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WSS NEWS
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Nominations are sought for the 2004 Roger Herriot Award for Innovation in Federal Statistics. After the sudden death in May 1994 of Roger Herriot, an Associate Commissioner for Statistical Standards and Methodology at the National Center for Education Statistics, the Washington Statistical Society, the Social Statistics and Government Statistics Sections of the American Statistical Association established an award in his memory to recognize individuals who develop unique approaches to the solution of statistical problems in Federal data collection programs.
The award is intended to reflect the special characteristics that marked Roger Herriot's career.
The award is not limited to senior members of an organization, nor is it to be considered as a culmination of a long period of service. Individuals at all levels (from entry to senior), Federal employees, private sector employees, and employees of the academic community, may be nominated on the basis of the significance of the specific contribution.
The recipient of the 2004 Roger Herriot Award will be chosen by a committee of representatives of the Social Statistics Section and Government Statistics Section of the American Statistical Association and a representative of the Washington Statistical Society. Roger Herriot was associated with and strongly supportive of these organizations during his career. The award consists of an honorarium of $1,000.00 and a framed citation.
Joseph Waksberg (Westat), Monroe Sirken (National Center for Health Statistics), Constance Citro (National Academy of Sciences), Roderick Harrison (U.S. Census Bureau), Clyde Tucker (Bureau of Labor Statistics), Thomas Jabine (SSA, EIA, CNSTAT), Donald Dillman (Washington State University), Jeanne Griffith (OMB, NCES, NSF), Daniel Weinberg (U. S. Census Bureau), and David Banks (FDA, BTS, NIST) are previous recipients of the Herriot Award.
For more information, contact Phillip S. Kott, Chair of the Roger Herriot Award Committee, 703-235-5211 x 102 or pkott@nass.usda.gov
Nominations must be submitted by April 15. Electronic submissions, via pdf, are permissible. Alternatively, nominations may be mailed to Phillip S. Kott, USDA/NASS, Room 305, 3251 Old Lee Highway, FAIRFAX, VA 22030-1504.
The Washington Academy of Sciences and its Affiliates present Capital Science 2004 to be held March 20 - 21, 2004.
On Saturday and Sunday, March 20-21, 2004, The Washington Academy of Sciences and its Affiliated Societies (including WSS) will hold the pan-Affiliate Conference, Capital Science. It will be held in the Conference Facility of the National Science Foundation in Ballston. With more than 25 of our Affiliates participating, the Conference will serve as an umbrella for scientific presentations, seminars, tutorials, and talks.
CONFERENCE HIGHLIGHTS
The Saturday evening dinner meeting will feature a keynote address by NSF Director and former Washington Academy of Sciences President Rita Colwell. The Saturday lunch meeting will feature a talk by Nobel Laureate William Phillips, of NIST and the University of Maryland. Dr. Phillips received the Nobel award in 1997 for his work in ultra-low temperature atomic physics. The Sunday lunch meeting will feature a talk by John Marburger III, Director of the White House Office of Science and Technology.
Plenary Sessions
Memorial Session honoring Nobelist Ilya Prigogine. Awarded the Nobel Prize for chemistry in 1977, Dr. Prigogine's work spanned mathematics, physics, chemistry, and philosophy.
Science, Ethics, and Religion, a special session of the AAAS lecture series.
A presentation by ASA President-Elect Fritz Scheuren on "Human Rights Issues Around the World: The Role of Good Data."
For more information or on-line registration, go to http://www.washacadsci.org/Website/Index.htm or contact Michael P. Cohen, 202-366-9949, Michael.cohen@bts.gov, the WSS representative to the Washington Academy of Sciences.
The American Statistical Association has two program LearnSTAT Program Offerings having registration deadlines this month. Both take place at the following location:
Arlington Campus Professional CenterGeorge Mason University
3401 North Fairfax Drive
Arlington, Virginia
(Near Washington, DC)
The registration fee for both courses is $500 for ASA members and $600 for nonmembers. (Registration fee includes materials, lunch, and refreshments for AM and PM breaks)
The first course is Intermediate/Advanced Bayesian Hierarchical Modeling which is a one-day course scheduled to be held on March 26, 2004 with a registration deadline of March 5, 2004. The second course is Longitudinal and Incomplete Data which is also a one-day course scheduled for April 2, 2004 having a registration deadline of March 12, 2004.
