Statistics and Probability Commons^™

Clme: An R Package For Linear Mixed Effects Models Under Inequality Constraints, Casey M. Jelsema, Shyamal D. Peddada

Faculty & Staff Scholarship

In many applications researchers are typically interested in testing for inequality constraints in the context of linear fixed effects and mixed effects models. Although there exists a large body of literature for performing statistical inference under inequality constraints, user friendly statistical software implementing such methods is lacking, especially in the context of linear fixed and mixed effects models. In this article we introduce CLME, a package in the R language that can be used for testing a broad collection of inequality constraints. It uses residual bootstrap based methodology which is reasonably robust to non-normality as well as heteroscedasticity. The package …

Enscat: Clustering Of Categorical Data Via Ensembling, Bertrand S. Clarke, Saeid Amiri, Jennifer L. Clarke

Department of Statistics: Faculty Publications

Background: Clustering is a widely used collection of unsupervised learning techniques for identifying natural classes within a data set. It is often used in bioinformatics to infer population substructure. Genomic data are often categorical and high dimensional, e.g., long sequences of nucleotides. This makes inference challenging: The distance metric is often not well-defined on categorical data; running time for computations using high dimensional data can be considerable; and the Curse of Dimensionality often impedes the interpretation of the results. Up to the present, however, the literature and software addressing clustering for categorical data has not yet led to a standard …

Genomic Bayesian Prediction Model For Count Data With Genotype X Environment Interaction, Abelardo Montesinos-López, Osval A. Montesinos-López, José Crossa, Juan Burgueño, Kent M. Eskridge, Esteban Falconi-Castillo, Xinyao He, Pawan Singh, Karen Cichy

Department of Statistics: Faculty Publications

Genomic tools allow the study of the whole genome, and facilitate the study of genotype-environment combinations and their relationship with phenotype. However, most genomic prediction models developed so far are appropriate for Gaussian phenotypes. For this reason, appropriate genomic prediction models are needed for count data, since the conventional regression models used on count data with a large sample size (n_T ) and a small number of parameters (p) cannot be used for genomic-enabled prediction where the number of parameters (p) is larger than the sample size (n_T ). Here, we propose a Bayesian mixed-negative binomial (BMNB) genomic …

A Genomic Bayesian Multi-Trait And Multi-Environment Model, Osval A. Montesinos-López, Abelardo Montesinos-López, José Crossa, Fernando Toledo, Oscar Pérez-Hernández, Kent M. Eskridge, Jessica Rutkoski

Department of Statistics: Faculty Publications

When information on multiple genotypes evaluated in multiple environments is recorded, a multi-environment single trait model for assessing genotype × environment interaction (G×E) is usually employed. Comprehensive models that simultaneously take into account the correlated traits and trait × genotype × environment interaction (T×G×E) are lacking. In this research, we propose a Bayesian model for analyzing multiple traits and multiple environments for whole-genome prediction (WGP) model. For this model, we used Half-𝑡 priors on each standard deviation term and uniform priors on each correlation of the covariance matrix. These priors were not informative and led to posterior inferences that were …

Student Fact Book, Fall 2016 - Fortieth Annual Edition, Office Of Student Information Systems, Wright State University

Wright State University Student Fact Books

The student fact book has general demographic information on all students enrolled at Wright State University for Fall Semester, 2016.

A Comparison Of Machine Learning Techniques And Logistic Regression Method For The Prediction Of Past-Due Amount, Jie Hao, Jennifer L. Priestley

Published and Grey Literature from PhD Candidates

The aim of this paper to predict a past-due amount using traditional and machine learning techniques: Logistic Analysis, k-Nearest Neighbor and Random Forest. The dataset to be analyzed is provided by Equifax, which contains 305 categories of financial information from more than 11,787,287 unique businesses from 2006 to 2014. The big challenge is how to handle with the big and noisy real world datasets. Among the three techniques, the results show that Logistic Regression Method is the best in terms of predictive accuracy and type I errors.

