Statistics and Probability Commons^™

Causal Mediation In A Survival Setting With Time-Dependent Mediators, Wenjing Zheng, Mark J. Van Der Laan

Wenjing Zheng

The effect of an expsore on an outcome of interest is often mediated by intermediate variables. The goal of causal mediation analysis is to evaluate the role of these intermediate variables (mediators) in the causal effect of the exposure on the outcome. In this paper, we consider causal mediation of a baseline exposure on a survival (or time-to-event) outcome, when the mediator is time-dependent. The challenge in this setting lies in that the event process takes places jointly with the mediator process; in particular, the length of the mediator history depends on the survival time. As a result, we argue …

Targeted Maximum Likelihood Estimation Of Natural Direct Effect, Wenjing Zheng, Mark Van Der Laan

Wenjing Zheng

In many causal inference problems, one is interested in the direct causal effect of an exposure on an outcome of interest that is not mediated by certain intermediate variables. Robins and Greenland (1992) and Pearl (2000) formalized the definition of two types of direct effects (natural and controlled) under the counterfactual framework. Since then, identifiability conditions for these effects have been studied extensively. By contrast, considerably fewer efforts have been invested in the estimation problem of the natural direct effect. In this article, we propose a semiparametric efficient, multiply robust estimator for the natural direct effect of a binary treatment …

Statistical Models For Predicting College Success, Yelen Nunez

Yelen Nunez

Colleges base their admission decisions on a number of factors to determine which applicants have the potential to succeed. This study utilized data for students that graduated from Florida International University between 2006 and 2012. Two models were developed (one using SAT as the principal explanatory variable and the other using ACT as the principal explanatory variable) to predict college success, measured using the student’s college grade point average at graduation. Some of the other factors that were used to make these predictions were high school performance, socioeconomic status, major, gender, and ethnicity. The model using ACT had a higher …

Create A Simple Predictive Analytics Classification Model In Java With Weka, James Howard

James Howard

Get an overview of the Weka classification engine and learn how to create a simple classifier for programmatic use. Understand how to store and load models, manipulate them, and use them to evaluate data. Consider applications and implementation strategies suitable for the enterprise environment so you turn a collection of training data into a functioning model for real- time prediction.

Hierarchical Vector Auto-Regressive Models And Their Applications To Multi-Subject Effective Connectivity, Cristina Gorrostieta, Mark Fiecas, Hernando Ombao, Erin Burke, Steven Cramer

Mark Fiecas

Integrative Analysis Of High-Throughput Cancer Studies With Contrasted Penalization, Shuangge Ma

Shuangge Ma

In cancer studies with high-throughput genetic and genomic measurements, integrative analysis provides a way to effectively pool and analyze heterogeneous raw data from multiple independent studies and outperforms ``classic" meta-analysis and single-dataset analysis. When marker selection is of interest, the genetic basis of multiple datasets can be described using the homogeneity model or the heterogeneity model. In this study, we consider marker selection under the heterogeneity model, which includes the homogeneity model as a special case and can be more flexible. Penalization methods have been developed in the literature for marker selection. This study advances from the published ones by …

Counting The Impossible: Sampling And Modeling To Achieve A Large State Homeless Count, Jennifer L. Priestley, Jane Massey

Jennifer L. Priestley

Objective: Using inferential statistics, we develop estimates of the homeless population of a geographically large and economically diverse state -- Georgia.

Methods: Multiple independent data sources (2000 U.S. Census, the 2006 Georgia County Guide, Georgia Chamber of Commerce) were used to develop Clusters of the 150 Georgia Counties. These clusters were used as "strata" to then execute traified sampling. Homeless counts were conducted within the sample counties, allowing for multiple regression models to be developed to generate predictions of homeless persons by county.

Results: In response to a mandate from the US Department of Housing and Urban Development, the State …

Multi-Organizational Networks: Three Antecedents Of Knowledge Transfer, Jennifer L. Priestley, Subhashish Samaddar

Jennifer L. Priestley

Researchers have demonstrated that organizations operating within formal networks are more likely to experience knowledge transfer, and the associated benefits of knowledge transfer, than would organizations operating outside of a network. However, limited research attention has been given to how the established antecedents of knowledge transfer are affected by the different forms that multi-organizational networks can assume. Using two case studies, we develop six testable propositions regarding how three of the established antecedents of knowledge transfer —absorptive capacity, shared identity and causal ambiguity—would be affected by the different characteristics, which define multi-organizational network form. We discuss these propositions and raise …

Active Presecription Drug Safety Surveillance: Exploring Omop 2011-2012 Experiments, Susan Gruber, James M. Robins

Susan Gruber

The Observational Medical Outcomes Partnership (OMOP), a consortium of pharmaceutical, FDA, and academic researchers focuses on developing and evaluating electronic records-based methods for enhancing post-market drug safety surveillance. The OMOP 2011-2012 experiment consists of applying variants of seven analysis methods to five different EMR or claims databases to estimate the increase (decrease) in risk associated with drug-outcome pairs whose causal association has been previously established, and serves as a gold standard for comparison. Variants of each method can produce very different effect estimates, sometimes at odds with the gold standard. We explore the reasons behind this heterogeneity, and in doing …

Critical Assessment Of Outcomes In Acute Aortic Dissection (Type A) At A Community Hospital: A 10 Year Review, Tim S. Misselbeck Md, James K. Wu Md, Stephen Deturk Ba, Michael F. Szwerc Md, Sanjay M. Mehta Md, Theodore G. Phillips Md, Gary W. Szydlowski Md, Raymond L. Singer Md

James K. Wu, M.D.

