Topic: Power-Tail Distributions for Modeling Internet Traffic
Speaker: Carl M. Harris, BDM International Professor of Information Technology and Operations Research, School of Information Technology & Engineering, George Mason University
Chair: Douglas A. Samuelson, InfoLogix, Inc.
Date: Thursday, January 13, 2000, 12:30 p.m. - 2 p.m.
Location: Bureau of Labor Statistics, Room 2990, Postal Square Building, 2 Massachusetts Avenue, NE, Washington, DC Note: Please Use the First St. NE entrance. Call Karen Jackson (202-691-7524) at least 2 days before the talk to be placed on the visitors' list and bring photo ID.
Sponsor: Statistical Computing
Abstract:
Internet traffic data indicate that long-tailed (power-tail, fat-tail) distributions typically serve as better models for packet interarrival times and/or service lengths. These distributions have properties (e.g., possibly lacking some or all of their moments) that make it impossible to derive manageable queueing theory formulas for measuring congestion. We discuss a plan to apply a new method for fitting probability distributions through their Laplace transforms to generate complete probabilistic analyses of queues with power-tail interarrival or service times.
Topic: The National Center for Health Statistics Research Data Center: New research Opportunities
Speakers: John Horm, Negasi Beyene, Vijay Gambhir, and Robert Krasowski, National Center for Health Statistics
Discussant: Carol House, National Agricultural Statistics Service
Chair: Arnold Reznek, Bureau of the Census, Center for Economic Studies
Date: Tuesday, January 18, 12:00-1:50 p.m. (NOTE SPECIAL TIME)
Location: Bureau of Labor Statistics, Room 2990, Postal Square Building, 2 Massachusetts Avenue, NE, Washington, DC Note: Please Use the First St. NE entrance. Call Karen Jackson (202-691-7524) at least 2 days before the talk to be placed on the visitors' list and bring photo ID.
Sponsor: WSS Methodology Section
Abstract:
The National Center for Health Statistics (NCHS) has developed a Research Data Center (RDC) which allows researchers and data users to access internal data files from its numerous surveys containing data items which have not been available to the research community until now. Internal NCHS files contain lower levels of geography such as state, county, census tract, block-group, or blocks, depending on the survey. Examples of data systems that are available through the RDC include the National Health Interview Survey, the National Health and Nutrition Examination Survey, the National Hospital Discharge Survey, the National Survey of Family Growth Contextual Data Files (these consist of the survey data and about 1,300 contextual variables and is only available through the RDC) the National Ambulatory Medical Care Survey among others. Researchers may use internal NCHS data files to merge data from the Census Bureau, the Area Resource File, or other data collected or provided by the researcher (air pollution data, state, county, or local laws or ordinances, reimbursement policies, medical facilities, etc.) to perform contextual analyses while maintaining respondent confidentiality. Because of the confidentiality constraints NCHS has not been able to release survey data with lower levels of geography to its data users which has limited the amount and types of research, policy, and programmatic projects that could be undertaken with its data systems. The development of the RDC begins an exciting new era for NCHS and its data users.
Topic: Issues in Combining Survey Data: Estimates from the Medical Expenditure Panel Survey and the Medicare Current Beneficiary Survey
Speaker: D.E.B. Potter, Agency for Healthcare Research and Quality
Date: Thursday, January 20, 12:30-2:00 p.m.
Location: Bureau of Labor Statistics, Room 2990, Postal Square Building, 2 Massachusetts Avenue, NE, Washington, DC Note: Please Use the First St. NE entrance. Call Karen Jackson (202-691-7524) at least 2 days before the talk to be placed on the visitors' list and bring photo ID.
Speaker: David Scott, Department of Statistics, Rice University
Date: Friday, January 21, 11:00 a.m.
Location: The George Washington University, Department of Statistic, Funger 308, 2201 G Street NW. Foggy Bottom metro stop on the blue and orange line. The campus map is at: http://www.gwu.edu/Map/. The contact person is Efstathia Bura at ebura@gwu.edu or 202-994-6358.
Abstract:
We investigate the use of the popular nonparametric integrated squared error criterion in parametric estimation. Of particular interest are the problems of fitting normal mixture densities and linear regression. The algorithm is in the class of minimum distance estimators. We discuss some of its theoretical properties and compare it to maximum likelihood. The robustness of the procedure is demonstrated by example. The criterion may be applied in a wide range of models. Two case studies are given: an application to a series of yearly household income samples as well as a more complex application involves estimating an economic frontier function of U.S. banks where the data are assumed to be noisy. Extensions to clustering and discrimination problems follow.
