Statistical Models Commons^™

A Statistical Framework For The Analysis Of Chip-Seq Data, Pei Fen Kuan, Dongjun Chung, Guangjin Pan, James A. Thomson, Ron Stewart, Sunduz Keles

Sunduz Keles

Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) has revolutionalized experiments for genome-wide profiling of DNA-binding proteins, histone modifications, and nucleosome occupancy. As the cost of sequencing is decreasing, many researchers are switching from microarray-based technologies (ChIP-chip) to ChIP-Seq for genome-wide study of transcriptional regulation. Despite its increasing and well-deserved popularity, there is little work that investigates and accounts for sources of biases in the ChIP-Seq technology. These biases typically arise from both the standard pre-processing protocol and the underlying DNA sequence of the generated data.

We study data from a naked DNA sequencing experiment, which sequences non-cross-linked DNA after deproteinizing and …

Mri: Acquisition Of Interactive Visualization Tools For Supercomputer Models, Bruce E. Segee, Huijie Xue, Kiran Bhaganagar, James Fastook, Peter O. Koons

University of Maine Office of Research Administration: Grant Reports

This project, acquiring a visualization facility (vizwall with high resolution display and high volume storage system to visualize large size data generated from diverse research activities), models polar ice sheets, oceans, atmospheric turbulent boundary layers, and geodynamics. The facility, whose main components consist of a visualization wall, a PRISM visualization server, and RAID storage disks, will be integrated to the university's existing supercomputer cluster.

Sequence Comparison And Stochastic Model Based On Multi-Order Markov Models, Xiang Fang

Department of Statistics: Dissertations, Theses, and Student Work

This dissertation presents two statistical methodologies developed on multi-order Markov models. First, we introduce an alignment-free sequence comparison method, which represents a sequence using a multi-order transition matrix (MTM). The MTM contains information of multi-order dependencies and provides a comprehensive representation of the heterogeneous composition within a sequence. Based on the MTM, a distance measure is developed for pair-wise comparison of sequences. The new method is compared with the traditional maximum likelihood (ML) method, the complete composition vector (CCV) method and the improved version of the complete composition vector (ICCV) method using simulated sequences. We further illustrate the application of …

Causal Inference In Epidemiological Studies With Strong Confounding, Kelly L. Moore, Romain S. Neugebauer, Mark J. Van Der Laan, Ira B. Tager

U.C. Berkeley Division of Biostatistics Working Paper Series

One of the identifiabilty assumptions of causal effects defined by marginal structural model (MSM) parameters is the experimental treatment assignment (ETA) assumption. Practical violations of this assumption frequently occur in data analysis, when certain exposures are rarely observed within some strata of the population. The inverse probability of treatment weighted (IPTW) estimator is particularly sensitive to violations of this assumption, however, we demonstrate that this is a problem for all estimators of causal effects. This is due to the fact that the ETA assumption is about information (or lack thereof) in the data. A new class of causal models, causal …

The Em Algorithm For Group Testing Regression Models Under Matrix Pooling, Christopher R. Bilder, Boan Zhang

Department of Statistics: Faculty Publications

No abstract provided.

Modeling Future Record Performances In Athletics, Joseph Hilbe

Joseph M Hilbe

No abstract provided.

Lrm Revision To Ch 2.1, Joseph Hilbe

Joseph M Hilbe

Rewording of part Ch 2.1 of Logistic Regression Models

Using Cone Beam Computed Tomography To Identify A Prediction Model For Obstructive Sleep Apnea, Jodi Parker

Loma Linda University Electronic Theses, Dissertations & Projects

Introduction: Obstructive Sleep Apnea (OSA) patients have increased risk of morbidity and mortality. Early diagnosis may reduce morbidity and mortality. Prediction of OSA from imaging may help to identify OSA patients earlier in life. CBCT can be used for OSA diagnostic imaging due to its three-dimensional (3D) visualization of the upper airway and craniofacial complex. Magnification associated with conventional 2D radiography is eliminated with CBCT, and radiation to the patient is significantly less than previous modalities used to measure craniofacial & airway measurements associated with OSA. During a CBCT scan, the patient's image is taken supine, rather than the upright …

Shrinkage Estimation Of Expression Fold Change As An Alternative To Testing Hypotheses Of Equivalent Expression, Zahra Montazeri, Corey M. Yanofsky, David R. Bickel

COBRA Preprint Series

Research on analyzing microarray data has focused on the problem of identifying differentially expressed genes to the neglect of the problem of how to integrate evidence that a gene is differentially expressed with information on the extent of its differential expression. Consequently, researchers currently prioritize genes for further study either on the basis of volcano plots or, more commonly, according to simple estimates of the fold change after filtering the genes with an arbitrary statistical significance threshold. While the subjective and informal nature of the former practice precludes quantification of its reliability, the latter practice is equivalent to using a …

Research On Value-At-Risk In International Crude Oil Shipping Market, Xiaoyin Cui

World Maritime University Dissertations

No abstract provided.

The Research On Optimization Of Liner Route Between China To Middle East, Tingyi Chen

World Maritime University Dissertations

No abstract provided.