No abstract provided.

Conventional Isolated Aortic Valve Replacement In Octogenarians: A 10-Year Single Center Experience, James K. Wu Md, Justin D. Roberts Do, Gregory S. Troutman Bs, Michael J. Weiss Mph, Sanjay M. Mehta Md, Theodore G. Phillips Md, Michael F. Szwerc Md, Gary W. Szydlowski Md, Tim S. Misselbeck Md, Raymond L. Singer Md

James K. Wu, M.D.

No abstract provided.

Critical Assessment Of Outcomes In Acute Aortic Dissection (Type A) At A Community Hospital: A 10 Year Review, Tim S. Misselbeck Md, James K. Wu Md, Stephen Deturk Ba, Michael F. Szwerc Md, Sanjay M. Mehta Md, Theodore G. Phillips Md, Gary W. Szydlowski Md, Raymond L. Singer Md

James K Wu MD

No abstract provided.

Conventional Isolated Aortic Valve Replacement In Octogenarians: A 10-Year Single Center Experience, James K. Wu Md, Justin D. Roberts Do, Gregory S. Troutman Bs, Michael J. Weiss Mph, Sanjay M. Mehta Md, Theodore G. Phillips Md, Michael F. Szwerc Md, Gary W. Szydlowski Md, Tim S. Misselbeck Md, Raymond L. Singer Md

James K Wu MD

No abstract provided.

Causes Of Death In Surgically Treated Patients With Type A Aortic Dissection - A Ten Year Review, James K. Wu Md, Eilizabeth Depaolo Bs, Theodore G. Phillips Md, Tim S. Misselbeck Md

James K. Wu, M.D.

No abstract provided.

Bayesian Analysis Of Hypothesis Testing Problems For General Population: A Kullback–Leibler Alternative, Naveen Bansal, Gholamhossein Hamedani, Ru Sheng

Naveen Bansal

We consider a hypothesis problem with directional alternatives. We approach the problem from a Bayesian decision theoretic point of view and consider a situation when one side of the alternatives is more important or more probable than the other. We develop a general Bayesian framework by specifying a mixture prior structure and a loss function related to the Kullback–Leibler divergence. This Bayesian decision method is applied to Normal and Poisson populations. Simulations are performed to compare the performance of the proposed method with that of a method based on a classical z-test and a Bayesian method based on the …

Creating Composite Age Groups To Smooth Percentile Rank Distributions Of Small Samples, Francesca Lopez, Amy Olson, Naveen Bansal

Naveen Bansal

Individually administered tests are often normed on small samples, a process that may result in irregularities within and across various age or grade distributions. Test users often smooth distributions guided by Thurstone assumptions (normality and linearity) to result in norms that adhere to assumptions made about how the data should look. Test users, however, may come across particular tests or sets of data in which the Thurstone assumptions are untenable. When users expect deviations from normality within age or grade, an alternate method is desirable. The authors present a relatively simple procedure that allows the user to treat observed raw …

Designing The Search Trial: Ph250b In Practice, Laura Balzer

Laura B. Balzer

No abstract provided.

Towards Real-Time, On-Board, Hardware-Supported Sensor And Software Health Management For Unmanned Aerial Systems, Johann Schumann, Kristin Y. Rozier, Thomas Reinbacher, Ole J. Mengshoel, Timmy Mbaya, Corey Ippolito

Ole J Mengshoel

On Covariance Structure In Noisy, Big Data, Randy Paffenroth, Ryan Nong, Philip Du Toit

Randy C. Paffenroth

Herein we describe theory and algorithms for detecting covariance structures in large, noisy data sets. Our work uses ideas from matrix completion and robust principal component analysis to detect the presence of low-rank covariance matrices, even when the data is noisy, distorted by large corruptions, and only partially observed. In fact, the ability to handle partial observations combined with ideas from randomized algorithms for matrix decomposition enables us to produce asymptotically fast algorithms. Herein we will provide numerical demonstrations of the methods and their convergence properties. While such methods have applicability to many problems, including mathematical finance, crime analysis, and …

The Challenge Of Early Inpatient Postpartum Depression Screening, Elizabeth A. Berger Do, John C. Smulian Md, Mph, Joanne Quiñones Md, Msce, Rory L. Marraccini Md, Amy Wu Bs, Elizabeth A. Smulian Bs, Sandra L. Curet Md

John C Smulian MD, MPH

No abstract provided.