Topic: Latent Class Analysis of Embedded Repeated Measurements:
An Application to the National Household Survey on Drug Abuse
Speakers: Paul Biemer and Christopher Wiesen, Research Triangle Institute
Discussants: Joseph Gfroerer and Douglas Wright, Substance Abuse and Mental Health Services Administration
Chair: Arthur Hughes, National Institute on Drug Abuse
Date:Tuesday, January 25, 10:30-12:00 p.m. (NOTE SPECIAL TIME)
Location: Bureau of Labor Statistics, Room 2990 Postal Square Building, 2 Massachusetts Avenue, NE, Washington, DC. Note: Please Use the First St. NE entrance. Call Karen Jackson (202-691-7524) at least 2 days before the talk to be placed on the visitors' list and bring photo ID.
Sponsor: WSS Methodology Section
Abstract:
Latent class analysis (LCA) is a statistical methodology that can be used to evaluate the error in categorical data when repeated measurements of the same constructs are available. Special problems arise in the analysis when the measurements are embedded within a single survey instrument. For example, the assumptions of independent classification error (ICE) may not hold due to respondent memory or other conditioning effects. In this article, we consider the application of LCA for evaluating classification error using repeated measurements embedded in survey questionnaire. To illustrate the techniques, we apply LCA to data from the 1994, 1995, and 1996 implementations of the National Household Survey on Drug Abuse. This application demonstrates the importance of LCA of embedded repeated measurements to identify questionnaire problems and, potentially, as a means for adjusting estimates, such as drug use prevalence, for classification error bias.
Topic: Analyzing Recurrent Event Data with Informative Censoring
Speaker: Mei-Cheng Wang, Department of Biostatistics, Johns Hopkins University
Date: Firday, February 4, 2000, 11:00 am
Location: Funger 308, 2201 G Street NW. Foggy Bottom metro stop on the blue and orange line. The campus map is at: http://www.gwu.edu/Map/. The contact person is Efstathia Bura at ebura@gwu.edu or 202-994-6358.
Abstract
Recurrent event data are frequently encountered in longitudinal follow-up studies. The non-informative censoring assumption is usually required for the validity of statistical methods for analyzing recurrent event data. In many applications, however, censoring could be caused by informative drop-out or death, and it is unrealistic to assume the independence between the recurrent event process and the censoring time. In this talk, we consider recurrent events of the same type and allow the censoring mechanism to be either informative or non-informative. A multiplicative intensity model which possesses desirable interpretations is used as the underlying model. Statistical methods are developed for (i) nonparametric estimation of the cumulative occurrence rate function, (ii) kernel estimation of the occurrence rate function, (iii) semiparametric estimation of regression parameters.
An analysis of the inpatient care data from the AIDS Link to Intravenous Experiences cohort (ALIVE) is presented.
Speaker: David Banks, Bureau of Transportation Statistics
Discussant: Edward Wegman, George Mason University
Chair: Virginia de Wolf, Office of Management and Budget
Date: Tuesday, February 8, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics Conference Center, Room 440 Postal Square Building, 2 Massachusetts Avenue, NE Washington, DC. Note: Please Use the First St. NE entrance. Call Karen Jackson (202-691-7524) at least 2 days before the talk to be placed on the visitors' list and bring photo ID.
Sponsor: WSS Methodology Section
Abstract:
Data mining has sprung up at the nexus of computer science, statistics, and management information systems. It attempts to find structure in large, high-dimensional datasets. To that end, the different disciplines have each developed their own repertoire of tools, which are now beginning to cross-pollinate and produce an improved understanding of structure discovery. This talk has two goals: (1) to outline to statisticians some of the contributions that have been developed by others, especially computer scientists, and (2) to lay out practical issues that have arisen in recent experience with superlarge datasets. More specifically, this talk will discuss the preanalysis and indexing of superlarge datasets, and present results of a desi gned experiment to compare the performances of such new-wave techniques as MARS, neural nets, projection pursuit regression, and other methods for structure discovery.
