Statistics and Probability Commons^™

Application Of Inter-Die Rank Statistics In Defect Detection, Vivek Bakshi

Dissertations and Theses

This thesis presents a statistical method to identify the test escapes. Test often acquires parametric measurements as a function of logical state of a chip. The usual method of classifying chips as pass or fail is to compare each state measurement to a test limit. Subtle manufacturing defects are escaping the test limits due to process variations in deep sub-micron technologies which results in mixing of healthy and faulty parametric test measurements. This thesis identifies the chips with subtle defects by using rank order of the parametric measurements. A hypothesis is developed that a defect is likely to disturb the …

On A Logistic Mixed Model Formulation Of A Quadratic Exponential Model For Correlated Binary Outcomes, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

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 …

Almost Oscillatory Three Dimensional Dynamic Systems, Elvan Akin, Zuzana Dosla, Bonita Lawrence

Mathematics and Statistics Faculty Research & Creative Works

In this article, we investigate oscillation and asymptotic properties for 3D systems of dynamic equations. We show the role of nonlinearities and we apply our results to the adjoint dynamic systems.

Toward A Regional Radiocarbon Model For The East Texas Woodland Period, Robert Z. Selden Jr., Timothy K. Perttula

CRHR: Archaeology

The East Texas Radiocarbon Database contributes to an analysis of tempo and place for Woodland era (ca. 500 B.C. - A.D. 800) archaeological sites within the region. The temporal and spatial distributions of calibrated radiocarbon (¹⁴C) ages (n=127) with a standard deviation (ΔT) of 61 from archaeological sites with Woodland components (n=51) are useful in exploring the development and geographical continuity of the peoples in East Texas, and lead to a refinement of our current chronological understanding of the period. While the analysis of the dates produces less than significant findings due to sample size, they are used …

Modeling Regional Radicarbon Trends: A Case Study From The East Texas Woodland Period, Robert Z. Selden Jr.

CRHR: Archaeology

The East Texas Radiocarbon Database contributes to an analysis of tempo and place for Woodland era (~500 BC–AD 800) archaeological sites within the region. The temporal and spatial distributions of calibrated ¹⁴C ages (n = 127) with a standard deviation (ΔT) of 61 from archaeological sites with Woodland components (n = 51) are useful in exploring the development and geographical continuity of the peoples in east Texas, and lead to a refinement of our current chronological understanding of the period. While analysis of summed probability distributions (SPDs) produces less than significant findings due to sample size, they are used …

The East Texas Caddo: Modeling Tempo And Place, Robert Z. Selden Jr., Timothy K. Perttula

CRHR: Archaeology

Analysis of the Caddo sample (n=889 dates) from the East Texas radiocarbon database is used to establish the tempo and place of Caddo era (ca. A.D. 800-1680) archaeological sites, site clusters, and communities across the region. The temporal and spatial distribution of radiocarbon ages from settlements, mound centers, and cemeteries across the region have utility in exploring the development and geographical continuity of the Caddo peoples; establishing the specific times when areas were abandoned or population sizes diminished; and defining times and areas illustrating an intensification in mound center construction and large cemeteries became a focus of community social practices.

Planned Missingness Study Design: Two Methods To Developing The Study Survey Versions, E. Whitney G. Moore

Kinesiology, Health and Sport Studies

A planned missingness data study design takes advantage of modern techniques for handling data missingness that is MCAR (Missing Completely at Random) and MAR (Missing at Random) (Brown, 2006; Enders, 2010). As modern data imputation techniques have improved, this study design option has become a powerful, cost-effective option for collecting the most data across the largest sample possible, while keeping the fatigue effect and expense of the study minimized (Little, 2010a, 2010b, 2012). The purpose of this guide is to provide an applied example for designing the surveys necessary when conducting a planned missingness research study design.

A Systematic Selection Method For The Development Of Cancer Staging Systems, Yunzhi Lin, Richard Chappell, Mithat Gonen

Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series

The tumor-node-metastasis (TNM) staging system has been the anchor of cancer diagnosis, treatment, and prognosis for many years. For meaningful clinical use, an orderly, progressive condensation of the T and N categories into an overall staging system needs to be defined, usually with respect to a time-to-event outcome. This can be considered as a cutpoint selection problem for a censored response partitioned with respect to two ordered categorical covariates and their interaction. The aim is to select the best grouping of the TN categories. A novel bootstrap cutpoint/model selection method is proposed for this task by maximizing bootstrap estimates of …

On Identification Of Natural Direct Effects When A Confounder Of The Mediator Is Directly Affected By Exposure, Eric J. Tchetgen Tchetgen, Tyler J. Vanderweele

Harvard University Biostatistics Working Paper Series

No abstract provided.

A Study Of The Gam Approach To Solve Laminar Boundary Layer Equations In The Presence Of A Wedge, Rahmat Ali Khan, Muhammad Usman

Mathematics Faculty Publications

We apply an easy and simple technique, the generalized ap- proximation method (GAM) to investigate the temperature field associated with the Falkner-Skan boundary-layer problem. The nonlinear partial differ- ential equations are transformed to nonlinear ordinary differential equations using the similarity transformations. An iterative scheme for the non-linear ordinary differential equations associated with the velocity and temperature profiles are developed via GAM. Numerical results for the dimensionless ve- locity and temperature profiles of the wedge flow are presented graphically for different values of the wedge angle and Prandtl number.