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ASA JSM Program Book 06.Indd
GENERAL PROGRAM SCHEDULE ✪ Themed Session ● Applied Session ❖ Presenter CC-Washington State Convention & Trade Center H-Grand Hyatt Seattle S-Sheraton Seattle Hotel & Towers THURSDAY, AUGUST 10 Invited Sessions 8:30 a.m.–10:20 a.m. Thursday 483 CC-603 Tours ● Collaborative Research in Statistics—Invited General Methodology, Section on Physical and Engineering Sciences 1:00 p.m.–5:00 p.m. CC-Convention Place Organizer(s): Bonnie K. Ray, IBM T. J. Watson Research Center TR10 - Northwest Winery Tour (fee event) Chair(s): Bonnie K. Ray, IBM T. J. Watson Research Center 8:35 a.m. Sensor Analytics: Radioactive Gas Quantity 1:00 p.m.–5:00 p.m. CC-Convention Place Estimation and Error Propagation—❖Dale TR11 - Glassblowing Tour (fee event) N. Anderson, Pacifi c Northwest National Laboratory; Justin I. McIntyre, Pacifi c Northwest National Laboratory; Deborah K. Carlson, Pacifi c Northwest National Laboratory; Reynold Suarez, Committee/Business Meetings & Other Pacifi c Northwest National Laboratory; James C. Activities Hayes, Pacifi c Northwest National Laboratory 9:00 a.m. Using Informative Bayesian Priors in a Sales 7:00 a.m.–8:30 a.m. CC-305 Forecasting System—❖Phillip M. Yelland, Sun Howard Levene Memorial Breakfast Reception Microsystems Laboratories (closed) Organizer(s): Zhiliang Ying, Columbia University 9:25 a.m. Formulation Prediction for Derivative Product Development—❖Martha Gardner, GE Global 7:00 a.m.–10:30 a.m. CC-507, CC-508 Research Speaker Work Rooms 9:50 a.m. Disc: Sarah Michalak, Los Alamos National Laboratory 7:00 a.m.–10:30 a.m. CC-Level 4 South Lobby 10:10 a.m. -
VITA George Casella Address Current Positions Previous Positions
September 13, 2011 VITA George Casella Address Department of Statistics Email: casella@ufl.edu 102 Griffin-Floyd Hall Phone: 352-392-273-2993 University of Florida Fax: 352-392-5175 Gainesville, FL 32611 Current Positions Distinguished Professor, Department of Statistics, College of Agriculture, University of Florida Distinguished Member, Genetics Institute, University of Florida University of Florida Research Foundation Professor 2011-2014 Member, Governing Board of the Statistical and Mathematical Sciences Institute (SAMSI) Member, Board of Trustees of the National Institute of Statistical Science (NISS) Member, Scientific Advisory Committee for the Oslo Centre of Statistics for Innovation, Norway Editor, Journal of the Royal Statistical Society, Series B Previous Positions Colonel Allan R. and Margaret G. Crow Term Professor, 2009-2010 Distinguished Professor, Department of Statistics, College of Liberal Arts, University of Florida, 2004-2010 Distinguished Professor and Chair, Department of Statistics, University of Florida Executive Editor , Statistical Science, 2002-2004 Professor and Chair, Department of Statistics, University of Florida, 2000-2003 Arun Varma Commemorative Term Professor, Department of Statistics, University of Florida Liberty Hyde Bailey Professor of Biological Statistics, Cornell University, Ithaca, New York 1997-2000 Theory and Methods Editor, Journal of the American Statistical Association, 1996-1999 Professor, Biometrics Unit, Cornell University, Ithaca, New York. 1989-1997 Graduate Faculty Representative, Field of Statistics, Cornell University. Director, Statistics Center, Cornell University. Associate Professor, Biometrics Unit, Cornell University, Ithaca, New York 14853, 1983-1989. Visiting Professor, Department of Statistics, Purdue University, West Lafayette, IN, 1987- 1988. Chairman, Biometrics Unit, Cornell University, Ithaca, NY, 1985-86. Visiting Associate Professor, Department of Statistics, North Carolina State University, Raleigh, NC, Jan.-May 1985. -
A Comprehensive Evaluation of Methods for Mendelian Randomization Using Realistic
