Physical Sciences and Mathematics Commons^™

Primary Care-Based Educational Interventions To Decrease Risk Factors For Metabolic Syndrome For Adults With Major Psychotic And/Or Affective Disorders: A Systematic Review, Cynthia Nover, Sarah S. Jackson

Epidemiology Faculty Publications

Background

Individuals with major psychotic and/or affective disorders are at increased risk for developing metabolic syndrome due to lifestyle- and treatment-related factors. Numerous pharmacological and non-pharmacological interventions have been tested in inpatient and outpatient mental health settings to decrease these risk factors. This review focuses on primary care-based non-pharmacological (educational or behavioral) interventions to decrease metabolic syndrome risk factors in adults with major psychotic and/or affective disorders.

Methods

The authors conducted database searches of PsychINFO, MEDLINE and the Cochrane Database of Systematic Reviews, as well as manual searches and gray literature searches to identify included studies.

Results

The authors were …

Efficient And Long-Time Accurate Second-Order Methods For The Stokes-Darcy System, Wenbin Chen, Max Gunzburger, Dong Sun, Xiaoming Wan

Mathematics and Statistics Faculty Research & Creative Works

We propose and study two second order in time implicit-explicit methods for the coupled Stokes-Darcy system that governs flows in karst aquifers and other subsurface flow systems. the first method is a combination of a second-order backward differentiation formula and the second order Gear's extrapolation approach. the second is a combination of the second-order Adams-Moulton and second-order Adams-Bashforth methods. Both algorithms only require the solution of decoupled Stokes and Darcy problems at each time-step. Hence, these schemes are very efficient and can be easily implemented using legacy codes. We establish the unconditional and uniform in time stability for both schemes. …

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. …

Issues Related To Combining Multiple Speciated Pm2.5 Data Sources In Spatio-Temporal Exposure Models For Epidemiology: The Npact Case Study, Sun-Young Kim, Lianne Sheppard, Timothy V. Larson, Joel Kaufman, Sverre Vedal

UW Biostatistics Working Paper Series

Background: Regulatory monitoring data have been the most common exposure data resource in studies of the association between long-term PM_2.5 components and health. However, data collected for regulatory purposes may not be compatible with epidemiological study.

Objectives: We aimed to explore three important features of the PM_2.5 component monitoring data obtained from multiple sources to combine all available data for developing spatio-temporal prediction models in the National Particle Component and Toxicity (NPACT) study.

Methods: The NPACT monitoring data were collected in an extensive monitoring campaign targeting cohort participants. The regulatory monitoring data were obtained from the Chemical Speciation …

Prediction Of Fine Particulate Matter Chemical Components For The Multi-Ethnic Study Of Atherosclerosis Cohort: A Comparison Of Two Modeling Approaches, Sun-Young Kim, Lianne Sheppard, Silas Bergen, Adam A. Szpiro, Paul D. Sampson, Joel Kaufman, Sverre Vedal

UW Biostatistics Working Paper Series

Recent epidemiological cohort studies of the health effects of PM_2.5 have developed exposure estimates from advanced exposure prediction models. Such models represent spatial variability across participant residential locations. However, few cohort studies have developed exposure predictions for PM_2.5 components. We used two exposure modeling approaches to obtain long-term average predicted concentrations for four PM_2.5 components: sulfur, silicon, and elemental and organic carbon (EC and OC). The models were specifically developed for the Multi-Ethnic Study of Atherosclerosis (MESA) cohort as a part of the National Particle Component and Toxicity (NPACT) study. The spatio-temporal model used 2-week average measurements …

Simulating Bipartite Networks To Reflect Uncertainty In Local Network Properties, Ravi Goyal, Joseph Blitzstein, Victor De Gruttola

Harvard University Biostatistics Working Paper Series

No abstract provided.

