Statistics and Probability Commons^™

Evaluating Methods For The Analysis Of Rare Variants In Sequence Data, Alexander Luedtke, Scott Powers, Ashley Petersen, Alexandra Sitarik, Airat Bekmetjev, Nathan L. Tintle

Faculty Work Comprehensive List

A number of rare variant statistical methods have been proposed for analysis of the impending wave of next-generation sequencing data. To date, there are few direct comparisons of these methods on real sequence data. Furthermore, there is a strong need for practical advice on the proper analytic strategies for rare variant analysis. We compare four recently proposed rare variant methods (combined multivariate and collapsing, weighted sum, proportion regression, and cumulative minor allele test) on simulated phenotype and next-generation sequencing data as part of Genetic Analysis Workshop 17. Overall, we find that all analyzed methods have serious practical limitations on identifying …

Evaluating Methods For Combining Rare Variant Data In Pathway-Based Tests Of Genetic Association, Ashley Petersen, Alexandra Sitarik, Alexander Luedtke, Scott Powers, Airat Bekmetjev, Nathan L. Tintle

Faculty Work Comprehensive List

Analyzing sets of genes in genome-wide association studies is a relatively new approach that aims to capitalize on biological knowledge about the interactions of genes in biological pathways. This approach, called pathway analysis or gene set analysis, has not yet been applied to the analysis of rare variants. Applying pathway analysis to rare variants offers two competing approaches. In the first approach rare variant statistics are used to generate p-values for each gene (e.g., combined multivariate collapsing [CMC] or weighted-sum [WS]) and the gene-level p-values are combined using standard pathway analysis methods (e.g., gene set enrichment analysis or …

Identifying Rare Variants From Exome Scans: The Gaw17 Experience, Saurabh Ghosh, Heike Bickeboller, Julia Bailey, Joan E. Bailey-Wilson, Rita Cantor, Robert Culverhouse, Warwick Daw, Anita L. Destefano, Corinne D. Engelman, Anthony Hinrichs, Jeanine Houwing-Duistermaat, Inke R. Konig, Jack Kent, Nan Laird, Nathan Pankratz, Andrew Paterson, Elizabeth Pugh, Brian Suarez, Yan Sun, Alun Thomas, Nathan L. Tintle, Xiaofeng Zhu, Andreas Ziegler, Jean W. Maccluer, Laura Almasy

Faculty Work Comprehensive List

Genetic Analysis Workshop 17 (GAW17) provided a platform for evaluating existing statistical genetic methods and for developing novel methods to analyze rare variants that modulate complex traits. In this article, we present an overview of the 1000 Genomes Project exome data and simulated phenotype data that were distributed to GAW17 participants for analyses, the different issues addressed by the participants, and the process of preparation of manuscripts resulting from the discussions during the workshop

Longitudinal Investigation Of The Curricular Effect: An Analysis Of Student Learning Outcomes From The Liecal Project In The United States, Jinfa Cai, Ning Wang, John Moyer, Chuang Wang, Bikai Nie

Mathematics, Statistics and Computer Science Faculty Research and Publications

In this article, we present the results from a longitudinal examination of the impact of a Standards-based or reform mathematics curriculum (called CMP) and traditional mathematics curricula (called non-CMP) on students’ learning of algebra using various outcome measures. Findings include the following: (1) students did not sacrifice basic mathematical skills if they are taught using a Standards-based or reform mathematics curriculum like CMP; (2) African American students experienced greater gain in symbol manipulation when they used a traditional curriculum; (3) the use of either the CMP or a non-CMP curriculum improved the mathematics achievement of all students, including …

Bayesian Item Response Theory: Statistical Inference And Power Analysis, Jason W. Bodnar

Dissertations

The regulatory pharmaceutical approval process is flawed in that industry clinical trials (ICTs) are always powered for efficacy and rarely powered for safety. The key safety parameter is the adverse event (AE). This practice may result in efficacious products with confounded safety. An ICT’s ability to be powered for detecting AE trends may improve patient safety. Therefore, this dissertation’s purpose was to determine if power analysis resulted in feasible sample sizes for substantiating AE hypotheses. AEs were modeled with three Bayesian 2PL IRT models. The unidimensional latent trait, transfusion-related AE, was modeled as a patient predisposition for experiencing an AE. …

Statistician Recommends A Dose Of Skepticism, Aldemaro Romero Jr.