Topic: Experimental Poverty Measures: Research Issues
Speakers: Kathleen Short and Pat Doyle, Census Bureau:
Chair: David Johnson, BLS
Date/Time: Wednesday, February 16, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics, 2 Massachusetts Ave. NE, Room 2990 (Cognitive Laboratory). Enter at Massachusettes Avenue and North Capitol Street (Red Line: Union Station). Visitors outside the BLS, please call Karen Jackson at (202) 691- 7524 (email: Karen_Jackson@bls.gov) at least two days in advance to have your name placed on the guard's list for admittance. Please bring a photo id.
Sponsor: Social and Demographic Statistics
Abstract:
In the summer of 1999 the Census Bureau released a report on experimental poverty measures. That report uses alternative measures of poverty based on recommendations of the National Academy of Sciences to illustrate our different understanding of who is poor depending on the measure of poverty that is used. We show the differential incidence of poverty among various demographic and socioeconomic subgroups using these alternative poverty measures compared with the current official measure of poverty. Particular attention will be paid to the important effect that changing our poverty measure has on our understanding of the economic situation of the elderly and the role of health care in poverty measurement.
Topic: Measuring Job Flows and the Life Cycle of Establishments With BLS Longitudinal Establishment Microdata
Speakers: Timothy R. Pivetz, Michael A. Searson, & James R. Spletzer, Bureau of Labor Statistics
Discussant: Martin David, University of Wisconsin
Chair: Virginia de Wolf, Office of Management and Budget
Date: Wednesday, February 23, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics, Room 2990 Postal Square Building, 2 Massachusetts Avenue, NE , Washington, DC. Note: Please Use the First St. NE entrance. Call Karen Jackson(202-691-7524) at least 2 days before the talk to be placed on the visitors' list and bring photo ID.
Sponsor: WSS Methodology Section
Abstract:
The Bureau of Labor Statistics (BLS) is constructing a longitudinal database with monthly employment and quarterly wage data for virtually all business establishments in the United States. This longitudinal database will enable us to track changes in employment and wages not only at the macro level, but also at the micro level of the establishment. This paper describes this new database, demonstrates its potential for researchers and policy-makers, and presents initial research results.
We begin with a description of the longitudinal database. The source of the establishment microdata are the quarterly contribution reports that all employers subject to state unemployment insurance laws are required to submit. These data are a comprehensive and accurate source of employment and wages, and they provide a virtual census (98 percent) of employees on nonfarm payrolls. A section of the paper will be devoted to explaining how we link establishments across quarters, with particular attention given to the accurate identification of continuous, new, and closing establishments. The longitudinal database is being constructed from ten years of quarterly microdata. At inception, this database will be a high quality, high frequency, timely and historically consistent source for empirical research.
One of the purposes of the longitudinal database is to encourage microdata research into topics such as job creation, job destruction, and the life cycle of establishments. We will discuss how researchers can obtain access to this longitudinal database. We will present initial research results from this database, highlighting differences across industries, geography, and size classes.
Title: Recent Developments in Legal Frameworks Governing Individually Identifiable Data
Speaker: Donna Eden, Department of Health and Human Services,
Office of General Counsel
Discussant: Jacob Bournazian, Energy Information Administration
Chair: Virginia de Wolf, Office of Management and Budget
Date: Wednesday , March 8, 1:00 - 2:30 p.m. (Note special time)
Location: Bureau of Labor Statistics, Room 2990, Postal Square Building (PSB), 2 Massachusetts Avenue, NE, Washington, DC. Please use the First St., NE, entrance to the PSB. The names of all seminar attendees must be on "the list" to gain entry to BLS. To be placed on the visitor list at BLS, either (1) e-mail name, affiliation, and name of seminar to wss_seminar@bls.gov by noon 1 day ahead or (2) call Karen Jackson at 202-691-7524 at least 2 days ahead. Please bring a photo ID when you come to the talk.
Sponsor: WSS Methodology Section
Abstract
This session will provide a brief overview of existing statutory and regulatory frameworks governing the use of individually identifiable data by federal agencies, including the Freedom of Information Act, the Privacy Act, and some of the agency specific requirements. It will then address the potential effects of recent Congressional requirements concerning OMB Circular A-110 and publication of the Notices of Proposed Rulemaking for the privacy and security of health data required under the Health Insurance Portability and Accountability Act of 1996.
