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Longitudinal Data Analysis and Time Series Commons

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All Articles in Longitudinal Data Analysis and Time Series

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Inversion Copulas From Nonlinear State Space Models With An Application To Inflation Forecasting, Michael S. Smith, Worapree Ole Maneesoonthorn 2018 Melbourne Business School

Inversion Copulas From Nonlinear State Space Models With An Application To Inflation Forecasting, Michael S. Smith, Worapree Ole Maneesoonthorn

Michael Stanley Smith

We propose the construction of copulas through the inversion of nonlinear state space models. These copulas allow for new time series models that have the same serial dependence structure as a state space model, but with an arbitrary marginal distribution, and flexible density forecasts. We examine the time series properties of the copulas, outline serial dependence measures, and estimate the models using likelihood-based methods. Copulas constructed from three example state space models are considered: a stochastic volatility model with an unobserved component, a Markov switching autoregression, and a Gaussian linear unobserved component model. We show that all three inversion copulas ...


Spatio-Temporal Dynamics Of Atlantic Cod Bycatch In The Maine Lobster Fishery And Its Impacts On Stock Assessment, Robert E. Boenish 2018 University of Maine

Spatio-Temporal Dynamics Of Atlantic Cod Bycatch In The Maine Lobster Fishery And Its Impacts On Stock Assessment, Robert E. Boenish

Electronic Theses and Dissertations

Of the most iconic fish species in the world, the Atlantic cod (Gadus morhua, hereafter, cod) has been a mainstay in the North Atlantic for centuries. While many global fish stocks have received increased pressure with the advent of new, more efficient fishing technology in the mid-20th century, exceptional pressure has been placed on this prized gadoid. Bycatch, or the unintended catch of organisms, is one of the biggest global fisheries issues. Directly resulting from the failed recovery of cod in the GoM, attention has been placed as to possible sources of unaccounted catch. Among the most prominent is ...


Model Misspecification And Assumption Violations With The Linear Mixed Model: A Meta-Analysis, Brandon LeBeau, Yoon Ah Song, Wei Cheng Liu 2018 University of Iowa

Model Misspecification And Assumption Violations With The Linear Mixed Model: A Meta-Analysis, Brandon Lebeau, Yoon Ah Song, Wei Cheng Liu

Department of Psychological and Quantitative Foundations Publications

This meta analysis attempts to synthesize the Monte Carlo literature for the linear mixed model under a longitudinal framework. The empirical type I error rate will serve as the effect size and Monte Carlo simulation conditions will be coded to serve as moderator variables. The type I error rate for the fixed and random effects will be explored as the primary dependent variable. Effect sizes were coded from 13 studies, resulting in a total of 4,002 and 621 effect sizes for fixed and random effects. Meta-regression and proportional odds models were used to explore variation in the empirical type ...


Misspecification Of The Random Effect Structure: Implications For The Linear Mixed Model, Brandon LeBeau 2018 University of Iowa

Misspecification Of The Random Effect Structure: Implications For The Linear Mixed Model, Brandon Lebeau

Department of Psychological and Quantitative Foundations Publications

The linear mixed model is a commonly used model for longitudinal or nested data due to its ability to account for the dependency of nested data. Researchers typically rely on the random effects to adequately account for the dependency due to correlated data, however serial correlation can also be used. If the random effect structure is misspecified (perhaps due to convergence problems), can the addition of serial correlation overcome this misspecification and allow for unbiased estimation and accurate inferences? This study explored this question with a simulation. Simulation results show that the fixed effects are unbiased, however inflation of the ...


Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard 2018 University of Louisville

Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard

Electronic Theses and Dissertations

Electrophysiological measurements have been used in recent history to classify instantaneous physiological configurations, e.g., hand gestures. This work investigates the feasibility of working with changes in physiological configurations over time (i.e., longitudinally) using a variety of algorithms from the machine learning domain. We demonstrate a high degree of classification accuracy for a binary classification problem derived from electromyography measurements before and after a 35-day bedrest. The problem difficulty is increased with a more dynamic experiment testing for changes in astronaut sensorimotor performance by taking electromyography and force plate measurements before, during, and after a jump from a small ...


