Statistics and Probability Commons^™

Toward An Mhealth Intervention For Smoking Cessation, Golam Mushih Tanimul Ahsan, Ivor D. Addo, Sheikh Iqbal Ahamed, Daniel Petereit, Shalini Kanekar, Linda Burhansstipanov, Linda U. Krebs

Mathematics, Statistics and Computer Science Faculty Research and Publications

The prevalence of tobacco dependence in the United States (US) remains alarming. Invariably, smoke-related health problems are the leading preventable causes of death in the US. Research has shown that a culturally tailored cessation counseling program can help reduce smoking and other tobacco usage. In this paper, we present a mobile health (mHealth) solution that leverages the Short Message Service (SMS) or text messaging feature of mobile devices to motivate behavior change among tobacco users. Our approach implements the Theory of Planned Behavior (TPB) and a phase-based framework. We make contributions to improving previous mHealth intervention approaches by delivering personalized …

Decoupling The Stationary Navier-Stokes-Darcy System With The Beavers-Joseph-Saffman Interface Condition, Yong Cao, Yuchuan Chu, Xiaoming He, Mingzhen Wei

Mathematics and Statistics Faculty Research & Creative Works

This paper proposes a domain decomposition method for the coupled stationary Navier-Stokes and Darcy equations with the Beavers-Joseph-Saffman interface condition in order to improve the efficiency of the finite element method. The physical interface conditions are directly utilized to construct the boundary conditions on the interface and then decouple the Navier-Stokes and Darcy equations. Newton iteration will be used to deal with the nonlinear systems. Numerical results are presented to illustrate the features of the proposed method.

Modelling Locally Changing Variance Structured Time Series Data By Using Breakpoints Bootstrap Filtering, Rajan Lamichhane

Mathematics & Statistics Theses & Dissertations

Stochastic processes have applications in many areas such as oceanography and engineering. Special classes of such processes deal with time series of sparse data. Studies in such cases focus in the analysis, construction and prediction in parametric models. Here, we assume several non-linear time series with additive noise components, and the model fitting is proposed in two stages. The first stage identifies the density using all the clusters information, without specifying any prior knowledge of the underlying distribution function of the time series. The effect of covariates is controlled by fitting the linear regression model with serially correlated errors. In …

Fast Covariance Estimation For High-Dimensional Functional Data, Luo Xiao, David Ruppert, Vadim Zipunnikov, Ciprian Crainiceanu

Johns Hopkins University, Dept. of Biostatistics Working Papers

For smoothing covariance functions, we propose two fast algorithms that scale linearly with the number of observations per function. Most available methods and software cannot smooth covariance matrices of dimension J x J with J>500; the recently introduced sandwich smoother is an exception, but it is not adapted to smooth covariance matrices of large dimensions such as J \ge 10,000. Covariance matrices of order J=10,000, and even J=100,000$ are becoming increasingly common, e.g., in 2- and 3-dimensional medical imaging and high-density wearable sensor data. We introduce two new algorithms that can handle very large covariance matrices: 1) FACE: a …

Uniformly Most Powerful Tests For Simultaneously Detecting A Treatment Effect In The Overall Population And At Least One Subpopulation, Michael Rosenblum

Johns Hopkins University, Dept. of Biostatistics Working Papers

After conducting a randomized trial, it is often of interest to determine treatment effects in the overall study population, as well as in certain subpopulations. These subpopulations could be defined by a risk factor or biomarker measured at baseline. We focus on situations where the overall population is partitioned into two predefined subpopulations. When the true average treatment effect for the overall population is positive, it logically follows that it must be positive for at least one subpopulation. We construct new multiple testing procedures that are uniformly most powerful for simultaneously rejecting the overall population null hypothesis and at least …

Soft Null Hypotheses: A Case Study Of Image Enhancement Detection In Brain Lesions, Haochang Shou, Russell T. Shinohara, Han Liu, Daniel Reich, Ciprian Crainiceanu

Johns Hopkins University, Dept. of Biostatistics Working Papers

This work is motivated by a study of a population of multiple sclerosis (MS) patients using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to identify active brain lesions. At each visit, a contrast agent is administered intravenously to a subject and a series of images is acquired to reveal the location and activity of MS lesions within the brain. Our goal is to identify and quantify lesion enhancement location at the subject level and lesion enhancement patterns at the population level. With this example, we aim to address the difficult problem of transforming a qualitative scientific null hypothesis, such as "this …

Phylogenetic Linkage Among Hiv-Infected Village Residents In Botswana: Estimation Of Clustering Rates In The Presence Of Missing Data, Nicole Bohme Carnegie, Rui Wang, Vladimir Novitsky, Victor G. Degruttola

Harvard University Biostatistics Working Paper Series

No abstract provided.

