Statistical Models Commons^™

Addressing The Problem Of Non-Response And Response Bias, Fabian C. Okafor

CBN Journal of Applied Statistics (JAS)

Survey planners and analysts in Nigeria have devoted much more attention to sampling errors at the expense of nonsampling errors (non-response and response errors). Sampling error is the degree to which the sample estimate differs from the average value of the characteristic due to chance. The present discussion will be centered on non-sampling error, which may present serious deficiencies in the statistics and render the survey useless. According to Platek and Gray (1986), “Non-response has been generally recognized as important measure of the quality of data since it affects the estimates by introducing a possible bias in the estimates and …

Poisson Process Monitoring, Test And Comparison, Qing Chen

UNLV Theses, Dissertations, Professional Papers, and Capstones

The task of determining whether a sudden change occurred in the generative parameters of a time series generates application in many areas. In this thesis, we aim at monitoring the change-point of a Poisson process by method, which is characterized by a forward-backward testing algorithm and several overall error control mechanisms. With the application of this proposed method, we declare that Mount Etna is not a simple Poissonian volcano, because two different regimes divided by the change point, January 30th 1974, are identified. The validation procedures, used in a complementary fashion, by the formal hypothesis tests and graphical method will …

Bayesian Logistic Regression Model For Siting Biomass-Using Facilities, Xia Huang

Masters Theses

Key sources of oil for western markets are located in complex geopolitical environments that increase economic and social risk. The amalgamation of economic, environmental, social and national security concerns for petroleum-based economies have created a renewed emphasis on alternative sources of energy which include biomass. The stability of sustainable biomass markets hinges on improved methods to predict and visualize business risk and cost to the supply chain.

This thesis develops Bayesian logistic regression models, with comparisons of classical maximum likelihood models, to quantify significant factors that influence the siting of biomass-using facilities and predict potential locations in the 13-state Southeastern …

Effects Of Acculturation On Hiv/Aids Sexual Risk Behaviors Among Asian And Pacific Islander (Api) Women, Margaret Cabotage Salud

Loma Linda University Electronic Theses, Dissertations & Projects

Background. In the US women are the fastest growing group for sexually transmitted infections (STIs), including HIV and AIDS. In addition, the estimated AIDS cases among female adults and adolescents, aged 13-19, increased from 7% in 1985 to approximately 26% in 2002. Most infections occur by heterosexual transmission with 53% occurring through contact with a high-risk sexual partner. While overall HIV/AIDS rates in the Asian Pacific Islander (API) community remain low, they are rising and HIV testing rates, one of the major prevention strategies for HIV, are lower than that of other populations. Furthermore, very little is known about APIs …

Modeling Longitudinal Data Using A Pair-Copula Decomposition Of Serial Dependence, Michael S. Smith, Aleksey Min, Carlos Almeida, Claudia Czado

Michael Stanley Smith

Copulas have proven to be very successful tools for the flexible modelling of cross-sectional dependence. In this paper we express the dependence structure of continuous-valued time series data using a sequence of bivariate copulas. This corresponds to a type of decomposition recently called a ‘vine’ in the graphical models literature, where each copula is entitled a ‘pair-copula’. We propose a Bayesian approach for the estimation of this dependence structure for longitudinal data. Bayesian selection ideas are used to identify any independence pair-copulas, with the end result being a parsimonious representation of a time-inhomogeneous Markov process of varying order. Estimates are …

A Bayesian Shared Component Model For Genetic Association Studies, Juan J. Abellan, Carlos Abellan, Juan R. Gonzalez

COBRA Preprint Series

We present a novel approach to address genome association studies between single nucleotide polymorphisms (SNPs) and disease. We propose a Bayesian shared component model to tease out the genotype information that is common to cases and controls from the one that is specific to cases only. This allows to detect the SNPs that show the strongest association with the disease. The model can be applied to case-control studies with more than one disease. In fact, we illustrate the use of this model with a dataset of 23,418 SNPs from a case-control study by The Welcome Trust Case Control Consortium (2007) …

Minimum Description Length And Empirical Bayes Methods Of Identifying Snps Associated With Disease, Ye Yang, David R. Bickel

COBRA Preprint Series

The goal of determining which of hundreds of thousands of SNPs are associated with disease poses one of the most challenging multiple testing problems. Using the empirical Bayes approach, the local false discovery rate (LFDR) estimated using popular semiparametric models has enjoyed success in simultaneous inference. However, the estimated LFDR can be biased because the semiparametric approach tends to overestimate the proportion of the non-associated single nucleotide polymorphisms (SNPs). One of the negative consequences is that, like conventional p-values, such LFDR estimates cannot quantify the amount of information in the data that favors the null hypothesis of no disease-association.