Publications and Research

No abstract provided.

Neath Studies, Teaches The Uncertainties Of Life, Aldemaro Romero Jr.

Publications and Research

No abstract provided.

Some Contributions To The Censored Empirical Likelihood With Hazard-Type Constraints, Yanling Hu

University of Kentucky Doctoral Dissertations

Empirical likelihood (EL) is a recently developed nonparametric method of statistical inference. Owen’s 2001 book contains many important results for EL with uncensored data. However, fewer results are available for EL with right-censored data. In this dissertation, we first investigate a right-censored-data extension of Qin and Lawless (1994). They studied EL with uncensored data when the number of estimating equations is larger than the number of parameters (over-determined case). We obtain results similar to theirs for the maximum EL estimator and the EL ratio test, for the over-determined case, with right-censored data. We employ hazard-type constraints which are better able …

Studies In Sampling Techniques And Time Series Analysis, Florentin Smarandache, Rajesh Singh

Branch Mathematics and Statistics Faculty and Staff Publications

This book has been designed for students and researchers who are working in the field of time series analysis and estimation in finite population. There are papers by Rajesh Singh, Florentin Smarandache, Shweta Maurya, Ashish K. Singh, Manoj Kr. Chaudhary, V. K. Singh, Mukesh Kumar and Sachin Malik. First chapter deals with the problem of time series analysis and the rest of four chapters deal with the problems of estimation in finite population. The book is divided in five chapters as follows: Chapter 1. Water pollution is a major global problem. In this chapter, time series analysis is carried out …

Uniform And Partially Uniform Redistribution Rules, Florentin Smarandache, Jean Dezert

Branch Mathematics and Statistics Faculty and Staff Publications

This short paper introduces two new fusion rules for combining quantitative basic belief assignments. These rules although very simple have not been proposed in literature so far and could serve as useful alternatives because of their low computation cost with respect to the recent advanced Proportional Conflict Redistribution rules developed in the DSmT framework.

Some Ratio Type Estimators Under Measurement Errors, Florentin Smarandache, Mukesh Kumar, Rajesh Singh, Ashish K. Singh

Branch Mathematics and Statistics Faculty and Staff Publications

This article addresses the problem of estimating the population mean using auxiliary information in the presence of measurement errors.

Weighted Scores Method For Regression Models With Dependent Data, Aristidis K. Nikoloulopoulos, Harry Joe, N. Rao Chaganty

Mathematics & Statistics Faculty Publications

There are copula-based statistical models in the literature for regression with dependent data such as clustered and longitudinal overdispersed counts, for which parameter estimation and inference are straightforward. For situations where the main interest is in the regression and other univariate parameters and not the dependence, we propose a "weighted scores method", which is based on weighting score functions of the univariate margins. The weight matrices are obtained initially fitting a discretized multivariate normal distribution, which admits a wide range of dependence. The general methodology is applied to negative binomial regression models. Asymptotic and small-sample efficiency calculations show that our …

Detecting Temporal Patterns Using Reconstructed Phase Space And Support Vector Machine In The Dynamic Data System, Wenjing Zhang, Xin Feng

Mathematics, Statistics and Computer Science Faculty Research and Publications

In this paper we present a method for detecting dynamic temporal patterns that are characteristic and predictive of significant events in a dynamic data system. We employ the Gaussian Mixture Model (GMM) to cluster the data sequence into three categories of signals, e.g. normal, patterns and events. The data sequence is then embedded into a Reconstructed Phase Space (RPS) which is topologically equivalent to the dynamics of the original system. We apply a hybrid method using Support Vector Machines (SVM) and Maximum a Posterior (MAP) to classify temporal pattern signals based on the event function. We performed two experimental applications …

On The First-Order Expressibility Of Lattice Properties To Unicoherence In Continua, Paul Bankston

Mathematics, Statistics and Computer Science Faculty Research and Publications

Many properties of compacta have “textbook” definitions which are phrased in lattice-theoretic terms that, ostensibly, apply only to the full closed-set lattice of a space. We provide a simple criterion for identifying such definitions that may be paraphrased in terms that apply to all lattice bases of the space, thereby making model-theoretic tools available to study the defined properties. In this note we are primarily interested in properties of continua related to unicoherence; i.e., properties that speak to the existence of “holes” in a continuum and in certain of its subcontinua.

