Statistical Models Commons^™

Stratifying Subjects For Treatment Selection With Censored Event Time Data From A Comparative Study, Lihui Zhao, Tianxi Cai, Lu Tian, Hajime Uno, Scott D. Solomon, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

Veterans Of The 1st Persian Gulf War: A Study Of Medically Unexplained Symptom Models, Alexis H. Collins

Loma Linda University Electronic Theses, Dissertations & Projects

In 1990-1991, shortly after the Persian Gulf War, a number of veterans began complaining about a wide range of symptoms, the most common of which were; fatigue, headache, sleep disturbance, low mood, and memory loss. These symptoms were similar to those experienced by individuals with Medically Unexplained Illnesses such as Chronic Fatigue Syndrome, Fibromyalgia, Irritable Bowel Syndrome, Multiple Chemical Sensitivity, and Somatoform Disorders. Utilizing structural equation modeling and data gathered from the Gulf War Veterans Health Questionnaire, this study attempted to determine whether symptoms experienced by veterans were best explained as individual items, discrete illnesses, or as a conglomeration of …

Creating Prediction Models For Obstructive Sleep Apnea Based On Gender, Jeffrey Hwang

Loma Linda University Electronic Theses, Dissertations & Projects

Introduction: Obstructive sleep apnea (OSA) is a common chronic disorder that is characterized by repetitive episodes of airflow cessation or reduction occurring during sleep as a result of partial or complete upper airway obstruction. These recurrent events have a tremendous impact on the cardiovascular system with a multitude of dangerous consequences. Numerous studies have been conducted determining etiological risk factors for OSA including anatomical predictors which have been observed with multiple imaging techniques. Cone beam computed tomography (CBCT) is a low-radiation mode of imaging that can be used to accurately identify anatomical landmarks and measure craniofacial relationships and airway dimensions. …

Mixed Effect Poisson Log-Linear Models For Clinical And Epidemiological Sleep Hypnogram Data, Bruce J. Swihart, Brian S. Caffo Phd, Ciprian Crainiceanu Phd, Naresh M. Punjabi Phd, Md

Johns Hopkins University, Dept. of Biostatistics Working Papers

Bayesian Poisson log-linear multilevel models scalable to epidemiological studies are proposed to investigate population variability in sleep state transition rates. Hierarchical random effects are used to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of importance. Essentially, non-parametric piecewise constant hazards are estimated and smoothed, allowing for time-varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming exponentially distributed survival times. Such re-derivation …

Estimating Teacher Effects Using Value-Added Models, Jennifer L. Green

Department of Statistics: Dissertations, Theses, and Student Research

Value-added modeling is an alternative approach to test-based accountability systems based on the proportions of students scoring at or above pre-determined proficiency levels. Value-added modeling techniques provide opportunities to estimate an individual teacher’s effect on student learning, while allowing for the possibility to control for the effect of non-educational factors beyond a school system’s control, such as socioeconomic status. However, numerous considerations exist when using value-added models to estimate teacher effects and defining what the teacher effects really describe. Chapter 2 provides an introduction to value-added methodology by describing several value-added models available for estimating teacher effects and their respective …

A Bayesian Approach To Dose-Response Assessment And Drug-Drug Interaction Analysis: Application To In Vitro Studies, Violeta G. Hennessey

Dissertations and Theses (Open Access)

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis.

The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method …

Principled Sure Independence Screening For Cox Models With Ultra-High-Dimensional Covariates, Sihai Dave Zhao, Yi Li

Harvard University Biostatistics Working Paper Series

No abstract provided.

A Unified Approach To Modeling Multivariate Binary Data Using Copulas Over Partitions, Bruce J. Swihart, Brian Caffo, Ciprian Crainiceanu

Johns Hopkins University, Dept. of Biostatistics Working Papers

Many seemingly disparate approaches for marginal modeling have been developed in recent years. We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the proposed copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate …

Statistical Analysis Of Texas Holdem Poker, Daniel Bragonier

Statistics

Gathered lifetime online Poker data for Mike Linn. Attempted to analyze data to obtain information to maximize profit. Techniques included Univariate Analysis, Regression analysis, Anova analysis, Logistic Regression, and outlier Analysis. After the analysis, nothing of supreme importance or sustenance was found. Encountered issues with too much power. Results lead to plenty of statistical significance, but little practical significance. Results showed that the data did not provide all the answers that were being sought after, but there was some value in examining the data in a strict statistical manner.

Survival Prediction For Brain Tumor Patients Using Gene Expression Data, Vinicius Bonato

Dissertations and Theses (Open Access)

Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. …

Nonparametric Regression With Missing Outcomes Using Weighted Kernel Estimating Equations, Lu Wang, Andrea Rotnitzky, Xihong Lin

Harvard University Biostatistics Working Paper Series

No abstract provided.