An Analysis Of Accuracy Using Logistic Regression And Time Series, Edwin Baidoo, Jennifer L. Priestley

Published and Grey Literature from PhD Candidates

This paper analyzes the accuracy rates for logistic regression and time series models. It also examines a relatively new performance index that takes into consideration the business assumptions of credit markets. Although prior research has focused on evaluation metrics, such as AUC and Gini index, this new measure has a more intuitive interpretation for various managers and decision makers and can be applied to both Logistic and Time Series models.

A Comparison Of Latent Class Analysis And The Mixture Rasch Model: A Cross-Cultural Comparison Of 8th Grade Mathematics Achievement In The Fourth International Mathematics And Science Study (Timss-2011), Turker Toker

Electronic Theses and Dissertations

This study provides a comparison of the results of latent class analysis (LCA) and mixture Rasch model (MRM) analysis using data from the Trends in International Mathematics and Science Study - 2011 (TIMSS-2011) with a focus on the 8th-grade mathematics section. The research study focuses on the comparison of LCA with Mplus version 7.31 and MRM with WinMira 2011 to determine if results obtained differ when the assumed psychometric model differs. Also, a log-linear analysis was conducted to understand the interactions between latent classes identified by LCA and MRM. The data set used in the study was from four diverse …

Socioecological Factors Influencing Women's Hiv Risk In The United States: Qualitative Findings From The Women's Hiv Seroincidence Study (Hptn 064)., Paula M Frew, Kimberly Parker, Linda Vo, Danielle Haley, Ann O'Leary, Dazon Dixon Diallo, Carol E Golin, Irene Kuo, Lydia Soto-Torres, Jing Wang, Adaora A Adimora, Laura A Randall, Carlos Del Rio, Sally Hodder, Hiv Prevention Trials Network 064 (Htpn) Study Team.

Epidemiology Faculty Publications

BACKGROUND: We sought to understand the multilevel syndemic factors that are concurrently contributing to the HIV epidemic among women living in the US. We specifically examined community, network, dyadic, and individual factors to explain HIV vulnerability within a socioecological framework.

METHODS: We gathered qualitative data (120 interviews and 31 focus groups) from a subset of women ages 18-44 years (N = 2,099) enrolled in the HPTN 064 HIV seroincidence estimation study across 10 US communities. We analyzed data from 4 diverse locations: Atlanta, New York City (the Bronx), Raleigh, and Washington, DC. Data were thematically coded using grounded theory methodology. …

What's In A Name? A Critical Review Of Definitions Of Quantitative Literacy, Numeracy, And Quantitative Reasoning, Gizem Karaali, Edwin H Villafane Hernandez '18, Jeremy Alexander Taylor '18

Pomona Faculty Publications and Research

This article aims to bring together various threads in the eclectic literature that make up the scholarship around the theme of Quantitative Literacy. In investigating the meanings of terms like "quantitative literacy," "quantitative reasoning," and "numeracy," we seek common ground, common themes, common goals and aspirations of a community of practitioners. A decade ago, these terms were relatively new in the public sphere; today policy makers and accrediting agencies are routinely inserting them into general education conversations. Having good, representative, and perhaps even compact and easily digestible definitions of these terms might come in handy in public relations contexts as …

Species Discovery And Diversity In Lobocriconema (Criconematidae: Nematoda) And Related Plant-Parasitic Nematodes From North American Ecoregions, Tom Powers, Ernest C. Bernard, T. Harris, Robert Higgins, M. Olson, S. Olson, M. Lodema, Julianne N. Matczyszyn, P. Mullin, L. Sutton, K.S Powers

Department of Statistics: Faculty Publications

There are many nematode species that, following formal description, are seldom mentioned again in the scientific literature. Lobocriconema thornei and L. incrassatum are two such species, described from North American forests, respectively 37 and 49 years ago. In the course of a 3-year nematode biodiversity survey of North American ecoregions, specimens resembling Lobocriconema species appeared in soil samples from both grassland and forested sites. Using a combination of molecular and morphological analyses, together with a set of species delimitation approaches, we have expanded the known range of these species, added to the species descriptions, and discovered a related group of …

