Statistical Models Commons^™

A Practical Solution To The Reference Class Problem, Edward K. Cheng

Vanderbilt Law School Faculty Publications

The "reference class problem" is a serious challenge to the use of statistical evidence that arguably arises every day in wide variety of cases, including toxic torts, property valuation, and even drug smuggling. At its core, it observes that statistical inferences depend critically on how people, events, or things are classified. As there is (purportedly) no principle for privileging certain categories over others, statistics become manipulable, undermining the very objectivity and certainty that make statistical evidence valuable and attractive to legal actors. In this paper, I propose a practical solution to the reference class problem by drawing on model selection …

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

Department of Statistics: Dissertations, Theses, and Student Research

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.

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 …

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

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.

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

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, …

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.

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 …

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 …

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 …

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.

Proportional Odds Model For Dose Finding Clinical Trial Designs With Ordinal Toxicity Grading, Emily Marie Van Meter

MUSC Theses and Dissertations

Currently many dose finding clinical trial designs, including the continual reassessment method (CRM) and the standard 3 + 3 design, dichotomize toxicity outcomes based on pre-specified dose-limiting toxicity criteria. This loss of information is particularly inefficient due to the small sample sizes in phase I trials. Common Toxicity Criteria (CTCAE v3 .0) classify adverse events into grades 1 through 5, which range from 1 as a mild adverse event to 5 as death related to an adverse event. In this paper, we extend the CRM to include ordinal toxicity outcomes as specified by CTCAEv3.0 using the proportional odds model and …

Statistical Approaches For Adding Or Switching Hypotheses In Multi-Armed Clinical Trials, Jordan Jaskwhich Elm

MUSC Theses and Dissertations

As treatments become ready for testing at staggered times, it is desirable to have clinical trials that can accommodate different entry and exit times without prematurely discarding potentially efficacious treatments. In a group sequential multi-armed clinical trial, one treatment arm could be found to be superior or inferior at an interim analysis while the remaining arm is inconclusive. Existing methods address dropping an inferior arm from further study, , but do not fully address the handling of an early finding of overwhelming superiority of one arm (scenario 1). We consider an approach to transition from a multi-armed superiority trial to …

Using Paired Comparison Matrices To Estimate Parameters Of The Partial Credit Rasch Measurement Model For Rater-Mediated Assessments, Mary Garner, George Engelhard Jr.

Faculty Articles

The purpose of this paper is to describe a technique for estimating the parameters of a Rasch model that accommodates ordered categories and rater severity. The technique builds on the conditional pairwise algorithm described by Choppin (1968, 1985) and represents an extension of a conditional algorithm described by Garner and Engelhard (2000, 2002) in which parameters appear as the eigenvector of a matrix derived from paired comparisons. The algorithm is used successfully to recover parameters from a simulated data set. No one has previously described such an extension of the pairwise algorithm to a Rasch model that includes both ordered …

Using Decision Analytic Modelling To Simulate Pregnancy, Jeffrey Cannon

Theses : Honours

Decision analytic modelling enables decision makers to assess the cost-effectiveness associated with a proposed change in a cunent system without physically implementing the changes. This can be achieved by formulating a mathematical model that represents all the major events occuning in the system through fmmulas and algorithms, and estimating the likely outcomes along with their costs. This type of modelling has been identified by the State Health Research Advisory Council (SHRAC) of the Western Australian Depmiment of Health as an asset for the plmming of health care investments in the future. One such area in which the Western Australian Department …

Multiple Imputation To Correct For Measurement Error In Admixture Estimates In Genetic Structured Association Testing, Miguel A. Padilla, Jamin Divers, Laura K. Vaughan, David B. Allison, Hemant K. Tiwari

Psychology Faculty Publications

Objectives: Structured association tests ( SAT), like any statistical model, assumes that all variables are measured without error. Measurement error can bias parameter estimates and confound residual variance in linear models. It has been shown that admixture estimates can be contaminated with measurement error causing SAT models to suffer from the same afflictions. Multiple imputation (MI) is presented as a viable tool for correcting measurement error problems in SAT linear models with emphasis on correcting measurement error contaminated admixture estimates. Methods: Several MI methods are presented and compared, via simulation, in terms of controlling Type I error rates for both …