Nonparametric And Semiparametric Analysis Of Current Status Data Subject To Outcome Misclassification, Victor G. Sal Y Rosas, James P. Hughes

UW Biostatistics Working Paper Series

In this article, we present nonparametric and semiparametric methods to analyze current status data subject to outcome misclassification. Our methods use nonparametric maximum likelihood estimation (NPMLE) to estimate the distribution function of the failure time when sensitivity and specificity may vary among subgroups. A nonparametric test is proposed for the two sample hypothesis testing. In regression analysis, we apply the Cox proportional hazard model and likelihood ratio based confidence intervals for the regression coefficients are proposed. Our methods are motivated and demonstrated by data collected from an infectious disease study in Seattle, WA.

An Analysis Of Nonignorable Nonresponse In A Survey With A Rotating Panel Design, Caterina Giusti, Roderick J. Little

The University of Michigan Department of Biostatistics Working Paper Series

Missing values to income questions are common in survey data. When the probabilities of nonresponse are assumed to depend on the observed information and not on the underlining unobserved amounts, the missing income values are missing at random (MAR), and methods such as sequential multiple imputation can be applied. However, the MAR assumption is often considered questionable in this context, since missingness of income is thought to be related to the value of income itself, after conditioning on available covariates. In this article we describe a sensitivity analysis based on a pattern-mixture model for deviations from MAR, in the context …

Software Internationalization: A Framework Validated Against Industry Requirements For Computer Science And Software Engineering Programs, John Huân Vũ

Master's Theses

View John Huân Vũ's thesis presentation at http://youtu.be/y3bzNmkTr-c.

In 2001, the ACM and IEEE Computing Curriculum stated that it was necessary to address "the need to develop implementation models that are international in scope and could be practiced in universities around the world." With increasing connectivity through the internet, the move towards a global economy and growing use of technology places software internationalization as a more important concern for developers. However, there has been a "clear shortage in terms of numbers of trained persons applying for entry-level positions" in this area. Eric Brechner, Director of Microsoft Development Training, suggested …

Research Poster: Climate Prediction Downscaling Of Temperature And Precipitation In The Great Basin Region, Ramesh Vellore, Benjamin J. Hatchett, Darko Koracin

2010 Annual Nevada NSF EPSCoR Climate Change Conference

Research poster

Research Poster: Hydrological Impacts Of Climate Change On Colorado Basin, Peng Jiang, Zhongbo Yu

2010 Annual Nevada NSF EPSCoR Climate Change Conference

Research poster

Research Poster: An Overview Of Progress In Nsf Epscor Project Entitled, “Reducing Cloud Uncertainties In Climate Models”, Subhashree Mishra, David L. Mitchell, W. Patrick Arnott

2010 Annual Nevada NSF EPSCoR Climate Change Conference

Research poster

The Location Decisions Of Foreign Investors In China: Untangling The Effect Of Wages Using A Control Function Approach, Xuepeng Liu, Mary E. Lovely, Jan Ondrich

Faculty Articles

There is almost no support for the proposition that capital is attracted to low wages from firm-level studies. We examine the location choices of 2,884 firms investing in China between 1993 and 1996 to offer two main contributions. First, we find that the location of labor-intensive activities is highly elastic to provincial wage differences. Generally, investors' wage sensitivity declines as the skill intensity of the industry increases. Second, we find that unobserved location-specific attributes exert a downward bias on estimated wage sensitivity. Using a control function approach, we estimate a downward bias of 50% to 90% in wage coefficients estimated …

Robustness Of Approaches To Roc Curve Modeling Under Misspecification Of The Underlying Probability Model, Sean Devlin, Elizabeth Thomas, Scott S. Emerson

UW Biostatistics Working Paper Series

The receiver operating characteristic (ROC) curve is a tool of particular use in disease status classification with a continuous medical test (marker). A variety of statistical regression models have been proposed for the comparison of ROC curves for different markers across covariate groups. A full parametric modeling of the marker distribution has been generally found to be overly reliant on the strong parametric assumptions. Pepe (2003) has instead developed parametric models for the ROC curve that induce a semi-parametric model for the marker distributions. The estimating equations proposed for use in these ROC-GLM models may differ from commonly used estimating …

The Joint Distribution Of Bivariate Exponential Under Linearly Related Model, Norou Diawara, Kumer Pial Das

Mathematics & Statistics Faculty Publications

In this paper, fundamental results of the joint distribution of the bivariate exponential distributions are established. The positive support multivariate distribution theory is important in reliability and survival analysis, and we applied it to the case where more than one failure or survival is observed in a given study. Usually, the multivariate distribution is restricted to those with marginal distributions of a specified and familiar lifetime family. The family of exponential distribution contains the absolutely continuous and discrete case models with a nonzero probability on a set of measure zero. Examples are given, and estimators are developed and applied to …