Statistics and Probability Commons^™

C2bat: A Novel Method For Association Between Ge- Netic Markers And Multiple Phenotypes, Melissa Naylor, Christoph Lange

Harvard University Biostatistics Working Paper Series

The purpose of this technical report is to describe a novel method developed to detect association between a genetic marker and multiple phenotypes. In order to obtain a one-degree of freedom test, a generalized principal component approach is suggested that aggregates the information about the genetic effect in the first prin- cipal component, while the remain principal components contain only environment noise. A limited simulation study is done validating the method. For scenarios in which the genetic effect is constant across all measurements and there is no envi- ronmental correlation between the measurements, preliminary results suggest that this method has …

Maximizing Network Lifetime On The Line With Adjustable Sensing Ranges, Amotz Bar-Noy, Ben Baumer

Statistical and Data Sciences: Faculty Publications

Given n sensors on a line, each of which is equipped with a unit battery charge and an adjustable sensing radius, what schedule will maximize the lifetime of a network that covers the entire line? Trivially, any reasonable algorithm is at least a 1/2-approximation, but we prove tighter bounds for several natural algorithms. We focus on developing a linear time algorithm that maximizes the expected lifetime under a random uniform model of sensor distribution. We demonstrate one such algorithm that achieves an average-case approximation ratio of almost 0.9. Most of the algorithms that we consider come from a family based …

Avoiding Boundary Estimates In Linear Mixed Models Through Weakly Informative Priors, Yeojin Chung, Sophia Rabe-Hesketh, Andrew Gelman, Jingchen Liu, Vincent Dorie

U.C. Berkeley Division of Biostatistics Working Paper Series

Variance parameters in mixed or multilevel models can be difficult to estimate, especially when the number of groups is small. We propose a maximum penalized likelihood approach which is equivalent to estimating variance parameters by their marginal posterior mode, given a weakly informative prior distribution. By choosing the prior from the gamma family with at least 1 degree of freedom, we ensure that the prior density is zero at the boundary and thus the marginal posterior mode of the group-level variance will be positive. The use of a weakly informative prior allows us to stabilize our estimates while remaining faithful …

On A Closed-Form Doubly Robust Estimator Of The Adjusted Odds Ratio For A Binary Exposure, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

Formulae For Causal Mediation Analysis In An Odds Ratio Context Without A Normality Assumption For The Continuous Mediator, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

A Cautionary Note On Specification Of The Correlation Structure In Inverse-Probability-Weighted Estimation For Repeated Measures, Eric J. Tchetgen Tchetgen, M. Maria Glymour, Jennifer Weuve, James Robins

Harvard University Biostatistics Working Paper Series

No abstract provided.

On Parametrization, Robustness And Sensitivity Analysis In A Marginal Structural Cox Proportional Hazards Model For Point Exposure, Eric J. Tchetgen Tchetgen, James M. Robins

Harvard University Biostatistics Working Paper Series

No abstract provided.

Multiple-Robust Estimation Of An Odds Ratio Interaction, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

Inverse Odds Ratio-Weighted Estimation For Causal Mediation Analysis, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

Cost-Effectiveness Of Reclassification Sampling For Prevalence Estimation, Airat Bekmetjev, Dirk Vanbruggen, Brian Mclellan, Benjamin Dewinkle, Eric Lunderberg, Nathan L. Tintle

Faculty Work Comprehensive List

Background: Typically, a two-phase (double) sampling strategy is employed when classifications are subject to error and there is a gold standard (perfect) classifier available. Two-phase sampling involves classifying the entire sample with an imperfect classifier, and a subset of the sample with the gold-standard.

Methodology/Principal Findings: In this paper we consider an alternative strategy termed reclassification sampling, which involves classifying individuals using the imperfect classifier more than one time. Estimates of sensitivity, specificity and prevalence are provided for reclassification sampling, when either one or two binary classifications of each individual using the imperfect classifier are available. Robustness of …

Effect Of Nutrition Changes On Foods Selected By Students In A Middle School-Based Diabetes Prevention Intervention Program: The Healthy Experience, Connie Mobley, Diane D. Stadler, Myrlene A. Staten, Laure El Ghormli, Bonnie Gillis, Jill Hartstein, Anna Maria Siega-Riz, Amy Virus, Healthy Study Group

GW Biostatistics Center

No abstract provided.

Repeat Prenatal Corticosteroid Prior To Preterm Birth: A Systematic Review And Individual Participant Data Meta-Analysis For The Precise Study Group (Prenatal Repeat Corticosteroid International Ipd Study Group: Assessing The Effects Using The Best Level Of Evidence) - Study Protocol, Caroline A. Crowther, Fariba Aghajafari, Lisa M. Askie, Elizabeth V. Asztalos, Peter Brocklehurst, Elizabeth A. Thom, +22 Additional Authors

GW Biostatistics Center

Background

The aim of this individual participant data (IPD) meta-analysis is to assess whether the effects of repeat prenatal corticosteroid treatment given to women at risk of preterm birth to benefit their babies are modified in a clinically meaningful way by factors related to the women or the trial protocol.