Topic: Issues in Combining Survey Data: Estimates from the
Medical Expenditure Panel Survey and the Medicare Current Beneficiary Survey
Speaker: D.E.B. Potter, Agency for Healthcare Research and Quality, DHHS
Date: Thursday, March 9, 12:30-2:00 p.m. (Rescheduled from January)
Location: Bureau of Labor Statistics, 2 Massachusetts Avenue, NE Room 2990 (Cognitive Lab). Enter at Massachusetts Ave and North Capitol Street (Red Line: Union Station) Call Karen Jackson at (202) 691-7524 (email: Karen_Jackson@bls.gov) at least 2 days before the talk to have your name placed on the guard=s list for admittance. Please bring a photo ID.
Sponsor: WSS Data Collection Methods Section
Abstract:
The household survey (HS) of both the Medical Expenditure Panel Survey (MEPS) and the Medicare Current Beneficiary Survey (MCBS) were designed to produce annual estimates for a variety of measures related to health care use, expenses, sources of payment, health status and insurance coverage. Both are national representative population based samples; longitudinal, with rotation; and require multiple rounds of in-person CAPI data collection to produce an annual estimate. The surveys differ with respect to their target populations; in MEPS HS, the U.S. civilian non-institutionalized population, and in MCBS, the current U.S. Medicare Beneficiary population. The purpose of this evaluation was to assess the compatibility of the survey estimates derived from these surveys. The objectives were to: (1) enhance the analytic utility of each survey, and (2) further advance the goals of the DHHS=s Survey Integration Plan, which called for Athe analytic linkage of the MCBS and the MEPS samples.@ For this presentation, we compare and contrast the design of each survey, explore issues for combining data, and compare and contrast estimates from the surveys. The paper also includes a discussion of key analytic measures considered incompatible for pooling, given survey differences, and provides some recommendations for future efforts.
Topic: Spatial and temporal trends in cancer incidence
Speaker: Ted Holford, Professor, Division of Biostatistics, Yale University
Chair: Linda Pickle, National Cancer Institute
Date/time: Monday, March 13, 2000, 11am - 12 noon
Location: Executive Plaza North, National Cancer Institute, 1st floor Conference room H; 6130 Executive Blvd., Rockville, MD, near White Flint metro stop.
Sponsor: NCI GIS Special Interest Group and the WSS Public Health & Biostatistics section
Abstract:
Empirical Bayes and Markov Chain Monte Carlo (MCMC) methods for fitting the conditional autoregressive model are known to offer a useful way of smoothing spatial patterns in disease rates. These methods are extended to incorporate time trends, thus offering additional insight into the spread of disease over space and time. Alternative ways of graphically displaying trends in disease maps will be presented. This model can also be used to identify geographic areas that are experiencing rapid change in disease incidence. These statistical techniques will be demonstrated using breast cancer incidence data from the 169 towns of Connecticut during the years 1984-1994.
Tutorial -- Multiple Imputation: Fabricate Your Data Well
Speaker: Joseph Schafer, Department of Statistics and The Methodology Center, Pennsylvania State University
Chair: Virginia de Wolf, Office of Management and Budget
Date: Monday , March 13, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics, Conference Center, Room 440, Postal Square Building, 2 Massachusetts Avenue, NE, Washington, DC. Please use the First St., NE, entrance to the PSB. The names of all seminar attendees must be on "the list" to gain entry to BLS. To be placed on the visitor list at BLS, either (1) e-mail name, affiliation, and name of seminar to wss_seminar@bls.gov by noon 1 day ahead or (2) call Karen Jackson at 202-691-7524 at least 2 days ahead. Please bring a photo ID when you come to the talk.
Sponsor: WSS Methodology Section
NOTE: This seminar will be shown simultaneously at the National Center for Health Statistics and at Westat via video.
Abstract:
Multiple imputation (MI) (Rubin, 1987) is a general-purpose method for handling missing data. Each missing observation is replaced by M > 1 simulated values, producing M completed datasets. The datasets are analyzed separately and the results are combined to yield inferences that account for missing-data uncertainty. This tutorial presentation will provide an overview of MI, including its advantages over other commonly used missing-data methods. Computational techniques for generating MI's in multivariate databases will be presented, with a live software demonstration. Finally, some issues surrounding the use of MI in complex surveys will be discussed, including its performance when used in conjunction with traditional randomization-based point and variance estimators.