Impact Of Curriculum Reform: Evidence Of Change In Classroom Instruction In The United States, John Moyer, Jinfa Cai, Ning Wang, Bikai Nie

Mathematics, Statistics and Computer Science Faculty Research and Publications

The purpose of the study reported in this article is to examine the impact of curriculum on instruction. Over a three-year period, we observed 579 algebra-related lessons in grades 6–8. Approximately half the lessons were taught in schools that had adopted a Standards-based mathematics curriculum called the Connected Mathematics Program (CMP), and the remainder of the lessons were taught in schools that used more traditional curricula (non-CMP). We found many significant differences between the CMP and non-CMP lessons. The CMP lessons, emphasized the conceptual aspects of instruction to a greater extent than the non-CMP lessons and the non-CMP lessons …

A Characterization Of Connected (1,2)-Domination Graphs Of Tournaments, Kim A. S. Factor, Larry J. Langley

Mathematics, Statistics and Computer Science Faculty Research and Publications

Recently. Hedetniemi et aI. introduced (1,2)-domination in graphs, and the authors extended that concept to (1, 2)-domination graphs of digraphs. Given vertices x and y in a digraph D, x and y form a (1,2)-dominating pair if and only if for every other vertex z in D, z is one step away from x or y and at most two steps away from the other. The (1,2)-dominating graph of D, dom_1,2 (D), is defined to be the graph G = (V, E ) , where V (G) = V (D), and xy is …

On The Distributions Of Certain Spacings, Gholamhossein Hamedani, Hans Volkmer

Mathematics, Statistics and Computer Science Faculty Research and Publications

A characterization of the uniform distribution based on distributions of spacings is presented which extends the existing result in this direction. Also, a result on the distribution of spacings for distributions close to the uniform one is discussed.

Bayesian Computational Methods For Hidden Markov Models, Samson Laine Ghebremariam

Open Access Theses & Dissertations

Hidden Markov Models (HMMs) have been applied to many real-world problems. Hidden Markov modeling has recently become increasingly important and popular among researchers,and many software tools are based on them. Given that the models are rich in mathematical structure, they can form theoretical foundation for use in a wide range of applications. Hidden Markov models provide a universal configuration for statistical analysis of a large variety of DNA sequences containing symbols A, C, G, T. In a HMM, it is impossible to figure out what state the model is in by just having a look at the symbol generated.

A …

A Proposed Epithermal Model For The High Grade District, California, Michael Nicholas Feinstein

Open Access Theses & Dissertations

A historic gold mining district in northeastern California has not been incorporated into the global knowledge base for precious metal vein deposits. This study collected various data types which are important characteristics in the classification and understanding of vein deposits. The High Grade District (HGD) is a gold mining site located in the northeast corner of Modoc County, California, in the Warner Mountains. The Warner Mountains are composed of Tertiary eruptive centers, cropping out between valleys formed through extensional tectonics. Mineralization of the HGD displays abundant silicification, adularia, and gold; these characteristics are sufficient to classify mineralization as low-sulfidation epithermal …

Gamma And Generalized Gamma Distributions, Victor Hugo Jiménez Nava

Open Access Theses & Dissertations

We present the Generalized Gamma Distribution, study its properties and derive the estimators of the parameters. This distribution includes many standard forms, like: Gamma, Exponential, Weibull, Half Normal and others. Sum and ratios of independent generalized gamma lead to intractable forms. However approximation works well. In particular two-moment gamma and three moment normal approximations are shown to approximate the sum of k independent gamma as well as generalized gamma distributions.