Flexible Partially Linear Single Index Regression Models For Multivariate Survival Data, Na Lei

Electronic Thesis and Dissertation Repository

Survival regression models usually assume that covariate effects have a linear form. In many circumstances, however, the assumption of linearity may be violated. The present work addresses this limitation by adding nonlinear covariate effects to survival models. Nonlinear covariates are handled using a single index structure, which allows high-dimensional nonlinear effects to be reduced to a scalar term. The nonlinear single index approach is applied to modeling of survival data with multivariate responses, in three popular models: the proportional hazards (PH) model, the proportional odds (PO) model, and the generalized transformation model. Another extension of the PH and PO model …

Asymptotic Theory For Garch-In-Mean Models, Weiwei Liu

Electronic Thesis and Dissertation Repository

The GARCH-in-mean process is an important extension of the standard GARCH (generalized autoregressive conditional heteroscedastic) process and it has wide applications in economics and finance. The parameter estimation of GARCH type models usually involves the quasi-maximum likelihood (QML) technique as it produces consistent and asymptotically Gaussian distributed estimators under certain regularity conditions. For a pure GARCH model, such conditions were already found with asymptotic properties of its QML estimator well understood. However, when it comes to GARCH-in-mean models those properties are still largely unknown. The focus of this work is to establish a set of conditions under which the QML …

Causal Mediation In A Survival Setting With Time-Dependent Mediators, Wenjing Zheng, Mark J. Van Der Laan

Wenjing Zheng

The effect of an expsore on an outcome of interest is often mediated by intermediate variables. The goal of causal mediation analysis is to evaluate the role of these intermediate variables (mediators) in the causal effect of the exposure on the outcome. In this paper, we consider causal mediation of a baseline exposure on a survival (or time-to-event) outcome, when the mediator is time-dependent. The challenge in this setting lies in that the event process takes places jointly with the mediator process; in particular, the length of the mediator history depends on the survival time. As a result, we argue …

Targeted Maximum Likelihood Estimation Of Natural Direct Effect, Wenjing Zheng, Mark Van Der Laan

Wenjing Zheng

In many causal inference problems, one is interested in the direct causal effect of an exposure on an outcome of interest that is not mediated by certain intermediate variables. Robins and Greenland (1992) and Pearl (2000) formalized the definition of two types of direct effects (natural and controlled) under the counterfactual framework. Since then, identifiability conditions for these effects have been studied extensively. By contrast, considerably fewer efforts have been invested in the estimation problem of the natural direct effect. In this article, we propose a semiparametric efficient, multiply robust estimator for the natural direct effect of a binary treatment …

Using Intelligent Prefetching To Reduce The Energy Consumption Of A Large-Scale Storage System, Brian Romoser, Ziliang Zong, Ribel Fares, Joal Wood, Rong Ge

Mathematics, Statistics and Computer Science Faculty Research and Publications

Many high performance large-scale storage systems will experience significant workload increases as their user base and content availability grow over time. The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) center hosts one such system that has recently undergone a period of rapid growth as its user population grew nearly 400% in just about three years. When administrators of these massive storage systems face the challenge of meeting the demands of an ever increasing number of requests, the easiest solution is to integrate more advanced hardware to existing systems. However, additional investment in hardware may significantly increase the …

Adjusted Tornado Probabilities, Holly M. Widen, James B. Elsner, Cameron Amrine, Rizalino B. Cruz, Erik Fraza, Laura Michaels, Loury Migliorelli, Brendan Mulholland, Michael Patterson, Sarah Strazzo, Guang Xing

Publications

Tornado occurrence rates computed from the available reports are biased low relative to the unknown true rates. To correct for this low bias, the authors demonstrate a method to estimate the annual probability of being struck by a tornado that uses the average report density estimated as a function of distance from nearest city/town center. The method is demonstrated on Kansas and then applied to 15 other tornado-prone states from Nebraska to Tennessee. States are ranked according to their adjusted tornado rate and comparisons are made with raw rates published elsewhere. The adjusted rates, expressed as return periods, arestates, including …

Improving Time Structure Patterns Of Orthogonal Markov Chains And Its Consequences In Hydraulic Simulations, Juan C. Jaimes-Correa