Trial Designs That Simultaneously Optimize The Population Enrolled And The Treatment Allocation Probabilities, Brandon S. Luber, Michael Rosenblum, Antoine Chambaz

Johns Hopkins University, Dept. of Biostatistics Working Papers

Standard randomized trials may have lower than desired power when the treatment effect is only strong in certain subpopulations. This may occur, for example, in populations with varying disease severities or when subpopulations carry distinct biomarkers and only those who are biomarker positive respond to treatment. To address such situations, we develop a new trial design that combines two types of preplanned rules for updating how the trial is conducted based on data accrued during the trial. The aim is a design with greater overall power and that can better determine subpopulation specific treatment effects, while maintaining strong control of …

Statistical Inference For Data Adaptive Target Parameters, Mark J. Van Der Laan, Alan E. Hubbard, Sara Kherad Pajouh

U.C. Berkeley Division of Biostatistics Working Paper Series

Consider one observes n i.i.d. copies of a random variable with a probability distribution that is known to be an element of a particular statistical model. In order to define our statistical target we partition the sample in V equal size sub-samples, and use this partitioning to define V splits in estimation-sample (one of the V subsamples) and corresponding complementary parameter-generating sample that is used to generate a target parameter. For each of the V parameter-generating samples, we apply an algorithm that maps the sample in a target parameter mapping which represent the statistical target parameter generated by that parameter-generating …

Bayesian Semi-Parametric Modeling Of Functional Data Exploration Into Major League Baseball Analytics, Jared Fisher, Dr. Gilbert Fellingham

Journal of Undergraduate Research

Most measurements follow trends over time, and those trends can be modeled. While there are many techniques for doing this, this project’s model brings a unique angle. This method can model trends with multiple peaks, from different subjects, and group them in clusters of similar curves. This permits inference on behalf of the scientist as to what is similar between subjects within a group. We have applied this algorithm to data from Major League Baseball, due to its rich nature. We hope to draw a conclusion as to who the greatest batter of all-time is, discover which players might be …

Parameter Estimation Using A Continuous, Differentiable And Asymmetric Penalized Likelihood Function, Brian Holt, Dr. Dennis Tolley

Journal of Undergraduate Research

Per the original ORCA proposal, work has been done to estimate relative amounts of compounds from GC-MS (gas chromatography-mass spectrometry) data using an asymmetric penalized likelihood function. The initial results of this project were presented at the CPMS Student Research Conference in March of this year1. The results consist of a simulation study where we simulate the problem of co-eluting, or overlapping, compounds and attempt to apply basic regression techniques as well as the asymmetric penalty function to see how they compare. Under certain conditions the new penalty function has less bias, but overall the function is unstable. There are …

Informative Retesting For Hierarchical Group Testing, Michael S. Black

Department of Statistics: Dissertations, Theses, and Student Research

Group testing is the process of pooling samples (e.g., blood, chemical compounds) from multiple sources and testing the pooled material for some binary characteristic. It is used in pathogen screening for humans and animals, drug discovery studies, electrical systems testing, and many other applications. Group testing has traditionally been used for two main types of investigations: 1) the identification of positive specimens and 2) the estimation of a characteristic’s prevalence in a population. This dissertation focuses on the identification process. We propose new identification procedures that exploit the heterogeneity among samples in order to reduce the number of tests needed …

When To Start Antiretroviral Therapy: The Need For An Evidence Base During Early Hiv Infection, James D. Lundgren, Abdel G. Babiker, Fred M. Gordin, Alvaro H. Borges, James D. Neaton

Epidemiology Faculty Publications

Background

Strategies for use of antiretroviral therapy (ART) have traditionally focused on providing treatment to persons who stand to benefit immediately from initiating the therapy. There is global consensus that any HIV+ person with CD4 counts less than 350 cells/μl should initiate ART. However, it remains controversial whether ART is indicated in asymptomatic HIV-infected persons with CD4 counts above 350 cells/μl, or whether it is more advisable to defer initiation until the CD4 count has dropped to 350 cells/μl. The question of when the best time is to initiate ART during early HIV infection has always been vigorously debated. The …

Association Between Adverse Childhood Experiences And Diagnosis Of Cancer, Monique J. Brown, Leroy R. Thacker, Steven A. Cohen

Faculty Publications

Objective: Adverse childhood experiences (ACEs) are linked to multiple adverse health outcomes. This study examined the association between ACEs and cancer diagnosis.

