Statistics and Probability Commons^™

Non-Invasive Prenatal Detection Of Trisomy 21 Using Tandem Single Nucleotide Polymorphisms, Sujana Ghanta, Michael Mitchell, Mary Ames, Mats Hidestrand, Pippa Simpson, Mary Goetsch, William Thilly, Craig Struble, Aoy Tomita-Mitchell

Mathematics, Statistics and Computer Science Faculty Research and Publications

Background: Screening tests for Trisomy 21 (T21), also known as Down syndrome, are routinely performed for the majority of pregnant women. However, current tests rely on either evaluating non-specific markers, which lead to false negative and false positive results, or on invasive tests, which while highly accurate, are expensive and carry a risk of fetal loss. We outline a novel, rapid, highly sensitive, and targeted approach to non-invasively detect fetal T21 using maternal plasma DNA.

Methods and Findings: Highly heterozygous tandem Single Nucleotide Polymorphism (SNP) sequences on chromosome 21 were analyzed using High-Fidelity PCR and Cycling Temperature Capillary …

Population Value Decomposition, A Framework For The Analysis Of Image Populations, Ciprian M. Crainiceanu, Brian S. Caffo, Sheng Luo, Vadim Zipunnikov

Johns Hopkins University, Dept. of Biostatistics Working Papers

Images, often stored in multidimensional arrays are fast becoming ubiquitous in medical and public health research. Analyzing populations of images is a statistical problem that raises a host of daunting challenges. The most severe challenge is that data sets incorporating images recorded for hundreds or thousands of subjects at multiple visits are massive. We introduce the population value decomposition (PVD), a general method for simultaneous dimensionality reduction of large populations of massive images. We show how PVD can seamlessly be incorporated into statistical modeling and lead to a new, transparent and fast inferential framework. Our methodology was motivated by and …

Multilevel Functional Principal Component Analysis For High-Dimensional Data, Vadim Zipunnikov, Brian Caffo, Ciprian Crainiceanu, David M. Yousem, Christos Davatzikos, Brian S. Schwartz

Johns Hopkins University, Dept. of Biostatistics Working Papers

We propose fast and scalable statistical methods for the analysis of hundreds or thousands of high dimensional vectors observed at multiple visits. The proposed inferential methods avoid the difficult task of loading the entire data set at once in the computer memory and use sequential access to data. This allows deployment of our methodology on low-resource computers where computations can be done in minutes on extremely large data sets. Our methods are motivated by and applied to a study where hundreds of subjects were scanned using Magnetic Resonance Imaging (MRI) at two visits roughly five years apart. The original data …

Student Fact Book, Fall 2010, Thirty-Fourth Annual Edition, Wright State University, Office Of Student Information Systems, Wright State University

Wright State University Student Fact Books

The student fact book has general demographic information on all students enrolled at Wright State University for Fall Quarter, 2010.

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.

Analysis Of Nonlinear Spectral Eddy-Viscosity Models Of Turbulence, Max Gunzburger, Eunjung Lee, Yuki Saka, Catalin Trenchea, Xiaoming Wang

Mathematics and Statistics Faculty Research & Creative Works

Fluid turbulence is commonly modeled by the Navier-Stokes equations with a large Reynolds number. However, direct numerical simulations are not possible in practice, so that turbulence modeling is introduced. We study artificial spectral viscosity models that render the simulation of turbulence tractable. We show that the models are well posed and have solutions that converge, in certain parameter limits, to solutions of the Navier-Stokes equations. We also show, using the mathematical analyses, how effective choices for the parameters appearing in the models can be made. Finally, we consider temporal discretizations of the models and investigate their stability. © 2009 Springer …

On Nonparametric Comparison Of Images And Regression Surfaces, Xiao-Feng Wang, Deping Ye

Xiaofeng Wang

Multivariate local regression is an important tool for image processing and analysis. In many practical biomedical problems, one is often interested in comparing a group of images or regression surfaces. In this paper, we extend the existing method of testing the equality of nonparametric curves by Dette and Neumeyer (2001) and consider a test statistic by means of an L2-distance in the multi-dimensional case under a completely heteroscedastic nonparametric model. The test statistic is also extended to be used in the case of spatial correlated errors. Two bootstrap procedures are described in order to approximate the critical values of the …

Application Of The Fractional Diffusion Equation For Predicting Market Behaviour, Jonathan Blackledge