School of Natural Resources: Dissertations, Theses, and Student Research

Rainfall¹ occurrences understood as rain events are relevant for agricultural practices because temporal distribution of rainfall highly affects yield production. A few stochastic models satisfactorily generate daily rainfall events while preserving temporal and spatial dependence among multiple sites. I evaluated an extension on the traditional Orthogonal Markov chain (TOMC) model in reproducing the temporal structure of rainfall events at multiple sites in Florida (FL), Nebraska (NE) and California (CA). In addition, a simulation of watershed runoff from rainfall events, reproduced by a single- and multi-site weather generator, was conducted. Results shows that (i) a temporal structure extended …

Experimental And Statistical Techniques To Probe Extraordinary Electronic Properties Of Molecules, Byron Hager Smith

Doctoral Dissertations

The existence of an additional electron or hole in the presence of an electric monopole is a well understood physical system, but this ideality is far from the true physical properties of many molecules. Examples of such irregular electronic states include the attachment of an excess charge to a molecule's dipole moment, electronic correlation spanning a molecule, or attachment of multiple excess charges. Current theoretical and experimental interpretations widely vary for these states and further elucidation of the nature of irregular electronic structure may provide solutions to unexplained observations and the impetus for industrial application. For example, in the case …

Reaching The Gold Standard: Assessing Driving Ability Among Student And Expert Drivers, Alyssa Davis

Statistics

No abstract provided.

Economic Challenges Facing Kentucky’S Electricity Generation Under Greenhouse Gas Constraints, Energy And Environment Cabinet, Commonwealth Of Kentucky, Department Of Statistics, University Of Kentucky, Center For Applied Energy Research, University Of Kentucky, Pacific Northwest National Laboratory

Statistics Reports

From the preface:

For the Energy and Environment Cabinet (EEC), which has primacy in administering most federal environmental laws and regulations at the state level, we have to understand the implications of what is arguably one of the most challenging issues to confront us—greenhouse gas (GHG) emissions and their impact on climate change. Efforts to reduce GHG or carbon dioxide (CO₂) emissions have moved beyond the point of discussion at the national level, and the United States Supreme Court has ruled that the U.S. Environmental Protection Agency (EPA) has the authority to regulate GHG emissions. Furthermore, while public …

The Log-Beta Generalized Half-Normal Regression Model, Rodrigo R. Pescim, Edwin M. M. Ortega, Gauss M. Cordeiro, Clarice G. B. Demtrio, Gholamhossein Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

We introduce a log-linear regression model based on the beta generalized half-normal distribution (Pescim et al., 2010). We formulate and develop a log-linear model using a new distribution so-called the log-beta generalized half normal distribution. We derive expansions for the cumulative distribution and density functions which do not depend on complicated functions. We obtain formal expressions for the moments and moment generating function. We characterize the proposed distribution using a simple relationship between two truncated moments. An advantage of the new distribution is that it includes as special sub-models classical distributions reported in the lifetime literature. We also show that …

Targeting Inflammation Using Salsalate In Patients With Type 2 Diabetes: Effects On Flow-Mediated Dilation (Tinsal-Fmd)., Allison B Goldfine, J Stewart Buck, Cyrus Desouza, Vivian Fonseca, Yii-Der Ida Chen, Steven E Shoelson, Kathleen A. Jablonski, Mark A Creager, The Tinsal-Fmd Team

GW Biostatistics Center

OBJECTIVE: To test whether inhibiting inflammation with salsalate improves endothelial function in patients with type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS: We conducted an ancillary study to the National Institutes of Health-sponsored, multicenter, randomized, double-masked, placebo-controlled trial evaluating the safety and efficacy of salsalate in targeting inflammation to improve glycemia in patients with T2D. Flow-mediated, endothelium-dependent dilation (FMD) and endothelium-independent, nitroglycerin-mediated dilation (NMD) of the brachial artery were assessed at baseline and 3 and 6 months following randomization to either salsalate 3.5 g/day or placebo. The primary end point was change in FMD at 6 months.