Three-way Video Conference - Michigan, Maryland, BLS
Topic: Common Influences Across Household Surveys on Noncontact Nonresponse: Theory and Data
Speaker: Robert M. Groves, University of Michigan & Joint Program in Survey Methodology, and Douglas Wissoker, Urban Institute (joint work with Alison Liberty Greene, Molly McNeeley, and Darlene A. Montemarano, JPSM)
Date/Time: Thursday, March 23, 12:10 - 1:00 p.m.
Locations: (1) University of Maryland, 1218 Lefrak Hall (a map to the location is found on www.jpsm.umd.edu or call (301) 314-7911) (2) BLS Conference Center, Room 9, Postal Square Building, 2 Massachusetts Avenue, NE, Washington, DC, 20212 (Metro Red Line- Union Station). Use the First St. NE entrance. To be placed on the visitor list, e-mail name, affiliation, and name of seminar to wss_seminar@bls.gov (underscore after 'wss') by noon 1 day ahead or call Karen Jackson at 202-691-7524 at least 2 days ahead. Bring photo ID.
Sponsors: JPSM & WSS Methodology Section
Abstract:
There is growing convergence of findings that household survey nonresponse rates are increasing in the United States and other developed countries. At the same time there are recent experimental findings that high nonresponse rates do not necessarily produce high nonresponse error in large classes of survey statistics and some designs. This combination has prompted the development of theories to explain when nonresponse matters to survey inference and when it can be ignored.
By dissecting the nonresponse phenomenon into two major components B noncontact and refusals B we argue that there is some hope of separating a set of influences that are pervasive from a set that act in a more limited set of situations. We present a theoretical rationale asserting that influences on noncontact nonresponse are more consistent over survey designs than those affecting refusal nonresponse.
We then combine data from several surveys differing in mode, agency of collection, and response rates. We show consistent patterns of ease of contact across the surveys, across groups varying in household composition, access impediments, and calling patterns. Given these empirical results, We end by speculating on classes of measures that will be more or less affected by high noncontact rates, consistently, over broad classes of household survey designs.
Washington Statistical Society
Office of Research and Methodology Seminar
Topic: An Innovative Technique for Estimating Sensitive Survey
Items ("Three Card Method")
Speaker: Judy Droitcour, Assistant Director of GAO's Advanced Studies and Evaluation Methodology Group.
Chair: Joe Fred Gonzalez, Jr., National Center for Health Statistics (NCHS) (jfg2cdc.gov, 301-458-4239)
Date: Tuesday, March 28, 2000
Time: 10:00- 11:30 am
Place: NCHS Auditorium, Room 1110, Presidential Building, 6525 Belcrest Road, Hyattsville, MD (Metro: Green line to Prince Georges Plaza, then approximately 1.5 blocks North on Belcrest RD to Toledo RD)
Sponsor: Office of Research and Methodology, NCHS
Abstract:
The "three card method" is an innovative questionnaire technique that is designed to protect respondent privacy and possibly encourage more truthful answers in large-scale surveys. The technique involves three random subsamples-each consisting of completely different respondents. All subsamples are asked the same question, but each subsample answers using a slightly different answer card-so that a different piece of nonsensitive information is gathered from each subsample. When results from all three subsamples are combined, the sensitive answer category can be indirectly estimated for the relevant population or key subgroups. Initial development and testing (conducted or sponsored by GAO) focused on asking Hispanic immigrants/farmworkers about their immigration status. However, the three card method may prove applicable to a range of sensitive areas, including violent behaviors (road rage, child abuse, spouse abuse, police brutality), sensitive personal choices (abortion, marijuana use), and potentially many others.
Day/Time: Wednesday, March 29, 2000, 12:30-2:00 p.m.
Location: BLS, Postal Square Building, Room 2990, 2 Massachusetts Avenue, NE, Washington, DC (Red Line -- Union Station). Enter at Massachusetts Avenue and North Capitol Street. Send an email with your name, affiliation, and name of the seminar to wss_seminar@bls.gov, or call 202-691-7524 if you don=t have email, at least 2 days before talk to be placed on the visitors' list and bring photo id.