Methods/Design

The Prenatal Repeat Corticosteroid International IPD Study Group: assessing the effects using the best level of Evidence (PRECISE) Group will conduct an IPD meta-analysis. The PRECISE International Collaborative Group was formed in 2010 and data collection commenced in 2011. Eleven trials with up to 5,000 women and 6,000 infants …

Physiologic Noise Regression, Motion Regression, And Toast Dynamic Field Correction In Complex-Valued Fmri Time Series, Andrew D. Hahn, Daniel B. Rowe

Mathematics, Statistics and Computer Science Faculty Research and Publications

As more evidence is presented suggesting that the phase, as well as the magnitude, of functional MRI (fMRI) time series may contain important information and that there are theoretical drawbacks to modeling functional response in the magnitude alone, removing noise in the phase is becoming more important. Previous studies have shown that retrospective correction of noise from physiologic sources can remove significant phase variance and that dynamic main magnetic field correction and regression of estimated motion parameters also remove significant phase fluctuations. In this work, we investigate the performance of physiologic noise regression in a framework along with correction for …

Alternate Estrogen Receptors Promote Invasion Of Inflammatory Breast Cancer Cells Via Non-Genomic Signaling, Kazufumi Ohshiro, Arnold M. Schwartz, Paul H. Levine, Rakesh Kumar

Epidemiology Faculty Publications

Although Inflammatory Breast Cancer (IBC) is a rare and an aggressive type of locally advanced breast cancer with a generally worst prognosis, little work has been done in identifying the status of non-genomic signaling in the invasiveness of IBC. The present study was performed to explore the status of non-genomic signaling as affected by various estrogenic and anti-estrogenic agents in IBC cell lines SUM149 and SUM190. We have identified the presence of estrogen receptor α (ERα) variant, ERα36 in SUM149 and SUM190 cells. This variant as well as ERβ was present in a substantial concentration in IBC cells. The treatment …

Estimation Of Performance Indices For The Planning Of Sustainable Transportation Systems, Pankaj Maheshwari, Alexander Paz, Pushkin Kachroo

Graduate Publications & Presentations

What is sustainable transportation system?

Fulfill the needs of current generations without compromising the ability of future generations

Utilize resources without compromising their health and productivity Leads to development that improves quality of life

Assimilate economic, ecological, social, and bio-physical components of resource ecosystems

Minimize the use of renewable and non-renewable resources, provide affordability and equity between generations

Statistical Methods For Normalization And Analysis Of High-Throughput Genomic Data, Tobias Guennel

Theses and Dissertations

High-throughput genomic datasets obtained from microarray or sequencing studies have revolutionized the field of molecular biology over the last decade. The complexity of these new technologies also poses new challenges to statisticians to separate biological relevant information from technical noise. Two methods are introduced that address important issues with normalization of array comparative genomic hybridization (aCGH) microarrays and the analysis of RNA sequencing (RNA-Seq) studies. Many studies investigating copy number aberrations at the DNA level for cancer and genetic studies use comparative genomic hybridization (CGH) on oligo arrays. However, aCGH data often suffer from low signal to noise ratios resulting …

Model Reduction Of Linear Pde Systems: A Continuous Time Eigensystem Realization Algorithm, John R. Singler

Mathematics and Statistics Faculty Research & Creative Works

The Eigensystem Realization Algorithm (ERA) is a well known system identification and model reduction algorithm for discrete time systems. Recently, Ma, Ahuja, and Rowley (Theoret. Comput. Fluid Dyn. 25(1) : 233-247, 2011) showed that ERA is theoretically equivalent to the balanced POD algorithm for model reduction of discrete time systems. We propose an ERA for model reduction of continuous time linear partial differential equation systems. The algorithm differs from other existing approaches as it is based on a direct approximation of the Hankel integral operator of the system. We show that the algorithm produces accurate balanced reduced order models for …

Mathematical Modeling And Simulation Of Biologically Inspired Hair Receptor Arrays In Laminar Unsteady Flow Separation, John R. Singler, Belinda A. Batten, Benjamin T. Dickinson

Mathematics and Statistics Faculty Research & Creative Works

Bats possess arrays of distributed flow-sensitive hair-like mechanoreceptors on their dorsal and ventral wing surfaces. Bat wing hair receptors are known to play a significant role in flight maneuverability and are directionally most sensitive to reversed flow over the wing. in this work, we consider the mechanics of flexible hair-like structures for the time accurate detection and visualization of hydrodynamic images associated with unsteady near surface flow phenomena. a nonlinear viscoelastic model of a hair-like structure coupled to an unsteady nonuniform flow is proposed. Writing the hair model in nondimensional form, we identify five dimensionless groups that govern hair behavior. …

A Linear Energy Stable Scheme For A Thin Film Model Without Slope Selection, Wenbin Chen, Sidafa Conde, Cheng Wang, Xiaoming Wang, Steven M. Wise

Mathematics and Statistics Faculty Research & Creative Works

We present a linear numerical scheme for a model of epitaxial thin film growth without slope selection. the PDE, which is a nonlinear, fourth-order parabolic equation, is the L2 gradient flow of the energy ∫Ω(-1/2 ln(1 + |ø|2) + ε2 2 |Ø(x)|2) dx. the idea of convex-concave decomposition of the energy functional is applied, which results in a numerical scheme that is unconditionally energy stable, i.e., energy dissipative. the particular decomposition used here places the nonlinear term in the concave part of the energy, in contrast to a previous convexity splitting scheme. as a result, the numerical scheme is fully …

Productivity Formulae Of An Infinite-Conductivity Hydraulically Fractured Well Producing At Constant Wellbore Pressure Based On Numerical Solutions Of A Weakly Singular Integral Equation Of The First Kind, Chaolang Hu, Jing Lu, Xiaoming He

Mathematics and Statistics Faculty Research & Creative Works

In order to increase productivity, it is important to study the performance of a hydraulically fractured well producing at constant wellbore pressure. This paper constructs a new productivity formula, which is obtained by solving a weakly singular integral equation of the first kind, for an infinite-conductivity hydraulically fractured well producing at constant pressure. And the two key components of this paper are a weakly singular integral equation of the first kind and a steady-state productivity formula. A new midrectangle algorithm and a Galerkin method are presented in order to solve the weakly singular integral equation. The numerical results of these …