bioRxiv preprint doi: https://doi.org/10.1101/702787; this version posted February 5, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. A Comprehensive Evaluation of Methods for Mendelian Randomization Using Realistic Simulations and an Analysis of 38 Biomarkers for Risk of Type-2 Diabetes Guanghao Qi1 and Nilanjan Chatterjee1,2* 1Department of Biostatistics, Bloomberg School of Public Health and 2Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA * Correspondence to Nilanjan Chatterjee ([email protected]) 1 bioRxiv preprint doi: https://doi.org/10.1101/702787; this version posted February 5, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Background: Mendelian randomization (MR) has provided major opportunities for understanding the causal relationship among complex traits. Previous studies have often evaluated MR methods based on simulations that do not adequately reflect the data-generating mechanism in GWAS and there are often discrepancies in performance of MR methods in simulations and real datasets. Methods: We use a simulation framework that generates data on full GWAS for two traits under realistic model for effect-size distribution coherent with heritability, co-heritability and polygenicity typically observed for complex traits. We further use recent data generated from GWAS of 38 biomarkers in the UK Biobank to investigate their causal effects on risk of type-2 diabetes using externally available GWAS summary-statistics. Results: Simulation studies show that weighted mode and MRMix are the only two methods which maintain correct type-I error rate in a diverse set of scenarios. -
2020 Participating Bloomberg Distinguished Professors
2020 Participating Bloomberg Distinguished Professors Participating faculty are listed alphabetically by last name: Rexford Ahima: Endocrinology, Diabetes, & Metabolism, SOM; Epidemiology, BSPH; Community-Public Health, SON Project: Impact of Lmo4 knockout in brain on time-restricted feeding and energy metabolism. Knockout of Lmo4 in brain correlates with gain in body weight. We are studying the effects of restricting access to food during certain time of the day to determine the kinetics of weight gain and energy metabolism. Undergraduates will work on mouse breeding, coordinating food access to animals, measuring body composition, gene expression analysis and isolation of tissues. Preferred (or required) skills and/ or experience: Basic knowledge in biology, chemistry, math and physics. Positions available: 1 Work location: Bayview Medical Center, Asthma and Allergy Center, 5501 Hopkins Bayview Cir, Rm 2A62 Chuck Bennett: Physics and Astronomy, KSAS; JHU Applied Physics Lab (APL) Project: The research project relates to the Cosmological Large Angular Scale Surveyor (CLASS) telescope array that Johns Hopkins University operates high in the Andes Mountains of northern Chile. The research group builds new instrumentation, improves existing instrumentation, operates the telescope system to survey the sky, and analyzes data from the survey. The overall two major goals of the research are: (1) to determine, via measurement, the detailed process that led to the first stars forming; and (2) to determine, via measurement, the nature of the first fraction of a second of the creation of the universe. To achieve these goals, CLASS conducts a survey of the polarized cosmic microwave background radiation (the remnant glow from billions of years ago) over most of the sky. -
Statistical Decision Theory and Related Topics V Shanti S
Statistical Decision Theory and Related Topics V Shanti S. Gupta James O. Berger Editors Statistical Decision Theory and Related Topics V With 68 Illustrations Springer-Verlag New York Berlin Heidelberg London Paris Tokyo Hong Kong Barcelona Budapest Shanti S. Gupta James O. Berger Department of Statistics Purdue University West Lafayette, IN 47907 USA Library of Congress Cataloging-in-Publication Data Statistical decision theory and related topics V IShanti S. Gupta, James O. Berger, editors. p. cm. Papers of the Fifth Purdue International Symposium on Statistical Decision Theory and Related Topics held June 14-19, 1992, at Purdue University Includes bibliographical references. ISBN-13:978-l-4612-7609-8 e-ISBN-13:978-l-4612-26l8-5 DOl: 10.1 007/978-1-4612-2618-5 1. Statistical decision-Congresses. I. Gupta, Shanti Swarup, 1925- . II. Berger, James O. III. Purdue International Symposium on Statistical Decision Theory and Related Topics (5th: 1992: Purdue University) QA279.4.S745 1994 519.5' 42-dc20 93-27603 Mathematics Subject Classification (1991); 62C05, 62-06 Printed on acid-free paper. © 1994 Springer-Verlag New York, Inc. Softcover reprint of the hardcover 1st edition 1994 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer-Verlag New York, Inc., 175 Fifth Avenue, New York, NY 10010, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereaf ter developed is forbidden. -