Articles

Most Financial modelling system rely on an underlying hypothesis known as the Eficient Market Hypothesi (EMH) including the famous BlackScholes formula for placing an option. However, the EMH has a fundamental flaw: it is based on the assumption that economic processes are normally distributed and it has long been known that this is not the case. This fundamental assumption leads to a number of shortcomings associated with using the EMH to analyse financial data which includes failure to predict the future volatility of a market share value. This paper introduces a new financial risk assessment model based on Levy statistics …

The Pathways To Mental Health Care Of First-Episode Psychosis Patients: A Systematic Review., Kelly K. Anderson, Rebecca Fuhrer, Ashok K. Malla

Epidemiology and Biostatistics Publications

BACKGROUND: Although there is agreement on the association between delay in treatment of psychosis and outcome, less is known regarding the pathways to care of patients suffering from a first psychotic episode. Pathways are complex, involve a diverse range of contacts, and are likely to influence delay in treatment. We conducted a systematic review on the nature and determinants of the pathway to care of patients experiencing a first psychotic episode.

METHOD: We searched four databases (Medline, HealthStar, EMBASE, PsycINFO) to identify articles published between 1985 and 2009. We manually searched reference lists and relevant journals and used forward citation …

Targeted Bayesian Learning, Ivan Diaz Munoz, Alan E. Hubbard, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Targeted maximum likelihood estimation (van der Laan & Rubin 2006) is a loss-based semi-parametric estimation method that yields a substitution estimator of a target parameter of the probability distribution of the data that solves the efficient influence curve estimating equation, and thereby yields a double robust locally efficient estimator of the parameter of interest, under regularity conditions. The Bayesian paradigm is concerned with including the researcher’s prior uncertainty about the parameter through a prior distribution, which combined with the likelihood yields a posterior distribution for the parameter that reflects the researcher’s posterior uncertainty. In this paper, we present a way …

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.

Fast, Flexible Function-On-Scalar Regression, With An Application To Brain Development, Philip T. Reiss, Lei Huang

Philip T. Reiss

No abstract provided.

Estimating Temporal Associations In Electrocorticographic (Ecog) Time Series With First Order Pruning, Haley Hedlin, Dana Boatman, Brian Caffo

Johns Hopkins University, Dept. of Biostatistics Working Papers

Granger causality (GC) is a statistical technique used to estimate temporal associations in multivariate time series. Many applications and extensions of GC have been proposed since its formulation by Granger in 1969. Here we control for potentially mediating or confounding associations between time series in the context of event-related electrocorticographic (ECoG) time series. A pruning approach to remove spurious connections and simultaneously reduce the required number of estimations to fit the effective connectivity graph is proposed. Additionally, we consider the potential of adjusted GC applied to independent components as a method to explore temporal relationships between underlying source signals. Both …

Journal Usage By Subject For Fiscal Year 2010, Michael A. Cerbo Ii

Technical Services Reports and Statistics

Journal holdings for the University Libraries are listed alphabetically by subject than authority title. Usage statistics for the fiscal year are included along with a cost per use where available. The information is taken from each vendor and incorporated in Serials Solutions 360 Counter.

Landmark Prediction Of Survival, Layla Parast, Tianxi Cai

Harvard University Biostatistics Working Paper Series

No abstract provided.

Weakly Positioned Nucleosomes Enhance The Transcriptional Competency Of Chromatin, Yaakov Belch, Jingyi Yang, Yang Liu, Sridhar A. Malkaram, Rong Liu, Jean-Jack M. Riethoven, Istvan Ladunga

Department of Statistics: Faculty Publications

Background: Transcription is affected by nucleosomal resistance against polymerase passage. In turn, nucleosomal resistance is determined by DNA sequence, histone chaperones and remodeling enzymes. The contributions of these factors are widely debated: one recent title claims ‘‘… DNA-encoded nucleosome organization…’’ while another title states that ‘‘histone-DNA interactions are not the major determinant of nucleosome positions.’’ These opposing conclusions were drawn from similar experiments analyzed by idealized methods. We attempt to resolve this controversy to reveal nucleosomal competency for transcription.