RESULTS: A total …

Multiple Hypotheses Testing Procedures In Clinical Trials And Genomic Studies, Qing Pan

Epidemiology Faculty Publications

We review and compare multiple hypothesis testing procedures used in clinical trials and those in genomic studies. Clinical trials often employ global tests, which draw an overall conclusion for all the hypotheses, such as SUM test, Two-Step test, Approximate Likelihood Ratio test (ALRT), Intersection-Union Test (IUT), and MAX test. The SUM and Two-Step tests are most powerful under homogeneous treatment effects, while the ALRT and MAX test are robust in cases with non-homogeneous treatment effects. Furthermore, the ALRT is robust to unequal sample sizes in testing different hypotheses. In genomic studies, stepwise procedures are used to draw marker-specific conclusions and …

Factors Associated With Parental Decision Making And Childhood Vaccination, Zuwen Qiu-Shultz

UNLV Theses, Dissertations, Professional Papers, and Capstones

In order to better understand factors affecting immunization status, logistic regression was used to assess the association of various socio-demographic factors and whether parents would have their child immunized if not a state mandate. Factors included in the study were race, household income, number of children in the household, number of adults in the household, if the child had a primary provider, if the child had a health check-up in the last twelve months, and medical insurance status of the child. The combined Nevada Kindergarten Health Survey Result of 2009-2010 (Year Two) and 2010-2011 (Year Three) conducted by the Nevada …

A Hybrid Agent-Based And Differential Equations Model For Simulating Antibiotic Resistance In A Hospital Ward, Lester Caudill, Barry Lawson

Department of Math & Statistics Faculty Publications

Serious infections due to antibiotic-resistant bacteria are pervasive, and of particular concern within hospital units due to frequent interaction among health-care workers and patients. Such nosocomial infections are difficult to eliminate because of inconsistent disinfection procedures and frequent interactions among infected persons, and because ill-chosen antibiotic treatment strategies can lead to a growth of resistant bacterial strains. Clinical studies to address these concerns have several issues, but chief among them are the effects on the patients involved. Realistic simulation models offer an attractive alternative. This paper presents a hybrid simulation model of antibiotic resistant infections in a hospital ward, combining …

Optimal Matching Distances Between Categorical Sequences: Distortion And Inferences By Permutation, Juan P. Zuluaga

Culminating Projects in Applied Statistics

Sequence data (an ordered set of categorical states) is a very common type of data in Social Sciences, Genetics and Computational Linguistics.

For exploration and inference of sets of sequences, having a measure of dissimilarities among sequences would allow the data to be analyzed by techniques like clustering, multimensional scaling analysis and distance-based regression analysis. Sequences can be placed in a map where similar sequences are close together, and dissimilar ones will be far apart. Such patterns of dispersion and concentration could be related to other covariates. For example, do the employment trajectories of men and women tend to form …

A Geographical Approach For Integrating Belief Networks And Geographic Information Sciences To Probabilistically Predict River Depth, Nathan Lee Hopper

Dissertations

Geography is, traditionally, a discipline dedicated to answering complex spatial questions. Although spatial statistical techniques, such as weighted regressions and weighted overlay analyses, are commonplace within geographical sciences, probabilistic reasoning, and uncertainty analyses are not typical. For example, belief networks are statistically robust and computationally powerful, but are not strongly integrated into geographic information systems. This is one of the reasons that belief networks have not been more widely utilized within the environmental sciences community. Geography’s traditional method of delivering information through maps provides a mechanism for conveying probabilities and uncertainties to decision makers in a clear, concise manner. This …

A Guide To Testing A Proportion When There May Be Misclassifications, David L. Farnsworth, Jonathan R. Bradley

Articles

Ignoring possible misclassifications when testing for a proportion can lead to erroneous decisions. A statistical test is described that incorporates misclassification rates into the analysis. Easily checked safeguards that ensure that the test is appropriate are given. Additionally, the test provides a procedure when the hypothesis stipulates that the proportion is zero. Applications of the test are illustrated with examples which show that it is practical. Comprehensive guidance is supplied for the practitioner.