For more information and to register for these courses online, visit the Education section of the ASA Web site at www.amstat.org/education and click on the link for one of the courses.
If you have any questions, email LearnSTAT@amstat.org or call (703) 684-1221 ext. 166.
This is an award-winning short course on intermediate- and advanced-level methods and applications of Bayesian hierarchical modeling, including reviews of Bayesian modeling, Bayesian computation, and hierarchical models (HMs) for meta-analysis, and coverage of Bayesian model diagnostics, model checking, and model elaboration, mixture modeling with latent variables, HMs for clustered (hierarchical, multilevel) data, and semi-parametric HMs for dealing realistically with model uncertainty; case studies drawn from medicine, education, and environmental risk assessment.
Abstract: This course provides coverage of intermediate- and advanced-level topics arising in the formulation, fitting, and checking of hierarchical or multilevel models from the Bayesian point of view. The Bayesian approach is particularly effective in fitting hierarchical models because other model- based methods -- principally involving maximum likelihood -- often do not capture all relevant sources of uncertainty, leading to over-confident decisions and scientific conclusions.
The basic principles of Bayesian hierarchical modeling are reviewed in this course with emphasis on practical rather than theoretical issues. Intermediate- and advanced-level ideas are illustrated with real data drawn from case studies involving complicated applications of hierarchical models in cluster sampling and mixture modeling. The course is intended for applied statisticians with an interest in learning more about intermediate and advanced topics in hierarchical modeling in general, and the Bayesian analysis of such models in particular.
The instructor is Dr. David Draper, University California, Santa Cruz. Dr. Draper is a Professor in and Chair of the Department of Applied Mathematics and Statistics in the Baskin School of Engineering at the University of California, Santa Cruz. From 2001 to 2003 he served as the President-Elect, President, and Past President of the International Society for Bayesian Analysis (ISBA). His research is in the area of Bayesian inference and prediction, model uncertainty and empirical model-building, hierarchical modeling, Markov Chain Monte Carlo methods, and Bayesian semi-parametric methods, with applications mainly in health policy, education, and environmental risk assessment. When he gave this same short course at the San Francisco JSM last year, it won the ASA Excellence in Continuing Education award for 2003.
Abstract: This course provides a general introduction to longitudinal data and the linear mixed model for continuous responses. The topic will be approached from the modeler(s and practitioner's points of view. Emphasis will be on model formulation, parameter estimation, and hypothesis testing, as well as on the distinction between the random-effects (hierarchical) model and the implied marginal model. When the response of interest is categorical, the linear mixed model concepts can be extended towards generalized linear mixed models. An alternative approach is the use of generalized estimating equations (GEE). A lot of emphasis will be put on the fact that the regression parameters in both types of models have different interpretations. Advantages and disadvantages of both procedures will be discussed and compared in detail. Finally, when analysing longitudinal data, one is often confronted with missing observations, i.e., scheduled measurements have not been made, due to a variety of (known or unknown) reasons. It will be shown that, if no appropriate measures are taken, missing data can cause seriously biased results, and interpretational difficulties.
The instructors are Dr. Geert Verbeke and Dr. Geert Molenberghs. Dr. Verbeke is an Associate Professor in Biostatistics at the Biostatistical Centre of the Katholieke Universiteit Leuven in Belgium. He wrote his dissertation as well as a number of methodological papers on various aspects of linear mixed models for longitudinal data. Dr. Molenberghs is a Professor of Biostatistics at the Limburgs Universitair Centrum in Belgium. He published methodological work on repeated categorical data and on the analysis of nonresponse in clinical and epidemiological studies. Both instructors are the editors and authors of three books on the use of linear mixed models for the analysis of longitudinal data and they have taught several courses on the topic in universities as well as industry.
The Statistics Consortium at the University of Maryland, College Park, will sponsor a Statistics Day on April 20, 2004. The event will be co-sponsored by the Office of Research and Methodology, National Center for Health Statistics, and by the Joint Program in Survey Methodology.
The Stat Day will feature a "Tutorial on Bootstrap Methods with Applications in Complex Surveys" by Professor Randy Sitter, Simon Fraser University, and two lectures for a broad audience by Professors Bradley Efron, Stanford University (Discussant: Professor Carl Morris, Harvard University), and C.R.Rao, Pennsylvania State University (Discussants: Professor Bradley Efron and Dr. Fritz Scheuren, Vice President, NORC).