Abstract:
In some services industries, the concept of real output is unclear. What is the output of an insurance company? Of an economics or statistics consulting firm? In what units would those outputs be measured? When the economic concepts that statistical agencies measure are unclear, it is hardly surprising that their output measures and their price indexes are problematic. And if it is difficult to measure the output of an industry, it must also be difficult to measure its productivity. The importance of this topic is indicated by two facts: First, as Griliches has pointed out, the post-1973 slowdown in U.S. productivity growth is concentrated in precisely those industries in which output measurement problems exist. For example, finance and insurance had positive productivity growth has been negative (declining by more than 2 per cent per year from 1977 to 1993). Do measurement errors in output and price deflators contribute to the negative productivity trend? Second, those hard-to-measure services sectors are also accounting for a growing proportion of the economy. Their measurement problems are accordingly making an increasing impact on the nation's overall measures of economic performance. The Brooking Program on Output and Productivity Measurement in the Service Sector was designed to address concepts and measurement problems in the difficult to measure services industries. This paper will present a progress report. It reviews measurement issues and recent research on a group of industries, such as banking, insurance and finance, communications and transportation, retail and wholesale trade, and business and professional services. It will also make a preliminary assessment of the degree that measurement errors in these sectors account for the post-1973 slowdown in the U.S. productivity growth.
Washington Statistical Society
Office of Research and Methodology Seminar
Title: Downweighting Influential PSUs in Surveys, with Application to the 1990 Post-Enumeration Survey
Speaker: Nathaniel Schenker, Senior Scientist for Research
and Methodology, National Center for Health Statistics
(NCHS)
Chair: Trena Ezzati-Rice, Chief, Survey Design Staff,
Office of Research and Methodology, NCHS
Date/Time: Wednesday, April 12, 2000, 10:00 - 11:30 a.m.
Location: NCHS Auditorium, Room 1110, Presidential Bldg.,
6525 Belcrest RD, Hyattsville, MD (Metro: Green line to
Prince Georges Plaza, then approximately 1.5 blocks North on
Belcrest RD to Toledo RD.)
Abstract
Certain primary sampling units (PSUs) may be extremely influential on survey estimates and consequently contribute disproportionately to their variance. This talk will propose a general approach to downweighting influential PSUs, with downweighting factors derived by applying robust M-estimation to the empirical influence of the PSUs. The method is motivated by a problem in census coverage estimation. In this context, both extreme sampling weights and large coverage errors can lead to high influence, and influence can be estimated empirically by Taylor linearization of the survey estimator. As predicted by theory, the robust procedure greatly reduces the variance of estimated coverage rates, more so than truncation of weights. On the other hand, the procedure may introduce bias into survey estimates when the distributions of the influence statistics are asymmetric. Properties of the procedure in the presence of asymmetry will be considered, and techniques for assessing the bias-variance tradeoff will be demonstrated.
For further information contact: Joe Fred Gonzalez, ORM,
NCHS, at 301-458-4239 or jfg2@cdc.gov
Topic: The Pros and Cons of Using Design-Based Methods for
Estimating Model Parameters: A General Theory
Speakers: David Binder and Georgia Roberts, Statistics
Canada
Discussant: John Eltinge, Bureau of Labor Statistics
Chair: Phil Kott, National Agricultural Statistics Service
Date: Wednesday, April 12, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics Conference Center,
G440 Postal Square Building, 2 Massachusetts Avenue, NE
Washington, DC 20212 (Metro Red Line; exit at Union
Station). Please use the First St. NE entrance. To attend
send E-mail name, affiliation, and name of seminar to
wss_seminar@bls.gov (underscore after 'wss') by noon 1 day
ahead or call Karen Jackson at 202-691-7524 (NOTE CHANGE!)
at least 2 days ahead to be placed on the visitor list.
Bring photo ID.
Sponsor: WSS Methodology Section
Abstract:
One of the first questions an analyst asks when fitting a model to data that has been collected from a complex survey is whether or not to account for the survey design in the analysis. In fact, there are two questions that should be addressed. Not only must the analyst decide on whether or not to use the sampling weights for the point estimates of the unknown parameters, he must also consider how to estimate the variance of the estimators for hypothesis testing and deriving confidence intervals. There are a number of schools of thought on these questions. The pure model-based approach would demand that if the model being fitted is true, then one should use an optimal model-based estimator, and normally this would result in ignoring the sample design.