We …

Geographic Factors Of Residential Burglaries - A Case Study In Nashville, Tennessee, Jonathan A. Hall

Masters Theses & Specialist Projects

This study examines geographic patterns and geographic factors of residential burglary at the Nashville, TN area for a twenty year period at five year interval starting in 1988. The purpose of this study is to identify what geographic factors have impacted on residential burglary rates, and if there were changes in the geographic patterns of residential burglary over the study period. Several criminological theories guide this study, with the most prominent being Social Disorganization Theory and Routine Activities Theory. Both of these theories focus on the relationships of place and crime. A number of spatial analysis methods are hence adopted …

Curriculum Vitae, Tatiyana V. Apanasovich

Tatiyana V Apanasovich

No abstract provided.

Men In Black: The Impact Of New Contracts On Football Referees’ Performances, Babatunde Buraimo, Alex Bryson, Rob Simmons

Dr Babatunde Buraimo

No abstract provided.

The Statistical Properties Of The Survivor Interaction Contrast, Joseph W. Houpt, James T. Townsend

Joseph W. Houpt

The Survivor Interaction Contrast (SIC) is a powerful tool for assessing the architecture and stopping rule of a model of mental processes. Despite its demonstrated utility, the methodology has lacked a method for statistical testing until now. In this paper we briefly describe the SIC then develop some basic statistical properties of the measure. These developments lead to a statistical test for rejecting certain classes of models based on the SIC. We verify these tests using simulated data, then demonstrate their use on data from a simple cognitive task.

The Statistical Properties Of The Survivor Interaction Contrast, Joseph W. Houpt, James T. Townsend

Psychology Faculty Publications

The Survivor Interaction Contrast (SIC) is a powerful tool for assessing the architecture and stopping rule of a model of mental processes. Despite its demonstrated utility, the methodology has lacked a method for statistical testing until now. In this paper we briefly describe the SIC then develop some basic statistical properties of the measure. These developments lead to a statistical test for rejecting certain classes of models based on the SIC. We verify these tests using simulated data, then demonstrate their use on data from a simple cognitive task.

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 …

Mixture Of Factor Analyzers With Information Criteria And The Genetic Algorithm, Esra Turan

Doctoral Dissertations

In this dissertation, we have developed and combined several statistical techniques in Bayesian factor analysis (BAYFA) and mixture of factor analyzers (MFA) to overcome the shortcoming of these existing methods. Information Criteria are brought into the context of the BAYFA model as a decision rule for choosing the number of factors m along with the Press and Shigemasu method, Gibbs Sampling and Iterated Conditional Modes deterministic optimization. Because of sensitivity of BAYFA on the prior information of the factor pattern structure, the prior factor pattern structure is learned directly from the given sample observations data adaptively using Sparse Root algorithm. …

Functional Principal Components Analysis And The Capacity Coefficient, D. Burns, Joseph W. Houpt, M. J. Endres, J. T. Townsend

Joseph W. Houpt

The capacity coefficient is a well established measure of the efficiency of processing combined sources of information. It has been applied to measure cognitive processes ranging from audio-visual integration to face perception. Recently, the capacity coefficient has also been applied in various clinical situations. Typical clinical analysis, such as structural equation modeling, use scalar values or vectors with limited length as input. We explored the use of functional principal component analysis (fPCA) to allow researchers to describe the capacity coefficient, a continuous function of time, with a small set of discrete values. The fPCA approach was compared with two simple …

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

Dissertations & 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 …

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

Department of Statistics: Dissertations, Theses, and Student Work

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 …

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.

The 1905 Einstein Equation In A General Mathematical Analysis Model Of Quasars, Byron E. Bell

Byron E. Bell

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

Dissertations & 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: Hydrological Impacts Of Climate Change On Colorado Basin, Peng Jiang, Zhongbo Yu

2010 Annual Nevada NSF EPSCoR Climate Change Conference

Research poster