A Study On Opmtimizing The Cold Chain Logistic System In China, Huizhong Chen

World Maritime University Dissertations

No abstract provided.

Research On Decision-Making On Take-Back Models In Reverse Logistics For End-Of-Life Electronic Products, Yiwei Wang

World Maritime University Dissertations

No abstract provided.

A Spatio-Temporal Approach For Estimating Chronic Effects Of Air Pollution, Sonja Greven, Francesca Dominici, Scott L. Zeger

Johns Hopkins University, Dept. of Biostatistics Working Papers

Estimating the health risks associated with air pollution exposure is of great importance in public health. In air pollution epidemiology, two study designs have been used mainly. Time series studies estimate acute risk associated with short-term exposure. They compare day-to-day variation of pollution concentrations and mortality rates, and have been criticized for potential confounding by time-varying covariates. Cohort studies estimate chronic effects associated with long-term exposure. They compare long-term average pollution concentrations and time-to-death across cities, and have been criticized for potential confounding by individual risk factors or city-level characteristics.

We propose a new study design and a statistical model, …

Logistic Regression Using R, Joseph Hilbe

Joseph M Hilbe

R code and output for examples in Logistic Regression Models, Chapman & Hall/CRC (2009)

A Class Of Semiparametric Mixture Cure Survival Models With Dependent Censoring, Megan Othus, Yi Li, Ram C. Tiwari

Harvard University Biostatistics Working Paper Series

No abstract provided.

The Effects Of The Use Of Technology In Mathematics Instruction On Student Achievement, Ron Y. Myers

FIU Electronic Theses and Dissertations

The purpose of this study was to examine the effects of the use of technology on students’ mathematics achievement, particularly the Florida Comprehensive Assessment Test (FCAT) mathematics results. Eleven schools within the Miami-Dade County Public School System participated in a pilot program on the use of Geometers Sketchpad (GSP). Three of these schools were randomly selected for this study. Each school sent a teacher to a summer in-service training program on how to use GSP to teach geometry. In each school, the GSP class and a traditional geometry class taught by the same teacher were the study participants. Students’ mathematics …

Analysis Of Randomized Comparative Clinical Trial Data For Personalized Treatment Selections, Tianxi Cai, Lu Tian, Peggy H. Wong, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

Correlated Binary Regression Using Orthogonalized Residuals, Richard C. Zink, Bahjat F. Qaqish

COBRA Preprint Series

This paper focuses on marginal regression models for correlated binary responses when estimation of the association structure is of primary interest. A new estimating function approach based on orthogonalized residuals is proposed. This procedure allows a new representation and addresses some of the difficulties of the conditional-residual formulation of alternating logistic regressions of Carey, Zeger & Diggle (1993). The new method is illustrated with an analysis of data on impaired pulmonary function.

Robust Sensitivity Analysis For The Joint Improvised Explosive Device Defeat Organization (Jieddo) Proposal Selection Model, Christina J. Willy

Theses and Dissertations

Throughout Operations Iraqi Freedom and Enduring Freedom, the Department of Defense (DoD) faced challenges not experienced in our previous military operations. The enemy’s unwavering dedication to the use of improvised explosive devices (IEDs) against the coalition forces continues to challenge the day-to-day operations of the current war. The Joint Improvised Explosive Device Defeat Organization’s (JIEDDO) proposal solicitation process enables military and non-military organizations to request funding for the development of Counter-Improvised Explosive Device (C-IED) projects. Decision Analysis (DA) methodology serves as a tool to assist the decision maker (DM) in making an informed decision. This research applies Value Focused Thinking …

Using Agent-Based Modeling To Evaluate Uas Behaviors In A Target-Rich Environment, Joseph A. Van Kuiken

Theses and Dissertations

The trade-off between accuracy and speed is a re-occurring dilemma in many facets of military performance evaluation. This is an especially important issue in the world of ISR. One of the most progressive areas of ISR capabilities has been the utilization of Unmanned Aircraft Systems (UAS). Many people believe that the future of UAS lies in smaller vehicles flying in swarms. We use the agent-based System Effectiveness and Analysis Simulation (SEAS) to create a simulation environment where different configurations of UAS vehicles can process targets and provide output that allows us to gain insight into the benefits and drawbacks of …

Demonstration And Verification Of A Broad Spectrum Anomalous Dispersion Effects Tool For Index Of Refraction And Optical Turbulence Calculations, J. Jean Cohen

Theses and Dissertations

An atmospheric optical turbulence strength model with a broad wavelength range of 355nm (ultraviolet) to 8.6m (radio frequencies) has been created at AFIT and implemented into the High Energy Laser End-to-End Operational Simulation tool (HELEEOS). This modeling and simulation tool is a first principles atmospheric propagation and characterization model. Within HELEEOS lies the High-Resolution Transmission Molecular Absorption (HITRAN) database, containing 1,734,469 spectral lines for 37 different molecules as of version 12.0 (2004). HITRAN affords HELEEOS incredible accuracy for electromagnetic (EM) propagation prediction. A full understanding of optical turbulence is needed to successfully predict EM radiation propagation, particularly within the application …