Improving Hiv Surveillance Data For Public Health Action In Washington, Dc: A Novel Multiorganizational Data-Sharing Method, Joanne Ocampo, J. C. Smart, Adam Allston, Reshma Bhattacharjee, Sahithi Boggavarapu, Amanda D. Castel, +13 More

GW Biostatistics Center

Background: The National HIV/AIDS Strategy calls for active surveillance programs for human immunodeficiency virus (HIV) to more accurately measure access to and retention in care across the HIV care continuum for persons living with HIV within their jurisdictions and to identify persons who may need public health services. However, traditional public health surveillance methods face substantial technological and privacy-related barriers to data sharing.

Objective: This study developed a novel data-sharing approach to improve the timeliness and quality of HIV surveillance data in three jurisdictions where persons may often travel across the borders of the District of Columbia, Maryland, and Virginia. …

Skin Collagen Fluorophore Lw-1 Versus Skin Fluorescence As Markers For The Long-Term Progression Of Subclinical Macrovascular Disease In Type 1 Diabetes., David R Sell, Wanjie Sun, Xiaoyu Gao, Christopher Strauch, John M. Lachin, Patricia A Cleary, Saul Genuth, Ddit/Edic Research Group, Vincent M Monnier

GW Biostatistics Center

BACKGROUND: Skin collagen Long Wavelength Fluorescence (LWF) is widely used as a surrogate marker for accumulation of advanced glycation end-products. Here we determined the relationship of LWF with glycemia, skin fluorescence, and the progression of complications during EDIC in 216 participants from the DCCT.

METHODS: LW-1 and collagen-linked fluorescence (CLF) were measured by either High Performance Liquid Chromatography (HPLC) with fluorescence detection (LW-1) or total fluorescence of collagenase digests (CLF) in insoluble skin collagen extracted from skin biopsies obtained at the end of the DCCT (1993). Skin intrinsic fluorescence (SIF) was noninvasively measured on volar forearm skin at EDIC year …

D-Dimer Levels Before Hiv Seroconversion Remain Elevated Even After Viral Suppression And Are Associated With An Increased Risk Of Non-Aids Events, Matthew S Freiberg, Ionut Bebu, Russell Tracy, Kaku So-Armah, Jason Okulicz, Anuradha Ganesan, Adam Armstrong, Thomas O'Bryan, David Rimland, Amy C Justice, Brian K Agan

GW Biostatistics Center

The mechanism underlying the excess risk of non-AIDS diseases among HIV infected people is unclear. HIV associated inflammation/hypercoagulability likely plays a role. While antiretroviral therapy (ART) may return this process to pre-HIV levels, this has not been directly demonstrated. We analyzed data/specimens on 249 HIV+ participants from the US Military HIV Natural History Study, a prospective, multicenter observational cohort of >5600 active duty military personnel and beneficiaries living with HIV. We used stored blood specimens to measure D-dimer and Interleukin-6 (IL-6) at three time points: pre-HIV seroconversion, ≥6 months post-HIV seroconversion but prior to ART initiation, and ≥6 months post-ART …

Generalized Confidence Intervals And Fiducial Intervals For Some Epidemiological Measures., Ionut Bebu, G. Luta, T. Mathew, B. K. Agan

GW Biostatistics Center

For binary outcome data from epidemiological studies, this article investigates the interval estimation of several measures of interest in the absence or presence of categorical covariates. When covariates are present, the logistic regression model as well as the log-binomial model are investigated. The measures considered include the common odds ratio (OR) from several studies, the number needed to treat (NNT), and the prevalence ratio. For each parameter, confidence intervals are constructed using the concepts of generalized pivotal quantities and fiducial quantities. Numerical results show that the confidence intervals so obtained exhibit satisfactory performance in terms of maintaining the coverage probabilities …