Methods: Data from the 2010 Behavioral Risk Factor Surveillance System (BRFSS) survey were used. The BRFSS is the largest ongoing telephone health survey, conducted in all US states, the District of Columbia, Puerto Rico, Guam and the U.S. Virgin Islands, and provides data on a variety of health issues among the non-institutionalized adult population. Principal component analysis (PCA) was used to derive components for ACEs. Multivariable logistic regression models were used to provide adjusted odds ratios (OR) and …

Death Certificate Completion Skills Of Hospital Physicians In A Developing Country, Ahmed Suleman Haque, Kanza Shamim, Najm Hasan Siddiqui, Muhammad Irfan, Javaid Ahmed Khan

Section of Pulmonary & Critical Care

Background

Death certificates (DC) can provide valuable health status data regarding disease incidence, prevalence and mortality in a community. It can guide local health policy and help in setting priorities. Incomplete and inaccurate DC data, on the other hand, can significantly impair the precision of a national health information database. In this study we evaluated the accuracy of death certificates at a tertiary care teaching hospital in a Karachi, Pakistan.

Methods

A retrospective study conducted at Aga Khan University Hospital, Karachi, Pakistan for a period of six months. Medical records and death certificates of all patients who died under adult …

Restricted Likelihood Ratio Tests For Functional Effects In The Functional Linear Model, Bruce J. Swihart, Jeff Goldsmith, Ciprian M. Crainiceanu

Johns Hopkins University, Dept. of Biostatistics Working Papers

The goal of our article is to provide a transparent, robust, and computationally feasible statistical approach for testing in the context of scalar-on-function linear regression models. In particular, we are interested in testing for the necessity of functional effects against standard linear models. Our methods are motivated by and applied to a large longitudinal study involving diffusion tensor imaging of intracranial white matter tracts in a susceptible cohort. In the context of this study, we conduct hypothesis tests that are motivated by anatomical knowledge and which support recent findings regarding the relationship between cognitive impairment and white matter demyelination. R-code …

Emirical Assessment Of The Future Performance Of The S&P 500 Losers, Nicholas Powers

Statistics

In the Wall Street Journal in early 2013, there was an article posted by Andrew Bary that explored a trend in the previous 3 years of the S&P 500. The article pointed out that the average returns for the top 10 percentage decliners for 2009, 2010, and 2011 outperformed the S&P 500 for the first two weeks of the next year. These top 10 percentage decliners or losers well enough to bet on. This study looks to see if there is statistical evidence that the losers outperformed the S&P 500.

Process Characterization Using Response Surface Methodology, Katherine A. Eng

Statistics

A local engineering firm proposed a joint collaboration with the Cal Poly Statistics Department to investigate the sources of variability in a certain measurement process, understand normal operability characteristics of the machine, reduce variability in machine measurements, establish process monitoring and control for the system, and verify utility of the proposed process control through designed experimentation. This senior project entailed designed experimentation and analysis using response surface methodology to better understand the normal operability characteristics of the machine. Further experimentation and analysis is necessary to devise, implement, and verify statistical process control measures.

Pedestrian Detection Using Image Blending, Hannah Haggerty

Statistics

No abstract provided.

Examining Introductory Students’ Attitudes In A Randomization-Based Curriculum, Joshua Ryan Beemer

Statistics

Student attitudes regarding introductory statistics courses are not always the most positive. The purpose of this research is to utilize the Survey of Attitudes Toward Statistics to evaluate introductory statistics students’ attitudes pre- and post course. Furthermore, comparisons of attitudes within different introductory course curricula across institutions will be made. Various components within the survey, such as difficulty, value, and interest, will be assessed in order to determine where students’ attitudes are affected the most and how they are correlated with other variables such as current GPA and curriculum taught. The outcomes for these models look at demographic predictors that …