Methodology/Principal Findings: To this end, we analyzed 26 in vivo, nonlinked, and in vitro genome-wide nucleosome maps/replicates by new, rigorous …

Diagnosing And Responding To Violations In The Positivity Assumption, Maya L. Petersen, Kristin Porter, Susan Gruber, Yue Wang, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

The assumption of positivity or experimental treatment assignment requires that observed treatment levels vary within confounder strata. This article discusses the positivity assumption in the context of assessing model and parameter-specific identifiability of causal effects. Positivity violations occur when certain subgroups in a sample rarely or never receive some treatments of interest. The resulting sparsity in the data may increase bias with or without an increase in variance and can threaten valid inference. The parametric bootstrap is presented as a tool to assess the severity of such threats and its utility as a diagnostic is explored using simulated data. Several …

Application Of Convex Methods To Identification Of Fuzzy Subpopulations, Ryan Lee Eliason

Theses and Dissertations

In large observational studies, data are often highly multivariate with many discrete and continuous variables measured on each observational unit. One often derives subpopulations to facilitate analysis. Traditional approaches suggest modeling such subpopulations with a compilation of interaction effects. However, when many interaction effects define each subpopulation, it becomes easier to model membership in a subpopulation rather than numerous interactions. In many cases, subjects are not complete members of a subpopulation but rather partial members of multiple subpopulations. Grade of Membership scores preserve the integrity of this partial membership. By generalizing an analytic chemistry concept related to chromatography-mass spectrometry, we …

Statistical Image Recovery From Laser Speckle Patterns With Polarization Diversity, Donald B. Dixon

Theses and Dissertations

This research extends the theory and understanding of the laser speckle imaging technique. This non-traditional imaging technique may be employed to improve space situational awareness and image deep space objects from a ground-based sensor system. The use of this technique is motivated by the ability to overcome aperture size limitations and the distortion effects from Earth’s atmosphere. Laser speckle imaging is a lensless, coherent method for forming two-dimensional images from their autocorrelation functions. Phase retrieval from autocorrelation data is an ill-posed problem where multiple solutions exist. This research introduces polarization diversity as a method for obtaining additional information so the …

Longitudinal Penalized Functional Regression, Jeff Goldsmith, Ciprian M. Crainiceanu, Brian Caffo, Daniel Reich

Johns Hopkins University, Dept. of Biostatistics Working Papers

We propose a new regression model and inferential tools for the case when both the outcome and the functional exposures are observed at multiple visits. This data structure is new but increasingly present in applications where functions or images are recorded at multiple times. This raises new inferential challenges that cannot be addressed with current methods and software. Our proposed model generalizes the Generalized Linear Mixed Effects Model (GLMM) by adding functional predictors. Smoothness of the functional coefficients is ensured using roughness penalties estimated by Restricted Maximum Likelihood (REML) in a corresponding mixed effects model. This method is computationally feasible …

On Two-Stage Hypothesis Testing Procedures Via Asymptotically Independent Statistics, James Dai, Charles Kooperberg, Michael L. Leblanc, Ross Prentice

UW Biostatistics Working Paper Series

Kooperberg and LeBlanc (2008) proposed a two-stage testing procedure to screen for significant interactions in genome-wide association (GWA) studies by a soft threshold on marginal associations (MA), though its theoretical properties and generalization have not been elaborated. In this article, we discuss conditions that are required to achieve strong control of the Family-Wise Error Rate (FWER) by such procedures for low or high-dimensional hypothesis testing. We provide proof of asymptotic independence of marginal association statistics and interaction statistics in linear regression, logistic regression, and Cox proportional hazard models in a randomized clinical trial (RCT) with a rare event. In case-control …

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.

Sample Size And Statistical Power Considerations In High-Dimensionality Data Settings: A Comparative Study Of Classification Algorithms, Yu Guo, Armin Garber, Raji Balasubramanian

Raji Balasubramanian

Background: Data generated using ‘omics’ technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of subjects in the study. In this paper, we consider issues relevant in the design of biomedical studies in which the goal is the discovery of a subset of features and an associated algorithm that can predict a binary outcome, such as disease status. We compare the performance of four commonly used classifiers (K-Nearest Neighbors, Prediction Analysis for Microarrays, Random Forests and Support Vector Machines) in high-dimensionality data settings. We evaluate the effects of varying levels of …

Geometry Of Satake And Toroidal Compactifications, Patrick Michael Boland

Open Access Dissertations

In [JM02, section 14], Ji and MacPherson give new constructions of the Borel--Serre and reductive Borel--Serre compactifications [BS73, Zuc82] of a locally symmetric space. They use equivalence classes of eventually distance minimizing (EDM) rays to describe the boundaries of these compactications. The primary goal of this thesis is to construct the Satake compactifications of a locally symmetric space [Sat60a] using finer equivalence relations on EDM rays. To do this, we first construct the Satake compactifications of the global symmetric space [Sat60b] with equivalence classes of geodesics in the symmetric space. We then define equivalence relations on EDM rays using geometric …