Creating Multi Objective Value Functions From Non-Independent Values, Christopher D. Richards

Theses and Dissertations

Decisions are made every day and by everyone. As these decisions become more important, involve higher costs and affect a broader group of stakeholders it becomes essential to establish a more rigorous strategy than simply intuition or "going with your gut". In the past several decades, the concept of Value Focused Thinking (VFT) has gained much acclaim in assisting Decision Makers (DMs) in this very effort. By identifying and organizing what a DM values VFT is able to decompose the original problem and create a mathematical model to score and rank alternatives to be chosen. But what if the decision …

Group Comparison Of Eigenvalues And Eigenvectors Of Diffusion Tensors, Armin Schwartzman, Robert F. Dougherty, Jonathan E. Taylor

Harvard University Biostatistics Working Paper Series

No abstract provided.

Conservation Implications Of A Marbled Salamander, Ambystoma Opacum, Metapopulation Model, Ethan B. Plunkett

Masters Theses 1911 - February 2014

Amphibians are in decline globally and a significantly greater percentage of ambystomatid salamander species are in decline relative to other species; habitat loss contributes significantly to this decline. The goals of this thesis is to better understand extinction risk in a marbled salamander (ambystoma opacum) population and how forestry effects extinction risk. To achieve this goal we first estimated an important life history parameter (Chapter 1) then used a metapopulation model to estimate population viability and determine what aspects of their life history put them most at risk (Chapter 2) and finally predicted extinction risk in response to hypothetical forestry …

An Examination Of The Persistence Of The Residual Child Welfare System In The United States: Addressing Charges Of Radical Theoretical Myopia With Implications For Social Work Practice, Peter Cabrera

Elián P. Cabrera-Nguyen

The United States follows what has been termed a residual approach to its public child welfare system. This article describes the residual model and contrasts it with the policies of other industrialized nations. It also explores the causes and persistence of the residual model in the United States through the lens of structural-functionalist theory. By doing so, this article attempts to respond to critics of structural social work who maintain that it is overly reliant on conflict theory and has nothing to offer in terms of distinct practice methods. Suggestions for a structurally informed social work practice are made.

Multilevel Functional Principal Component Analysis, Chong-Zhi Di, Ciprian M. Crainiceanu, Brian S. Caffo, Naresh M. Punjabi

Chongzhi Di

The Sleep Heart Health Study (SHHS) is a comprehensive landmark study of sleep and its impacts on health outcomes. A primary metric of the SHHS is the in-home polysomnogram, which includes two electroencephalographic (EEG) channels for each subject, at two visits. The volume and importance of this data presents enormous challenges for analysis. To address these challenges, we introduce multilevel functional principal component analysis (MFPCA), a novel statistical methodology designed to extract core intra- and inter-subject geometric components of multilevel functional data. Though motivated by the SHHS, the proposed methodology is generally applicable, with potential relevance to many modern scientific …

Nonparametric Signal Extraction And Measurement Error In The Analysis Of Electroencephalographic Activity During Sleep, Ciprian M. Crainiceanu, Brian S. Caffo, Chong-Zhi Di, Naresh M. Punjabi

Chongzhi Di

We introduce methods for signal and associated variability estimation based on hierarchical nonparametric smoothing with application to the Sleep Heart Health Study (SHHS). SHHS is the largest electroencephalographic (EEG) collection of sleep-related data, which contains, at each visit, two quasi-continuous EEG signals for each subject. The signal features extracted from EEG data are then used in second level analyses to investigate the relation between health, behavioral, or biometric outcomes and sleep. Using subject specific signals estimated with known variability in a second level regression becomes a nonstandard measurement error problem.We propose and implement methods that take into account cross-sectional and …

Generalized Multilevel Functional Regression, Ciprian M. Crainiceanu, Ana-Maria Staicu, Chong-Zhi Di

Chongzhi Di

We introduce Generalized Multilevel Functional Linear Models (GMFLMs), a novel statistical framework for regression models where exposure has a multilevel functional structure. We show that GMFLMs are, in fact, generalized multilevel mixed models. Thus, GMFLMs can be analyzed using the mixed effects inferential machinery and can be generalized within a well-researched statistical framework. We propose and compare two methods for inference: (1) a two-stage frequentist approach; and (2) a joint Bayesian analysis. Our methods are motivated by and applied to the Sleep Heart Health Study, the largest community cohort study of sleep. However, our methods are general and easy to …

Balance Diagnostics For Comparing The Distribution Of Baseline Covariates Between Treatment Groups In Propensity-Score Matched Samples, Peter C. Austin

Peter Austin

The propensity score is a subject’s probability of treatment, conditional on observed baseline covariates. Conditional on the true propensity score, treated and untreated subjects have similar distributions of observed baseline covariates. Propensity-score matching is a popular method of using the propensity score in the medical literature. Using this approach, matched sets of treated and untreated subjects with similar values of the propensity score are formed. Inferences about treatment effect made using propensity-score matching are valid only if, in the matched sample, treated and untreated subjects have similar distributions of measured baseline covariates. In this paper we discuss the following methods …