Significance Of Epicardial And Intrathoracic Adipose Tissue Volume Among Type 1 Diabetes Patients In The Dcct/Edic: A Pilot Study., Sirous Darabian, Jye-Yu C Backlund, Patricia A Cleary, Nasim Sheidaee, Ionut Bebu, John M. Lachin, Matthew J Budoff, Dcct/Edic Research Group

GW Biostatistics Center

Introduction

Type 1 diabetes (T1DM) patients are at increased risk of coronary artery disease (CAD). This pilot study sought to evaluate the relationship between epicardial adipose tissue (EAT) and intra-thoracic adipose tissue (IAT) volumes and cardio-metabolic risk factors in T1DM.

Method

EAT/IAT volumes in 100 patients, underwent non-contrast cardiac computed tomography in the Diabetes Control and Complications Trial /Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study were measured by a certified reader. Fat was defined as pixels’ density of -30 to -190 Hounsfield Unit. The associations were assessed using–Pearson partial correlation and linear regression models adjusted for gender and age …

Lymphoblastoid Cell Lines As A Tool To Study Inter-Individual Differences In The Response To Glucose., Michael A Grassi, Vidhya R Rao, Siquan Chen, Dingcai Cao, Xiaoyu Gao, Patricia A. Cleary, R Stephanie Huang, Andrew D Paterson, Rama Natarajan, Jalees Rehman, Timothy S Kern

GW Biostatistics Center

BACKGROUND: White blood cells have been shown in animal studies to play a central role in the pathogenesis of diabetic retinopathy. Lymphoblastoid cells are immortalized EBV-transformed primary B-cell leukocytes that have been extensively used as a model for conditions in which white blood cells play a primary role. The purpose of this study was to investigate whether lymphoblastoid cell lines, by retaining many of the key features of primary leukocytes, can be induced with glucose to demonstrate relevant biological responses to those found in diabetic retinopathy.

METHODS: Lymphoblastoid cell lines were obtained from twenty-three human subjects. Differences between high and …

Importance Of Hereditary And Selected Environmental Risk Factors In The Etiology Of Inflammatory Breast Cancer: A Case-Comparison Study., Roxana Moslehi, Elizabeth Freedman, Nur Zeinomar, Carmela Veneroso, Paul H. Levine

Epidemiology Faculty Publications

BACKGROUND: To assess the importance of heredity in the etiology of inflammatory breast cancer (IBC), we compared IBC patients to several carefully chosen comparison groups with respect to the prevalence of first-degree family history of breast cancer.

METHODS: IBC cases (n = 141) were compared to non-inflammatory breast cancer cases (n = 178) ascertained through George Washington University (GWU) with respect to the prevalence of first-degree family history of breast cancer and selected environmental/lifestyle risk factors for breast cancer. Similar comparisons were conducted with subjects from three case-control studies: breast cancer cases (n = 1145) and unaffected controls (n = …

Importance Of Hereditary And Selected Environmental Risk Factors In The Etiology Of Inflammatory Breast Cancer: A Case-Comparison Study., Roxana Moslehi, Elizabeth Freedman, Nur Zeinomar, Carmela Veneroso, Paul H. Levine

Epidemiology Faculty Publications

BACKGROUND: To assess the importance of heredity in the etiology of inflammatory breast cancer (IBC), we compared IBC patients to several carefully chosen comparison groups with respect to the prevalence of first-degree family history of breast cancer.

METHODS: IBC cases (n = 141) were compared to non-inflammatory breast cancer cases (n = 178) ascertained through George Washington University (GWU) with respect to the prevalence of first-degree family history of breast cancer and selected environmental/lifestyle risk factors for breast cancer. Similar comparisons were conducted with subjects from three case-control studies: breast cancer cases (n = 1145) and unaffected controls (n = …

Interruptions Of Antiretroviral Therapy In Children And Adolescents With Hiv Infection In Clinical Practice: A Retrospective Cohort Study In The Usa., Natella Rakhmanina, Kam S Lam, Jaclyn Hern, Heather A. Young, Alex Walters, Amanda D. Castel

Epidemiology Faculty Publications

INTRODUCTION: Changes in combination antiretroviral therapy (cART) throughout childhood challenge the continuity of paediatric HIV treatment. This study aimed to evaluate the prevalence of treatment interruption (TI), including lamivudine (3TC) monotherapy, and the relationship of TI to virologic and immunologic parameters in HIV-infected paediatric patients.

