Free-Tailed Bat Chirp Syllables: Bayesian Functional Mixed Modeling Of Nonstationary Time Series Data With Time-Dependent Spectra, Josue G. Martinez, Kirsten M. Bohn, Raymond J. Carroll, Jeffrey S. Morris

Jeffrey S. Morris

We describe a new approach to analyze chirp syllables of free-tailed bats from two regions of Texas in which they are predominant: Austin and College Station. Our goal is to characterize any systematic regional differences in the mating chirps and assess whether individual bats have signature chirps. The data are analyzed by modeling spectrograms of the chirps as responses in a Bayesian functional mixed model. Given the variable chirp lengths, we compute the spectrograms on a relative time scale interpretable as the relative chirp position, using a variable window overlap based on chirp length. We use 2D wavelet transforms to …

Persistence And Anti-Persistence: Theory And Software, Justin Quinn Veenstra

Electronic Thesis and Dissertation Repository

Persistent and anti-persistent time series processes show what is called hyperbolic decay. Such series play an important role in the study of many diverse areas such as geophysics and financial economics. They are also of theoretical interest. Fractional Gaussian noise (FGN) and fractionally-differeneced white noise are two widely known examples of time series models with hyperbolic decay. New closed form expressions are obtained for the spectral density functions of these models. Two lesser known time series models exhibiting hyperbolic decay are introduced and their basic properties are derived. A new algorithm for approximate likelihood estimation of the models using frequency …

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 …

Interactions Between Serotypes Of Dengue Highlight Epidemiological Impact Of Cross-Immunity, Nicholas Reich, Sourya Shrestha, Aaron King, Pejman Rohani, Justin Lessler, Siripen Kalayanarooj, In-Kyu Yoon, Robert Gibbons, Donald Burke, Derek Cummings

Nicholas G Reich

Dengue, a mosquito-borne virus of humans, infects over 50 million people annually. Infection with any of the four dengue serotypes induces protective immunity to that serotype, but does not confer long-term protection against infection by other serotypes. The immunological interactions between sero- types are of central importance in understanding epidemiological dynamics and anticipating the impact of dengue vaccines. We analysed a 38-year time series with 12 197 serotyped dengue infections from a hospital in Bangkok, Thailand. Using novel mechanistic models to represent different hypothesized immune interactions between serotypes, we found strong evidence that infec- tion with dengue provides substantial short-term …

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 …

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 …

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 …

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 …