Participation In Perinatal Interventional Research: Which Characteristics Matter?, Hai-Yen T. Nguyen Md, Joanne Quiñones Md, Msce, Daniel G. Kiefer Md, Anita Kurt Phd, Rn, Felisa Saldutti, John C. Smulian Md, Mph

John C Smulian MD, MPH

No abstract provided.

Reference Interval Studies: What Is The Maximum Number Of Samples Recommended?, Robert Hawkins, Tony Badrick

Tony Badrick

Background: Little attention has been paid to the maximum number of specimens for reference interval calculation, i.e., the number of specimens beyond which there is no further benefit in reference interval calculation. We present a model for the estimation of the maximum number of specimens for reference interval studies based on setting the 90% confidence interval of the reference limits to be equal to the analyte reporting interval. Methods: Equations describing the bounds on the upper and lower 90% confidence intervals for logarithmically transformed and untransformed data were derived and applied to determine the maximum number of specimens required to …

Cosine Directions Using Rao-Blackwell Theorem And Hausdorff Metric In Quasars, Byron E. Bell

Byron E. Bell

This analysis will determine the equations of the Cosine Directions for all flux of the Optical Spectrum in quasars. Studies on Hausdorff metric will greatly enhance our understanding of quasars distances. The essential work of J. Bovy and D. Mortlock in the probabilities of quasars will set the methods/process of probability theory in the research along with Fokker-Planck probability theory. This study will complete steps in the classification of quasars by finding the minimum variance of flux by using the Rao–Blackwell Theorem. The papers of C. R. Rao and D. Blackwell will be examined to clarify more of the above …

National Survey Of Adolescent Well-Being (Nscaw): A Comparison Of Model And Design Based Analyses Of Cognitive Stimulation Scores, Marianne Bertolet, Howard Seltman, Joel Greenhouse, Kelly Kelleher

Joel B Greenhouse

Understanding and protecting vulnerable children is key to helping them become productive members of society. The Department of Health and Human Services sponsored the National Survey of Child and Adolescent Well-Being (NSCAW) to better understand the lives of children who come into contact with the child welfare system. This paper uses the NSCAW data to investigate the role of maternal depression and maternal substance abuse on a child's cognitive stimulation scores for a subset of the children. An investigation of the survey methodology and the actual data led to some manipulation of the data and assumptions for the analysis. The …

On Becoming A Bayesian: Early Correspondences Between J Cornfield And Lj Savage, Joel B. Greenhouse

Joel B Greenhouse

Jerome Cornfield was arguably the leading proponent for the use of Bayesian methods in biostatistics during the 1960s. Prior to 1963, however, Cornfield had no publications in the area of Bayesian statistics. At a time when frequentist methods were the dominant influence on statistical practice, Cornfield went against the mainstream and embraced Bayes. The goal of this paper is (i) to explore how and why this transformation came about and (ii) to provide some sense as to who Cornfield was and the context in which he worked.

Two Talks By Samuel W. Greenhouse, Joel B. Greenhouse

Joel B Greenhouse

The following two papers are written versions of talks given by my father, Samuel W. Greenhouse. The first paper in the series, entitled On Psychiatry, Epidemiology, and Statistics: A View from the 1950's and 60's, was presented in 1999 at the Harvard School of Public Health. The second paper, The Growth and Future of Biostatistics (A View from the 1980's) was the 1982 invited ENAR Presidential address delivered in San Antonio. It is an honor and a privilege to be able to include them as part of this special issue of Statistics in Medicine dedicated to him. Although these talks …

Meta-Analysis: In Practice, Joel Greenhouse

Joel B Greenhouse

The practice of meta-analysis is concerned with the details of implementation of a research synthesis that ensure the validity and robustness of the results from that synthesis. In this article, selected topics are discussed that represent current intellectual themes in the practice of meta-analysis, such as, (i) the role of decisions and judgments, particularly judgments about similarity of studies; (ii) the importance of sensitivity analysis to investigate the robustness of those decisions; and (iii) the role research synthesis plays in the process of scientific discovery. Brief illustrations of the role meta-analysis plays in explanation, program evaluation, and in informing policy …

A Study Of Non-Central Skew T Distributions And Their Applications In Data Analysis And Change Point Detection, Abeer Hasan

Abeer Hasan

Bayesian Hierarchical Modeling With 3pno Item Response Models, Yanyan Sheng, Todd Christopher Headrick

Todd Christopher Headrick

Fully Bayesian estimation has been developed for unidimensional IRT models. In this context, prior distributions can be specified in a hierarchical manner so that item hyperparameters are unknown and yet still have their own priors. This type of hierarchical modeling is useful in terms of the three-parameter IRT model as it reduces the difficulty of specifying model hyperparameters that lead to adequate prior distributions. Further, hierarchical modeling ameliorates the noncovergence problem associated with nonhierarchical models when appropriate prior information is not available. As such, a Fortran subroutine is provided to implement a hierarchical modeling procedure associated with the three-parameter normal …

Optimizing Parallel Belief Propagation In Junction Trees Using Regression, Lu Zheng, Ole J. Mengshoel

Ole J Mengshoel