An Investigation Of The Effects Of Taking Remedial Math In College On Degree Attainment And College Gpa Using Multiple Imputation And Propensity Score Matching, Meghan A. Clovis 2018 Florida International University

An Investigation Of The Effects Of Taking Remedial Math In College On Degree Attainment And College Gpa Using Multiple Imputation And Propensity Score Matching, Meghan A. Clovis

FIU Electronic Theses and Dissertations

Enrollment in degree-granting postsecondary institutions in the U.S. is increasing, as are the numbers of students entering academically underprepared. Students in remedial mathematics represent the largest percentage of total enrollment in remedial courses, and national statistics indicate that less than half of these students pass all of the remedial math courses in which they enroll. In response to the low pass rates, numerous studies have been conducted into the use of alternative modes of instruction to increase passing rates. Despite myriad studies into course redesign, passing rates have seen no large-scale improvement. Lacking is a thorough investigation into preexisting ...


Building A Better Risk Prevention Model, Steven Hornyak 2018 Houston County Schools

Building A Better Risk Prevention Model, Steven Hornyak

National Youth-At-Risk Conference Savannah

This presentation chronicles the work of Houston County Schools in developing a risk prevention model built on more than ten years of longitudinal student data. In its second year of implementation, Houston At-Risk Profiles (HARP), has proven effective in identifying those students most in need of support and linking them to interventions and supports that lead to improved outcomes and significantly reduces the risk of failure.


Modelling The Common Risk Among Equities Using A New Time Series Model, Jingjia Chu 2018 The University of Western Ontario

Modelling The Common Risk Among Equities Using A New Time Series Model, Jingjia Chu

Electronic Thesis and Dissertation Repository

A new additive structure of multivariate GARCH model is proposed where the dynamic changes of the conditional correlation between the stocks are aggregated by the common risk term. The observable sequence is divided into two parts, a common risk term and an individual risk term, both following a GARCH type structure. The conditional volatility of each stock will be the sum of these two conditional variance terms. All the conditional volatility of the stock can shoot up together because a sudden peak of the common volatility is a sign of the system shock.

We provide sufficient conditions for strict stationarity ...


Investigating The Role Of Prescription Drug Monitoring Programs In Reducing Rates Of Opioid-Related Poisonings, Nathan James Pauly 2018 University of Kentucky

Investigating The Role Of Prescription Drug Monitoring Programs In Reducing Rates Of Opioid-Related Poisonings, Nathan James Pauly

Theses and Dissertations--Pharmacy

The United States is in the midst of an opioid epidemic. In addition to other system level interventions, almost all states have responded to the crisis by implementing prescription drug monitoring programs (PDMPs). PDMPs are state-level interventions that track the dispensing of Controlled Substances. Data generated at the time of medication dispensing is uploaded to a central data server that may be used to assist in identifying drug diversion, medication misuse, or potentially aberrant prescribing practices.

Prior studies assessing the impact of PDMPs on trends in opioid-related morbidity have often failed to take into account the wide heterogeneity of program ...


Improved Methods And Selecting Classification Types For Time-Dependent Covariates In The Marginal Analysis Of Longitudinal Data, I-Chen Chen 2018 University of Kentucky

Improved Methods And Selecting Classification Types For Time-Dependent Covariates In The Marginal Analysis Of Longitudinal Data, I-Chen Chen

Theses and Dissertations--Epidemiology and Biostatistics

Generalized estimating equations (GEE) are popularly utilized for the marginal analysis of longitudinal data. In order to obtain consistent regression parameter estimates, these estimating equations must be unbiased. However, when certain types of time-dependent covariates are presented, these equations can be biased unless an independence working correlation structure is employed. Moreover, in this case regression parameter estimation can be very inefficient because not all valid moment conditions are incorporated within the corresponding estimating equations. Therefore, approaches using the generalized method of moments or quadratic inference functions have been proposed for utilizing all valid moment conditions. However, we have found that ...


Penalized Mixed-Effects Ordinal Response Models For High-Dimensional Genomic Data In Twins And Families, Amanda E. Gentry 2018 Virginia Commonwealth University

Penalized Mixed-Effects Ordinal Response Models For High-Dimensional Genomic Data In Twins And Families, Amanda E. Gentry

Theses and Dissertations

The Brisbane Longitudinal Twin Study (BLTS) was being conducted in Australia and was funded by the US National Institute on Drug Abuse (NIDA). Adolescent twins were sampled as a part of this study and surveyed about their substance use as part of the Pathways to Cannabis Use, Abuse and Dependence project. The methods developed in this dissertation were designed for the purpose of analyzing a subset of the Pathways data that includes demographics, cannabis use metrics, personality measures, and imputed genotypes (SNPs) for 493 complete twin pairs (986 subjects.) The primary goal was to determine what combination of SNPs and ...