Jennifer Rexford and Westley Weimer Receive the 2019 CRA-E Undergraduate See Page 2 for Full Article
COMPUTING RESEARCH NEWS Computing Research Association Uniting Industry, Academia and Government to Advance Computing Research and Change the World. FEBRUARY 2019 Vol. 31 / No. 2 CRN At-A-Glance New York Times Article Spotlights the High In This Issue Demand for Computer Science Professors 2 New York Times Article Spotlights Recently, The New York Times featured an article "The Hard Part the High Demand for Computer of Computer Science? Getting Into Class." The story explores how Science Professors the increasing student demand for computer science courses is 3 2019 Nominees for CRA Board; outstripping the supply of professors. The article cites CRA Taulbee CRA Board Elections in Progress data and quotes several current and former CRA board members. 4 Jennifer Rexford and Westley Weimer Receive the 2019 CRA-E Undergraduate See page 2 for full article. Research Faculty Mentoring Award 6 CCC Launches the “Catalyzing Computing” Podcast 2019 Nominees for CRA Board; 7 CCC Response to NITRD RFI to Update the 2016 Federal CRA Board Elections in Progress Cybersecurity Research and Development CRA is pleased to announce the 2019 Election Committee’s slate of Strategic Plan nominees for the CRA Board. Ballots have been distributed to all CRA 8 Interdisciplinary Research Challenges in Computer Systems department chairs and lab directors. Each will have one vote for each open (NSF Workshop Report) slot on the board. Completed ballots are due February 27. 9 Feeling Like an Outsider in Computing? See page 3 for full article. You Are not Alone! 11 Expanding -
Statistical Methods for Integrating Disparate Data Sources
STATISTICAL METHODS FOR INTEGRATING DISPARATE DATA SOURCES by Prosenjit Kundu A dissertation submitted to Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland April, 2020 Copyright 2020 by Prosenjit Kundu All rights reserved Abstract My thesis is about developing statistical methods by integrating disparate data sources with real data applications, and identifying gene-environment interac- tions (G E) in more extensive studies using existing analytical methods. We × propose a general and novel statistical framework for combining information on multivariate regression parameters across multiple different studies which have varying level of covariate information (Chapter 2). We illustrate the method us- ing real data for developing a breast cancer risk prediction model. We propose a generalized method of moments (GMM) approach for analyzing two-phase studies where we take into account the dependent structure of the datasets across the two-phases (Chapter 3). We illustrate the method using real data on Wilm’s tumor, a common type of kidney cancer in children. We analyze the largest gene by smoking interaction study for pancreatic ductal adenocarcinoma risk conducted to date using existing statistical methods (Chapter 4). Primary Readers Nilanjan Chatterjee (Advisor) Professor Department of Biostatistics & Department of Oncology ii Bloomberg School of Public Health, School of Medicine, The Johns Hop- kins University Alison Patricia Klein Professor Department of Oncology School of Medicine, The Johns Hopkins University Mei-Cheng Wang Professor Department of Biostatistics Bloomberg School of Public Health, The Johns Hopkins University Debashree Ray Assisstant Professor Department of Epidemiology Bloomberg School of Public Health, The Johns Hopkins University Alternate Readers Elizabeth L. -
Invited Session Submissions 1
01/12/2001 INVITED SESSION SUBMISSIONS 1 Wald Lecture I Chair: Mary Sara McPeek, University of Chicago Speaker: Presentation Title: Meiosis Presenting Author: Terry Speed, UC Berkeley and Hall Institute of Medical Research Wald Lecture II Chair: John Rice, University of California at Berkeley Speaker: Presentation Title: Biological Sequences Presenting Author: Terry Speed, UC Berkeley and Hall Institute of Medical Research Wald Lecture III Chair: Honggyu Zhao, Yale University Speaker: Presentation Title: Gene Expression Presenting Author: Terry Speed, UC Berkeley and Hall Institute of Medical Research Rietz Lecture Chair: Susan Murphy, University of Michigan Speaker: Presentation Title: Tomorrow and tomorrow and