Statistics and Probability Commons^™

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.

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 …

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 …

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 …

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 …

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 …

Short-Term Inflation Forecasting Models For Nigeria, Sani I. Doguwa, Sarah O. Alade

CBN Journal of Applied Statistics (JAS)

Short-term inflation forecasting is an essential component of the monetary policy projections at the Central Bank of Nigeria. This paper proposes four short-term headline inflation forecasting models using the SARIMA and SARIMAX processes and compares their performance using the pseudo-out-of-sample forecasting procedure over July 2011 to September 2013. According to the results the best forecasting performance is demonstrated by the model based on the all items CPI estimated using the SARIMAX model. This model is, therefore, recommended for use in short-term forecasting of headline inflation in Nigeria. The forecasting performance up to eight months ahead, of the models based on …

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.

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 …

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 …

Road Systems And Betweenness, Paul Bankston

Mathematics, Statistics and Computer Science Faculty Research and Publications

A road system is a collection of subsets of a set—the roads—such that every singleton subset is a road in the system and every doubleton subset is contained in a road. The induced ternary (betweenness) relation is defined by saying that a point c lies between points a and b if c is an element of every road that contains both a and b . Traditionally, betweenness relations have arisen from a plethora of other structures on a given set, reflecting intuitions that range from the order-theoretic to the geometric and topological. In this paper we initiate a study …

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.

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 …

Estimation And Inference For Spatial And Spatio-Temporal Mixed Effects Models, Casey M. Jelsema

Dissertations

One of the most common goals of geostatistical analysis is that of spatial prediction, in other words: filling in the blank areas of the map. There are two popular methods for accomplishing spatial prediction. Either kriging, or Bayesian hierarchical models. Both methods require the inverse of the spatial covariance matrix of the data. As the sample size, n, becomes large, both of these methods become impractical. Reduced rank spatial models (RRSM) allow prediction on massive datasets without compromising the complexity of the spatial process. This dissertation focuses on RRSMs, particularly situations where the data follow non-Gaussian distributions.

The manner in …

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 …

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 …