Time Series Copulas For Heteroskedastic Data, Ruben Loaiza-Maya, Michael S. Smith, Worapree Maneesoonthorn 2017 Melbourne Business School

Time Series Copulas For Heteroskedastic Data, Ruben Loaiza-Maya, Michael S. Smith, Worapree Maneesoonthorn

Michael Stanley Smith

We propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We suggest copulas for first-order Markov series, and then extend them to higher orders and multivariate series. We derive the copula of a volatility proxy, based on which we propose new measures of volatility dependence, including co-movement and spillover in multivariate series. In general, these depend upon the marginal distributions of the series. Using exchange rate returns, we show that the resulting copula models can capture
their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models, and produce more accurate value-at-risk forecasts.


Variational Bayes Estimation Of Discrete-Margined Copula Models With Application To Ime Series, Ruben Loaiza-Maya, Michael S. Smith 2017 Melbourne Business School

Variational Bayes Estimation Of Discrete-Margined Copula Models With Application To Ime Series, Ruben Loaiza-Maya, Michael S. Smith

Michael Stanley Smith

We propose a new variational Bayes estimator for high-dimensional copulas with discrete, or a combination of discrete and continuous, margins. The method is based on a variational approximation to a tractable augmented posterior, and is faster than previous likelihood-based approaches. We use it to estimate drawable vine copulas for univariate and multivariate Markov ordinal and mixed time series. These have dimension $rT$, where $T$ is the number of observations and $r$ is the number of series, and are difficult to estimate using previous methods. 
The vine pair-copulas are carefully selected to allow for heteroskedasticity, which is a feature of most ...


Prairie Strips Improve Biodiversity And The Delivery Of Multiple Ecosystem Services From Corn–Soybean Croplands, John C. Tyndall, Lisa A. Schulte-Moore, Jarad Niemi, Matthew J. Helmers, Matthew Z. Liebman, J. Gordon Arbuckle Jr., David E. James, Randall K. Kalka, Matthew E. O'Neal, Mark D. Tomer, Heidi Asbjornsen, Pauline Drobney, Jeri Neal, Gary Van Ryswyk, Christopher C. Witte 2017 Iowa State University

Prairie Strips Improve Biodiversity And The Delivery Of Multiple Ecosystem Services From Corn–Soybean Croplands, John C. Tyndall, Lisa A. Schulte-Moore, Jarad Niemi, Matthew J. Helmers, Matthew Z. Liebman, J. Gordon Arbuckle Jr., David E. James, Randall K. Kalka, Matthew E. O'Neal, Mark D. Tomer, Heidi Asbjornsen, Pauline Drobney, Jeri Neal, Gary Van Ryswyk, Christopher C. Witte

Natural Resource Ecology and Management Publications

Loss of biodiversity and degradation of ecosystem services from agricultural lands remain important challenges in the United States despite decades of spending on natural resource management. To date, conservation investment has emphasized engineering practices or vegetative strategies centered on monocultural plantings of nonnative plants, largely excluding native species from cropland. In a catchment-scale experiment, we quantified the multiple effects of integrating strips of native prairie species amid corn and soybean crops, with prairie strips arranged to arrest run-off on slopes. Replacing 10% of cropland with prairie strips increased biodiversity and ecosystem services with minimal impacts on crop production. Compared with ...


Environmentally-Driven Variation In The Population Dynamics Of Gulf Menhaden (Brevoortia Patronus), Grant D. Adams 2017 University of Southern Mississippi

Environmentally-Driven Variation In The Population Dynamics Of Gulf Menhaden (Brevoortia Patronus), Grant D. Adams

Master's Theses

Gulf Menhaden (Brevoortia patronus) is an abundant forage fish distributed throughout the Northern Gulf of Mexico (NGOM). Gulf Menhaden support the second largest fishery, by weight, in the United States and represent a key linkage between upper and lower trophic levels. Variation in the population dynamics can, therefore, pose consequences for the ecology and economy in the NGOM. Here we aim to understand variation in the individual and population dynamics of Gulf Menhaden throughout ontogeny and how such variation relates to environmental processes. We utilized a suite of fishery-dependent and –independent, remote sensing, modeled, and in situ data to explicitly ...