The variance of the estimator would be with respect to the underlying stochastic model in which the sample design is irrelevant. In the design-based approach, on the other hand, we assume that the observations are a random sample from a finite population. There is no reference to a superpopulation. The randomization mechanism is dictated by the chosen sampling design, which may include unequal probabilities of selection, clustering, stratification, and so on. We show that the design-based variance of the weighted estimator will be asymptotically equal to its model-based variance under a wide range of assumptions, at least for large samples where the sampling fraction is small, and that the pure model-based approach can lead to misleading conclusions when the model assumptions are violated. Some interesting new results on variance estimation based on estimating functions will be discussed.
Title: An Analysis of The Relationship Between Survey
burden and Non-response: If we bother them more, are they
less cooperative?
Writers: Jaki Stanley McCarthy and Dan Beckler
Speaker: Dan Beckler
Chair: Anne Peterson
Date/Time: Tuesday, April 18, 2000, 12:00 - 2:00 p.m.
Location: Bureau of Labor Statistics Conference Center,
G440 Postal Square Building, 2 Massachusetts Avenue, NE
Washington, DC 20212 (Metro Red Line; exit at Union
Station). Please use the First St. NE entrance. To attend
send E-mail name, affiliation, and name of seminar to
wss_seminar@bls.gov (underscore after 'wss') by noon 1 day
ahead or call Karen Jackson at 202-691-7524 (NOTE CHANGE!)
at least 2 days ahead to be placed on the visitor list.
Bring photo ID.
Sponsor: WSS Methodology Section
Abstract:
In surveys of certain populations, individuals may be contacted on numerous occasions over time. This is particularly true in surveys of establishments, where large or unique operations may be selected with near certainty for recurring surveys and may be included in samples for multiple surveys. Cooperation in any particular survey may be affected by the number and frequency of times an establishment has been selected for surveys by that organization in the past.
This paper examines the relationship between response on the 1998 June Crops Survey in South Dakota and the reporting burden placed on operations by NASS in the past. The number of other NASS surveys operations have been contacted for the length of time since they were last contacted for a NASS survey, and the type of information they have been contacted for in the 2 years prior to the June Survey will be considered. Comparisons of these burden measures will be made between respondents and non-respondents for the June Survey. Implications of the relationship between survey burden and response will be discussed
Title: Exploring the Relationship between Survey
Participation and Survey Sponsorship: What do respondents
and non-respondents think of us?
Writers: Jaki Stanley McCarthy and Dan Beckler
Speaker: Kathy Ott
Chair: Anne Peterson
Date/Time: Tuesday, April 18, 2000, 12:00 - 2:00 p.m.
Location: Bureau of Labor Statistics Conference Center,
G440 Postal Square Building, 2 Massachusetts Avenue, NE
Washington, DC 20212 (Metro Red Line; exit at Union
Station). Please use the First St. NE entrance. To attend
send E-mail name, affiliation, and name of seminar to
wss_seminar@bls.gov (underscore after 'wss') by noon 1 day
ahead or call Karen Jackson at 202-691-7524 (NOTE CHANGE!)
at least 2 days ahead to be placed on the visitor list.
Bring photo ID.
Sponsor: WSS Methodology Section
NOTE: This seminar immediately follows the one above.
Abstract:
A series of questions was asked of QAS respondents in South Dakota in order to examine the relationship between their knowledge and attitudes toward NASS surveys and their survey participation. The questions were about the respondents' identification of NASS (at the local and national level), their perceptions of NASS and its data, the effect of data on the respondents, and their opinions regarding responding to NASS surveys. These questions were asked of both respondents and non-respondents to the QAS in contacts throughout 1998 and 1999.
Distinct differences were found in attitudes of respondents and non-respondents for most of these measures. Some differences were also found between different types and sizes of operations.
Findings are intended to guide promotional and public relations activities that will be targeted toward potential respondents and suggest data collection procedures that will increase survey participation. The opinion questions will continue to be asked of survey respondents to gauge changes in attitudes toward NASS as these activities continue.
Topic: Estimation of Capital and Technology with a Dynamic
Economic Model
Speaker: Peter Zadrozny, Bureau of Labor Statistics
Discussant: Michael Binder, University of Maryland
Chair: Mark Doms, Federal Reserve Board
Day/Time: Wednesday, April 19, 2000, 12:30 - 2:00 p.m.