A Hierarchical Spherical Radial Quadrature Algorithm For Multilevel Glmms, Gsmms, And Gene Pathway Analysis, Jacob A. Gagnon

Open Access Dissertations

The first part of my thesis is concerned with estimation for longitudinal data using generalized semi-parametric mixed models and multilevel generalized linear mixed models for a binary response. Likelihood based inferences are hindered by the lack of a closed form representation. Consequently, various integration approaches have been proposed. We propose a spherical radial integration based approach that takes advantage of the hierarchical structure of the data, which we call the 2 SR method. Compared to Pinheiro and Chao's multilevel Adaptive Gaussian quadrature, our proposed method has an improved time complexity with the number of functional evaluations scaling linearly in the …

Roger Temam On The Occasion Of His 70th Birthday, Claude Michel Brauner, Danielle Hilhorst, Alain Miranville, Shouhong Wang, Xiaoming Wang

Mathematics and Statistics Faculty Research & Creative Works

No abstract provided.

Health Benefits Of Increased Walking For Sedentary, Generally Healthy Older Adults: Using Longitudinal Data To Approximate An Intervention Trial, Paula Diehr

Paula Diehr

BACKGROUND: Older adults are often advised to walk more, but randomized trials have not conclusively established the benefits of walking in this age group. Typical analyses based on observational data may have biased results. Here, we propose a "limited-bias," more interpretable estimate of the health benefits to sedentary healthy older adults of walking more, using longitudinal data from the Cardiovascular Health Study. METHODS: The number of city blocks walked per week, collected annually, was classified as sedentary (<7 blocks per>week), somewhat active, or active (>or=28). Analysis was restricted to persons sedentary and healthy in the first 2 years. In Year …

Facial Type Analysis Comparison Between Mri, Cbct, And Lateral Cephalometrics, Matthew A. Sanders

Loma Linda University Electronic Theses, Dissertations & Projects

Introduction: Single Cephalometric measurements are comparable between Cone Beam Computed Tomography (CBCT), Magnetic Resonance Imaging (MRl) and Conventional Lateral Cephalometric (LC) imaging methods. This study evaluated the agreement between the three imaging methods in facial type analysis (using a composite of 5 cephalometric measures).

Methods and Materials: Twenty-two subjects participated in this study. Cranial images were generated via three modalities: LC, CBCT and MRl. Cephalometric landmarks were identified on the three images per subject and a facial type analysis performed. An equally weighted facial type calculation composed of 5 cephalometric measurements (facial axis, facial depth, mandibular plane, lower face height, …

Psychological Profiles In A Female Bariatric Surgery Sample, Aimee L. Donato

Loma Linda University Electronic Theses, Dissertations & Projects

Morbid obesity is an epidemic. Current literature suggests that people with morbid obesity tend to show increased levels of psychological dysfunction. This is especially pertinent to the clinicians who work with morbidly obese patients who seek bariatric surgery as the method for weight control. Surgery should be performed on patients who are psychologically ready to adjust to the stringent post-operative lifestyle.

The purpose of the present study was (1) to compare two groups of bariatric patients (a White group and a non-White group) on pre-surgery measures: specific scales on the Millon Behavioral Medicine Diagnostic (MBMD), the Beck Depression Inventory II …

Macroevolutionary Patterns In The Evolutionary Radiation Of Archosaurs (Tetrapoda: Diapsida), S. L. Brusatte, M. J. Benton, G. T. Lloyd, M. Ruta, Steve C. Wang

Mathematics & Statistics Faculty Works

The rise of archosaurs during the Triassic and Early Jurassic has been treated as a classic example of an evolutionary radiation in the fossil record. This paper reviews published studies and provides new data on archosaur lineage origination, diversity and lineage evolution, morphological disparity, rates of morphological character change, and faunal abundance during the Triassic–Early Jurassic. The fundamental archosaur lineages originated early in the Triassic, in concert with the highest rates of character change. Disparity and diversity peaked later, during the Norian, but the most significant increase in disparity occurred before maximum diversity. Archosaurs were rare components of Early–Middle Triassic …