Socioeconomic Status, Air Quality And Geographic Variation In Emergency Room Visits For Acute Bronchitis On The California Central Coast, Sean Lang-Brown, Heather W. Starnes, Gary B. Hughes 2017 California Polytechnic State University

Socioeconomic Status, Air Quality And Geographic Variation In Emergency Room Visits For Acute Bronchitis On The California Central Coast, Sean Lang-Brown, Heather W. Starnes, Gary B. Hughes

Symposium

IMPORTANCE: Analysis of geospatial variation in acute bronchitis due to socioeconomic and environmental factors can allow the efficient delivery of resources to populations most at risk.

OBJECTIVE: We sought to determine if small scale variation in socioeconomic factors and emergency room (ER) visits for acute bronchitis are associated in small cities or rural communities. We also modeled the effects of air quality on daily rates of ER visits for acute bronchitis in the context of socioeconomic factors to investigate modifying relationships.

DESIGN, SETTING, AND PARTICIPANTS: We examined ER visits for acute bronchitis in San Luis Obispo and Santa Barbara counties ...


Burden Of Atopic Dermatitis In The United States: Analysis Of Healthcare Claims Data In The Commercial, Medicare, And Medi-Cal Databases, Sulena Shrestha, Raymond Miao, Li Wang, Jingdong Chao, Huseyin Yuce, Wenhui Wei 2017 STATinMED Research/SIMR, Inc.

Burden Of Atopic Dermatitis In The United States: Analysis Of Healthcare Claims Data In The Commercial, Medicare, And Medi-Cal Databases, Sulena Shrestha, Raymond Miao, Li Wang, Jingdong Chao, Huseyin Yuce, Wenhui Wei

Publications and Research

Comparative data on the burden of atopic dermatitis (AD) in adults relative to the general population are limited. We performed a large-scale evaluation of the burden of disease among US adults with AD relative to matched non-AD controls, encompassing comorbidities, healthcare resource utilization (HCRU), and costs, using healthcare claims data. The impact of AD disease severity on these outcomes was also evaluated.


The Importance Of Inhaler Technique In Measuring And Calculating Inhaler Adherence, And Its Clinical Outcomes, Imran Sulaiman 2017 Royal College of Surgeons in Ireland

The Importance Of Inhaler Technique In Measuring And Calculating Inhaler Adherence, And Its Clinical Outcomes, Imran Sulaiman

PhD theses

Depending on the population studied, cross-sectional observational studies suggest that between 14%-90% of patients do not use their pressurized metered dose inhaler correctly, while 50-60% misuse a dry powder inhaler. This means that unless incorrect technique is acounted for a significant underestimation of how much medication the person actually obtained may be made.

The aim of this thesis was to objectively determine the frequency and importance of inhaler technique errors and to combine these with inhaler use to provide an acurate method of calculating adherence. I then investigated different patterns of inhaler use, determinants of inhaler use and the ...


Determining Graduation Rates In Engineering For Community College Transfer Students Using Data Mining, Marcia Laugerman, Diane T. Rover, Mack C. Shelley, Steven K. Mickelson 2017 Iowa State University

Determining Graduation Rates In Engineering For Community College Transfer Students Using Data Mining, Marcia Laugerman, Diane T. Rover, Mack C. Shelley, Steven K. Mickelson

Diane Rover

This study presents a unique synthesized set of data for community college students entering the university with the intention of earning a degree in engineering. Several cohorts of longitudinal data were combined with transcript-level data from both the community college and the university to measure graduation rates in engineering. The emphasis of the study is to determine academic variables that had significant correlations with graduation in engineering, and levels of these academic variables. The article also examines the utility of data mining methods for understanding the academic variables related to achievement in science, technology, engineering, and mathematics. The practical purpose ...


The Acquisition And Analysis Of Electroencephalogram Data For The Classification Of Benign Partial Epilepsy Of Childhood With Centrotemporal Spikes, Jessica A. Scarborough 2017 University of San Francisco

The Acquisition And Analysis Of Electroencephalogram Data For The Classification Of Benign Partial Epilepsy Of Childhood With Centrotemporal Spikes, Jessica A. Scarborough

Master's Theses

In this thesis, I will expand upon each step in the process of acquiring and analyzing electroencephalogram (EEG) for the classification of benign childhood epilepsy with centrotemporal spikes. Despite huge advancements in the field of health informatics—natural language processing, machine learning, predictive modeling—there are significant barriers to the access of clinical data. These barriers include information blocking, privacy policy concerns, and a lack of stakeholder support. We will see that these roadblocks are all responsible for stunting biomedical research in some way, including my own experiences in acquiring the data for the second chapter of this thesis.

This ...


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