tomorrow... Statistics as a sequential game Presenting Author: A.P. Dawid, University College London, UK President's Address Speaker: Presentation Title: Are probabilists more of a community than statisticians? Presenting Author: Bernard Silverman, University of Bristol, UK Special Invited Paper Chair: Soumendra Lahiri, Iowa State University Speaker: Presentation Title: Hierarchical Modeling in the Analysis of Spatial Data Presenting Author: Alan Gelfand, University of Connecticut Discussant: Mark Handcock, University of Washington Special Invited Paper Chair: Steven Lalley, University of Chicago Speaker: Presentation Title: Random Processes with Reinforcement Presenting Author: Robin Pemantle, Ohio State University 01/12/2001 INVITED SESSION SUBMISSIONS 2 Discussant: Thomas Sellke, Purdue University Special Invited Paper Chair: -
Bhramar Mukherjee
Bhramar Mukherjee • Contact Information Office : Department of Biostatistics University of Michigan Home: 2353 Alder Ct 1420 Washington Heights Ann Arbor Ann Arbor, MI 48109-2029. MI 48103 Ph: (734)-764-6544 Phone:(734)-332-8976 Fax:(734)-763-2215 [email protected] http://www.sph.umich.edu/bhramar/public html • Employment Associate Professor (2009-), Department of Biostatistics, University of Michigan. Assistant Professor (2006-2009), John G. Searle Assistant Professor (2008-2009), Department of Biostatistics, University of Michigan. Participating Faculty: Occupational and Environmental Epidemiology Concentration, Department of Environmental Health Sciences, University of Michigan. Member, University of Michigan Comprehensive Cancer Center. Assistant Professor (Spring 2002-2006), Department of Statistics, University of Florida. • Other Employment Summer Intern, (Summer, 2000), Statistics Division, Eli Lilly and Company, Indianapolis. Teaching assistant, Statistical Consultant, Research Assistant (1996-2001), Department of Statistics, Purdue University. Visiting Scholar (Summer 2002), Department of Statistics, Stanford University. Visiting Scholar (Summer 2004), Applied Statistics Unit, Indian Statistical Institute, Kolkata, India. Visiting Assistant Professor (Fall 2001 and academic year 2004-2005), Department of Statistics, Purdue University. Visitor (Summer 2006), Division of Cancer Epidemiology and Genetics, The National Cancer Institute,(NCI/NIH), Bethesda, MD. 1 Visiting Scholar (Summer 2006, 2009), Department of Mathematics, Statistics and Computer Science Victoria University, Wellington, New Zealand. Visiting Scholar (Summer, 2010) Institut d’Investigaci Biomdica de Bellvitge Institut Catal d’Oncologia, Unitat de Bioestadistica Bioinformtica (Recipient of a visiting scholar grant awarded by the Agency for Administration of University and Research Grants (AGAUR), Catalonia, Spain) • Education Ph.D. in Statistics (Received 2001) Advisor : William J. Studden Optimal designs for estimating the path of a stochastic process Purdue University M.S. -
Genome-Wide Gene-Diabetes and Gene-Obesity Interaction Scan In
Author Manuscript Published OnlineFirst on June 16, 2020; DOI: 10.1158/1055-9965.EPI-20-0275 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Genome-wide gene-diabetes and gene-obesity interaction scan in 8,255 cases and 11,900 controls from Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case Control Consortium Hongwei Tang*1, Lai Jiang*2, Rachael Z. Stolzenberg-Solomon3, Alan A. Arslan4,5,6,, Laura E. Beane Freeman3, Paige M. Bracci7, Paul Brennan8, Federico Canzian9, Mengmeng Du10, Steven Gallinger11, Graham G. Giles12,13,14, Phyllis J. Goodman15, Charles Kooperberg16, Loic Le Marchand17, Rachel E. Neale18, Xiao-Ou Shu19, Kala Visvanathan20,21, Emily White22, Wei Zheng19, Demetrius Albanes3, Gabriella Andreotti3, Ana Babic23, William R. Bamlet24, Sonja I. Berndt3, Amanda Blackford21, Bas Bueno-de-Mesquita25,26,27,28, Julie E. Buring2,29, Daniele Campa30, Stephen J. Chanock3, Erica Childs21, Eric J. Duell31, Charles Fuchs32,33,34, J. Michael Gaziano29,35, Michael Goggins36, Patricia Hartge3, Manal H Hassam1, Elizabeth A. Holly7, Robert N. Hoover3, Rayjean J. Hung11, Robert C. Kurtz37, I-Min Lee2,29, Núria Malats38, Roger L. Milne12,13,14, Kimmie Ng23, Ann L. Oberg24, Irene Orlow10, Ulrike Peters22, Miquel Porta39,40, Kari G. Rabe24 , Nathaniel Rothman3, Ghislaine Scelo8, Howard D. Sesso2,29, Debra T. Silverman3, Ian M. Thompson, Jr41, Anne Tjønneland42, Antonia Trichopoulou43, Jean Wactawski-Wende44, Nicolas Wentzensen3, Lynne R. Wilkens17, Herbert Yu17, Anne Zeleniuch- Jacquotte5,6, Laufey T. Amundadottir3, Eric J. Jacobs42, Gloria M. Petersen24, Brian M. Wolpin23, Harvey A. Risch45, Nilanjan Chatterjee46, Alison P. Klein21,36 Donghui Li#1, Peter Kraft#2,47, Peng Wei#48. -