Analysis Of Mixed Correlated Bivariate Negative Binomial And Continuous Responses, F. Razie, E. B. Samani, M. Ganjali

Applications and Applied Mathematics: An International Journal (AAM)

A general model for the mixed correlated negative binomial and continuous responses is proposed. It is shown how to construct parameter of the models, using the maximization of the full likelihood. Influence of a small perturbation of correlation parameter of the model on the likelihood displacement is also studied. The model is applied to a medical data, obtained from an observational study on women, where the correlated responses are the negative binomial response of joint damage and continuous responses of body mass index. Simultaneous effects of some covariates on both responses are investigated.

Application Of Fractional Moments For Comparing Random Variables With Varying Probability Distributions, Munther R. Al Shami, A. R. Mugdadi, R. R. Nigmatullin, S. I. Osokin

Applications and Applied Mathematics: An International Journal (AAM)

New methods are being presented for statistical treatment of different random variables with unknown probability distributions. These include analysis based on the probability circles, probability ellipses, generalized mean values, generalized Pearson correlation coefficient and the beta-function analysis. Unlike other conventional statistical procedures, the main distinctive feature of these new methods is that no assumptions are made about the nature of the probability distribution of the random series being evaluated. Furthermore, the suggested procedures do not introduce uncontrollable errors during their application. The effectiveness of these methods is demonstrated on simulated data with extended and reduced sample sizes having different probability …

The Mx/G/1 Queue With Unreliable Server, Delayed Repairs, And Bernoulli Vacation Schedule Under T-Policy, L. Tadj, G. Choudhury

Applications and Applied Mathematics: An International Journal (AAM)

In this paper we study a batch arrival queuing system. The server may break down while delivering service. However, repair is not provided immediately, rather it is delayed for a random amount of time. At the end of service, the server may process the next customer if any are available, or may take a vacation to execute some other job. Finally, the server implements the T-policy. We describe for this system an optimal management policy. Numerical examples are provided.

Local Influence In Bayesian Elliptically Contoured-Ordinal Model For Mixed Data, Ehsan B. Samani

Applications and Applied Mathematics: An International Journal (AAM)

This paper develops a new class of joint modeling of mixed correlated ordinal and continuous responses with elliptically contoured errors. This joint model includes the latent variable approach of using an elliptically contoured distribution for mixed ordinal and continuous responses. A Markov Chain Monte Carlo sampling algorithm is described for estimating the posterior distribution of the parameters. For sensitivity analysis to investigate the perturbation from associate responses, it is demonstrated how one can use some elements of covariance structure. Influence of small perturbation of these elements on the posterior normal curvature is also studied. To illustrate the application of such …

Using Fuzzy Linear Regression To Estimate Relationship Between Forest Fires And Meteorological Conditions, Hande G. Akdemir, Fatma Tiryaki

Applications and Applied Mathematics: An International Journal (AAM)

Each year, millions of hectares of forest land are destroyed by fires causing great financial loss and ecological damage. In this paper, our aim is to study the effect of the variation of meteorological conditions on the total burned area in hectares, by using fuzzy linear regression analysis based on Tanaka’s approaches. The total burned area is considered a dependent variable. Air temperature (in ºC), relative humidity (in %), wind speed (in km/h) and rainfall (in mm/m² ) are considered to be independent variables. The relationship between input and output data is estimated using data provided in data mining …

Certain Fractional Integral Operators And The Generalized Incomplete Hypergeometric Functions, H. M. Srivastava, Praveen Agarwal

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we apply a certain general pair of operators of fractional integration involving Appell’s function F₃ in their kernel to the generalized incomplete hypergeometric functions _pΓ_q[z] and _pɣ_q [z], which were introduced and studied systematically by Srivastava et al. in the year 2012. Some interesting special cases and consequences of our main results are also considered.