METHODS: Nested within a prospective observational study of a city-wide cohort of HIV-infected persons in the District of Columbia, this sub-study collected retrospective data on antiretroviral therapy, enrolment (endpoint) and historic (lifelong) CD4 counts and HIV RNA viral load (VL) of the paediatric cohort. TI was defined as interruption of cART ≥4 consecutive weeks. Data …

Arsenic In Drinking Water And Lung Cancer Mortality In The United States: An Analysis Based On Us Counties And 30 Years Of Observation (1950-1979)., Hamid Ferdosi, Elisabeth K Dissen, Nana Ama Afari-Dwamena, Ji Li, Rusan Chen, Manning Feinleib, Steven H Lamm

Epidemiology Faculty Publications

Background. To examine whether the US EPA (2010) lung cancer risk estimate derived from the high arsenic exposures (10-934 µg/L) in southwest Taiwan accurately predicts the US experience from low arsenic exposures (3-59 µg/L). Methods. Analyses have been limited to US counties solely dependent on underground sources for their drinking water supply with median arsenic levels of ≥3 µg/L. Results. Cancer risks (slopes) were found to be indistinguishable from zero for males and females. The addition of arsenic level did not significantly increase the explanatory power of the models. Stratified, or categorical, analysis yielded relative risks that hover about 1.00. …

Estimating Effects Of Non-Normality In Assessing Structural Equation Model Fit For Use Of Physical Science Data, Sarah Rose

Wayne State University Dissertations

ABSTRACT

ESTIMATING EFFECTS OF NON-NORMALITY IN ASSESSING

STRUCTURAL EQUATION MODEL FIT FOR USE OF PHYSICAL SCIENCE DATA

by

SARAH ALTA ROSE

May 2016

Advisor: Dr. Barry Markman

Major: Education (Evaluation and Research)

Degree: Doctor of Philosophy

The purpose of this study was to evaluate the sensitivity of selected fit index statistics in determining model fit when the distribution varied from normality, as is typically true of data research for the physical sciences. SEM is a popular statistical method and is used in many physical and social behavioral science research projects; however, the sensitivity of the model fit indices when normality …

A Hierarchical Statistical Engineering Modeling Methodology, Teddy Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

In the ASEM-IAC 2015, Cotter (2015) proposed a systemic joint deterministic-stochastic dynamic causal Bayesian statistical engineering model that addressed the knowledge gap needed to integrate deterministic mathematical engineering models within a stochastic framework. However, Cotter did not specify the modeling methodology through which statistical engineering models could be developed, diagnosed, and applied to predict systemic mission performance. This paper updates research into the development a hierarchical statistical engineering modeling methodology and sets forth the initial theoretical foundation for the methodology.

Is The Time Allocated To Review Patent Applications Inducing Examiners To Grant Invalid Patents?: Evidence From Micro-Level Application Data, Michael D. Frakes, Melissa F. Wasserman

Faculty Scholarship

We explore how examiner behavior is altered by the time allocated for reviewing patent applications. Insufficient examination time may hamper examiner search and rejection efforts, leaving examiners more inclined to grant invalid applications. To test this prediction, we use application-level data to trace the behavior of individual examiners over the course of a series of promotions that carry with them reductions in examination-time allocations. We find evidence demonstrating that such promotions are associated with reductions in examination scrutiny and increases in granting tendencies, as well as evidence that those additional patents being issued on the margin are of below-average quality.