Final Program & Abstracts
ENAR 2015SPRING MEETING With IMS & Sections of ASA MARCH 15 –18 Hyatt Regency Miami Miami, FL FINAL PROGRAM & ABSTRACTS 4 Welcome and Overview 6 Acknowledgements 13 Special Thanks 15 Miami Highlights 18 Presidential Invited Speaker 19 IMS Medallion Lecture 20 Short Courses 23 Tutorials 26 Roundtables 29 Program Summary 44 Scientific Program 148 Abstracts & Poster Presentations 383 Index 397 Floor Plan WELCOME ¡Bienvenidos a Miami! It is my great pleasure to introduce the 2015 ENAR Spring Meeting to be held at the Hyatt Regency Miami, in Miami, FL, from March 15-18. The ENAR Spring Meeting brings together researchers and practitioners from academia, industry and government, connected through a common interest in Biom- etry. It offers a unique opportunity for learning new exciting methods and software, hearing about interesting and impactful applications, meeting new people (including prospective employers and job candidates), reconnecting with friends, and, this year, getting a break from the cold and snowy winter. The ENAR Spring Meeting only hap- pens through the diligent work of a large number of people who organize and contrib- ute to the program, plan and oversee the meeting logistics, and help with sponsorship – my heartfelt gratitude to all of them. Scientific Program: Through the leadership of Program Chair Mithat Gönen, of Memorial Sloan- Kettering Cancer Center, and Associate Chair Brisa Sánchez, of the University of Michigan School of Public Health, and with contributions from many of you, the Program Committee (with representatives from different ASA sections) has created an outstanding invited program. The sessions cover a wide range of topics of great interest to both researchers and practitioners, such as, data sciences (big data), genomics, clinical trials, neuroimaging, biomarkers, health policy, electronic health records, ecology, and epidemiol- ogy. -
Lessons Learned from Past Gene-Environment (Gxe) Interaction Successes
Lessons Learned from Past Gene-Environment (GxE) Interaction Successes Beate R. Ritz, Nilanjan Chatterjee, Montserrat Garcia-Closas, W. James Gauderman, Brandon L. Pierce, Peter Kraft, Caroline M. Tanner, Leah E. Mechanic, Kimberly McAllister Running Title: Gene-Environment (GxE) Interaction Successes Corresponding Author: Beate R. Ritz, MD, PhD Department of Epidemiology Fielding School of Public Health University of California Los Angeles Los Angeles, CA, 90095 Phone: 310-825-8579 Fax: 310-206-6039 Email: [email protected] 1 Abbreviations ALDH, aldehyde dehydrogenase; AS3MT, arsenite methyltransferase; CHRNA5, nicotinic receptor α5; CYP, cytochrome P-450; FeNO, nitric oxid; FTO, fat mass- and obesity; GxE, gene- environment; GWAS, genome-wide association study; G6PD, Glucose-6-phosphate dehydrogenase; GSTs, glutathione S-transferases; HLA-B, human leukocyte antigen-B; NAT2, N-acetyltransferase; NOS2, nitric oxide synthase 2; PD, Parkinson’s Disease; PON1, paraoxonase 1; VKORC1, Vitamin K epoxide reductase complex subunit 1 2 Abstract Genetic and environmental factors are both known to contribute to susceptibility to complex diseases. Therefore, the study of gene-environment (GxE) interactions has been a focus of research for several years. In this manuscript, select examples of GxE from the literature are described to highlight different approaches and underlying principles related to the success of these studies. These examples were broadly categorized as studies of: single metabolism genes, genes in complex metabolism pathways, ranges of exposure levels, functional approaches and model systems, and pharmacogenomics. Some studies illustrated the success of studying exposure metabolism for which candidate genes can be identified. Moreover, some GxE successes depended on the availability of high quality exposure assessment and longitudinal measures, study populations with a wide range of exposure levels, and the inclusion of ethnically and geographically diverse populations.