Pre-registration is required to attend the tutorial. The late afternoon lectures by Professors Efron and Rao are open to the public and registration is not required. The stat day will end with a reception for the presenters and the audience. Food and drinks will be served.
Please visit the UMD Statistics Consortium web site at http://www.statconsortium.umd.edu for updates and details.
Please visit for directions to University of Maryland @ College Park http://www.uga.umd.edu/visit/direct.html.
A number of developments - requirements of the HIPAA Privacy Rule, NIH requirements for data sharing plans for large grants, together with the proliferation of electronic data and the technical means for intrusions into those data - have intensified the need for guidance from statisticians skilled in data protection. In response to a number of requests, the Washington Statistical Society (WSS) and members of the Confidentiality and Data Access Committee (CDAC) are planning a workshop on Privacy, Confidentiality, and the Protection of Health Data -- A Statistical Perspective.
Over the past several decades, a significant body of research has emerged to form what has come to be known as Statistical Disclosure Limitation Techniques. These methods have not been widely disseminated in the health-related areas and yet are very applicable. The purpose of this WSS short course is to provide a basic understanding of the techniques and procedures employed by statisticians and others, to assess disclosure risk in statistical tabulations and electronic data and to minimize this risk to produce analytically useful information. Examples will be drawn from a wide variety of health and medical sources. In addition, the short course will present a review of legal issues related to the confidentiality of health data and, for those cases where a useful data product cannot be safely released or shared, a description of the various means of restricted access currently in use. As part of the course, extensive documentation will be provided to all attendees.
This one-day course, scheduled for April 27, 2004, will cover five areas:
About the Speakers:
Who Should Attend:
Professionals (epidemiologists, sociologists, demographers, etc.) who may be called upon to develop disclosure protection in compliance with the HIPAA privacy rule, NIH data sharing requirements, or other situations.
Schedule for Course:
The course will be held all day April 27, 2004. Registration will begin at 8:30 A.M. and the class will run from 9 A.M to 4:30 P.M.. There will be coffee and Danish in the morning before class and at the morning break, with beverages and cookies in the afternoon. Lunch will also be provided.
Location:
BLS Conference Center (near Union Station Metro stop)Registration:
WSS Members - $70
ASA Members - $85
Other registrants (except students) - $100
Full-time students - $25
Please make check payable to Washington Statistical Society. Mail, FAX, or e-mail the registration form (pdf) and send payment by April 16, 2004 to:
Mary V. Seidenberg
Support Staff
Agency for Healthcare Research and Quality
Gaither Road Rockville, Maryland 20850
E-mail: mseidenb@ahrq.gov
Phone Number: 301-427-1650
Fax Number: 301-427-1276 540
For more information on this course, please contact the WSS short-course co-chairs:
Sylvia Dohrmann (SylviaDohrmann@westat.com)
Trena M. Ezzati-Rice (tezzatir@ahrq.gov)
This is a one-day short course sponsored by the Joint Program in Survey Methodology on April 14, 2004 and presented at the Hyatt Regency Bethesda, Bethesda, Maryland. The instructors are Ben Shneiderman (ben@cs.umd.edu) and Catherine Plaisant (plaisant@cs.umd.edu). Both are from the Human-Computer Interaction Laboratory at University of Maryland, College Park, MD 20742 USA
The objectives of the course are to enable attendees: - to recognize the seven types of information visualizations and which combination is best for a given problem domain; - to distinguish between scientific and information visualization; - to learn guidelines for successful designs; - to see demos of novel visualizations; and - to understand opportunities for successful visualizations.
Information visualization has rapidly emerged as a potent technology to support human decision making. The latest generation of visual data mining tools and animated GUIs take advantage of human perceptual skills to produce striking results. This tutorial will show examples of successful uses of information visualization technology, plus recent research breakthroughs and hints of what's to come. Our emphasis will be on examples of government statistical data sets and we will highlight the challenges of providing universally usable interface designs.
Information visualization techniques empower users to perceive important patterns in large data sets, identify areas that need further scrutiny, and make sophisticated decisions. But looking at information is only a start. Users also need to manipulate and explore the data, using real-time tools to zoom, filter, and relate the information - and undo if they make a mistake.
Information visualization tools can aid in any situation that's characterized by large amounts of multi-dimensional or rapidly changing data, e.g. demographic trends, economic data analysis, health statistics, homeland security. The lectures are enhanced by a large number of live demonstrations, and with time for question asking and discussion.