Modeling Daily Electricity Load Curve Using Cubic Splines And Functional Principal Components, Abdelmonaem Salem Jornaz

Doctoral Dissertations

"Forecasting electricity load is very important to the electric utilities as well as producers of power because accurate predictions can cut down costs by avoiding power shortages or surpluses. Of specific interest is the 24-hour daily electricity load profile, which provides insight into periods of high demand and periods where the use of electricity is at a minimum. Researchers have proposed many approaches to modeling electricity prices, real-time load, and day-ahead demand, with varying success. In this dissertation three new approaches to modeling and forecasting the 24-hour daily electricity load profiles are presented. The application of the proposed methods is …

Identifying Data Centers From Satellite Imagery, Adam Buskirk

Electronic Theses and Dissertations

We develop two different descriptors which can be utilized to describe satellite imagery. The first, the differential-magnitude and radius descriptor, describes a scene by computing the directional gradient of the scene with respect to a vector field whose solutions are circles around a pixel to be described, and then counts pixels in a descriptor matrix according to the magnitude of this gradient and the distance at which this magnitude occurs. The second, the radial Fourier descriptor, extracts from the scene a sequence of annuloid sectors, and uses this to approximate the behavior of the image on a circle around the …

A Comparison Of The Utility Of Craniometric And Dental Morphological Data For Assessing Biodistance And Sex-Differential Migration In The Pacific Islands, Brittney A. Eubank

Graduate Student Theses, Dissertations, & Professional Papers

Genetic analysis of maternally-inherited mitochondrial DNA and the paternally-inherited Y-chromosome yield contrasting pictures of movement of peoples into the Pacific Islands. A possible explanation for this discrepancy is a matrilocal residency pattern practiced by early Pacific settlers, in which Melanesian men were brought into settler communities to intermarry with local women, yielding a higher intrapopulation variance and lower interpopulation variance exhibited in males compared to females. This research investigates the possibility of sex-differential migration in the Oceanic populations of Easter Island, Fiji, Guam, Mokapu, and New Britain through analysis of biodistance based on dental morphological trait frequencies and craniometric measures …

Simulation Of Nuclear Fusion Using A One Dimensional Particle In Cell Method, Steven T. Margell

Cal Poly Humboldt theses and projects

In this thesis several novel techniques are developed to simulate fusion events in an isotropic, electrostatic three-dimensional Deuterium-Tritium plasma. These techniques allow us to accurately predict three-dimensional collision events with a one-dimensional model while simultaneously reducing compute time via a nearest neighbor algorithm. Furthermore, a fusion model based on first principles is developed that yields an average fusion reactivity which correlates well with empirical results.

Design & Analysis Of A Computer Experiment For An Aerospace Conformance Simulation Study, Ryan W. Gryder

Theses and Dissertations

Within NASA's Air Traffic Management Technology Demonstration # 1 (ATD-1), Interval Management (IM) is a flight deck tool that enables pilots to achieve or maintain a precise in-trail spacing behind a target aircraft. Previous research has shown that violations of aircraft spacing requirements can occur between an IM aircraft and its surrounding non-IM aircraft when it is following a target on a separate route. This research focused on the experimental design and analysis of a deterministic computer simulation which models our airspace configuration of interest. Using an original space-filling design and Gaussian process modeling, we found that aircraft delay assignments …

Extending The Latent Multinomial Model With Complex Error Processes And Dynamic Markov Bases, Simon J. Bonner, Matthew R. Schofield, Patrik Noren, Steven J. Price

Forestry and Natural Resources Faculty Publications

The latent multinomial model (LMM) of Link et al. [Biometrics 66 (2010) 178–185] provides a framework for modelling mark-recapture data with potential identification errors. Key is a Markov chain Monte Carlo (MCMC) scheme for sampling configurations of the latent counts of the true capture histories that could have generated the observed data. Assuming a linear map between the observed and latent counts, the MCMC algorithm uses vectors from a basis of the kernel to move between configurations of the latent data. Schofield and Bonner [Biometrics 71 (2015) 1070–1080] shows that this is sufficient for some models within the …