The target audience is information professionals who must manage, present, interpret, and explore vital databases along with designers of advanced tools for decision support and business intelligence.
The course will be held at the Hyatt Regency Bethesda, One Bethesda Metro Center, at Wisconsin Avenue and Old Georgetown Road in Maryland. The hotel is in the heart of Maryland's high-tech corridor, just 6 miles from downtown Washington, D.C., with convenient access to the Capital Beltway and Metro Subway. The Hyatt is accessible via the Metro Red Line at the Bethesda Metro stop. For overnight room reservations, call the Hyatt Regency Bethesda at 301-657-1234. There is a parking garage located directly underneath the Hotel which offers both valet and self-parking. The garage is not owned or operated by the Hyatt Regency.
JPSM group lunches and refreshments are included in the course fee. Registrants will be provided with "The Craft of Information Visualization: Readings and Reflections", and a course pack containing detailed course notes.
The registration fee for staff at sponsoring agencies and affiliates is $400, $400 for full-time university students, and $535 for other participants. Payment by credit card is required. Post registration payment may be done online using the student's confirmation number. Payment is required by March 30, 2004. The JPSM Sponsor Affiliate List is located at http://projects.isr.umich.edu/jpsm/sponsorlist.cfm.
Online registration is required. Go to the JPSM Home Page at http://www.jpsm.org. Click on "JPSM Short Courses" for online registration. Confirmation of registration and instructions will be sent after the registration form has been processed. Registration is not firm until you receive a confirmation letter. Payment by credit card is required. Post registration payment should be done online using the student's confirmation number. Please note confirmation number. The registration deadline is March 30, 2004.
Please notify JPSM as soon as possible if you need to cancel your registration. Cancellation requests should be done online. You will be fully reimbursed if you cancel by March 30, 2004. Cancellation between March 31-April 6, 2004 will require a $100 administrative fee with the remainder being reimbursed. Cancellation on or after April 7, 2004 is subject to the full fee amount
The Joint Program in Survey Methodology strives to increase the number of survey professionals from groups traditionally under-represented in the field. As part of the effort, a limited number of competitive minority fellowships are available for African-Americans, Hispanic Americans, and Native American Indians for the short course.
Applicants should complete:
JPSM will evaluate the applications and inform the successful applicants by March 24, 2004. The fellowship covers the registration fee for the course including the cost of materials to be distributed during the course and lunch. Essays and recommendations may be either faxed to (734) 764-8263 or mailed to JPSM Short Course, Institute for Social Research, University of Michigan, 426 Thompson Street, Room 4050, Ann Arbor, MI 48106-1248.
Questions for this course should be directed to:
JPSM Short Course
Institute for Social Research
University of Michigan
426 Thompson Street, Room 4050
Ann Arbor, MI 48106-1248
Phone: (800) 937-9320
Fax: (734) 764-8263
Email: jpsmshort@isr.umich.edu
Web: http://projects.isr.umich.edu/jpsm/
Continuing the topic begun in October 2003, we examine residual plots and a histogram of the residuals. Subjects with residual values in the first or last percentiles are identified. Finally, we examine how the violation of assumptions regarding the random effects influences the inference of the model.
Continuing the topic begun in October 2003, the difference between general linear models and models using generalized estimating equations (GEE's) is covered. The available correlation structures in PROC GENMOD are discussed and GENMOD is used to fit a longitudinal data model. Finally, the concepts behind generalized linear mixed models are discussed and a longitudinal data model is fit using the GLIMMIX macro.
SIGSTAT is the Special Interest Group in Statistics for the CPCUG, the Capital PC User Group, and WINFORMS, the Washington Institute for Operations Research Service and Management Science.
All meetings are in Room S3031 (Food Safety and Nutrition Room), 1800 M St, NW from 12:30 to 1:30. Enter the South Tower and take the elevator to the 3rd floor to check in at the guard's desk.
First-time attendees should contact Charlie Hallahan, 202-694-5051, hallahan@ers.usda.gov and leave their name. Directions to the building and many links of statistical interest can be found at the SIGSTAT website, www.cpcug.org/user/sigstat/
Items for publication in the May 2004 WSS NEWS should be submitted no later than March 30, 2004. E-mail items to Michael Feil at michael.feil@usda.gov.
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First posted February 25, 2004 |
http://www.scs.gmu.edu/%7Ewss/wss0403.shtml |