Location: BLS, Postal Square Building, Room 2990, 2
Massachusetts Avenue, NE, Washington, DC (Red Line -- Union
Station). Enter at Massachusetts Avenue and North Capitol
Street. Send an email with your name, affiliation, and name
of the seminar to wss_seminar@bls.gov, or call 202-691-7524
if you don't have email, at least 2 days before talk to be
placed on the visitors' list, and bring photo id.
Sponsor: Economics Section
Abstract:
Two fundamental sources of growth of output are accumulation of production capital and technological knowledge (henceforth, more simply called 'capital' and 'technology'). The problem is that capital and technology are unobserved except at the most disaggregated levels of production activity. Therefore, in order to use capital and technology series in quantitative analysis, economists first have had to construct or estimate these series. The premise of the paper is that conventional estimates of capital and technology series have been based on unnecessarily limited theoretical and sample information. The paper describes a method for obtaining estimates of capital and technology from prices and quantities of related input and output variables. The method involves specifying and estimating a detailed structural dynamic economic model of a representative production firm in an industry and applying the Kalman smoother to the estimated model to compute estimates of unobserved capital and technology over the sample period. The specified model is estimated using annual U.S. total manufacturing data from 1947 to 1998. Because the resulting estimates of capital and technology are based on the detailed structural model and on sample observations of ten related prices and quantities of inputs and output, they are based on much wider theoretical and sample information than conventional estimates.
Topic: Latent Class Analysis of Embedded Repeated
Measurements: An Application to the National Household
Survey on Drug Abuse
Speakers: Paul Biemer and Christopher Wiesen, Research
Triangle Institute
Discussants: Joseph Gfroerer and Douglas Wright, Substance
Abuse and Mental Health Services Administration
Chair: Arthur Hughes, National Institute on Drug Abuse
Date: Tuesday, April 25, 2000, 10:30-12:00 p.m. (NOTE
SPECIAL TIME)
Location: Bureau of Labor Statistics, Postal Square
Building (PSB), Conference Center, Room G440, Rooms 1 & 2,
2 Massachusetts Avenue,NE, Washington, DC. Please use the
First St., NE, entrance to the PSB. To gain entrance to
BLS, please see "Notice" at the end of this announcement.
Sponsor: WSS Methodology Section
Abstract:
Latent class analysis (LCA) is a statistical methodology that can be used to evaluate the error in categorical data when repeated measurements of the same constructs are available. Special problems arise in the analysis when the measurements are embedded within a single survey instrument. For example, the assumptions of independent classification error (ICE) may not hold due to respondent memory or other conditioning effects. In this article, we consider the application of LCA for evaluating classification error using repeated measurements embedded in survey questionnaire. To illustrate the techniques, we apply LCA to data from the 1994, 1995, and 1996 implementations of the National Household Survey on Drug Abuse. This application demonstrates the importance of LCA of embedded repeated measurements to identify questionnaire problems and, potentially, as a means for adjusting estimates, such as drug use prevalence, for classification error bias.
Topic: Producing an Annual Superlative Index Using Monthly
Price Data
Speaker: Erwin Diewert, Department of Economics, University
of British Columbia, e-mail: diewert@econ.ubc.ca
Discussant: Alan Dorfman, Office of Survey Methods
Research, Bureau of Labor Statistics
Chair: Bill Alterman, Office of Prices and Living
Conditions, Bureau of Labor Statistics
Date/Time: Tuesday, April 25, 2000, 12:30 - 2:00 p.m.
Location: BLS Conference Center, Rooms 1 & 2, Postal Square
Building, 2 Massachusetts Avenue, NE, Washington, DC, 20212
(Metro Red Line-Union Station). Use the First St. NE
entrance. To be placed on the visitor list, e-mail name,
affiliation, and name of seminar to wss_seminar@bls.gov
(underscore after 'wss') by noon 1 day ahead or call Karen
Jackson at 202-691-7524 at least 2 days ahead. Bring photo
ID.
Sponsor: WSS Methodology Section
Abstract:
The main purpose of the presentation is to outline some alternative approaches on how a superlative annual consumer price index could be constructed using the monthly price information that is presently collected by statistical agencies. The first issue that must be addressed is: how should the monthly price information at the lowest level of aggregation be aggregated up (over months) to form an annual price level or price relative at this lowest level of commodity aggregation? Having constructed appropriate annual elementary indexes, the presentation discusses how to complete the process to construct an annual (calendar year) superlative index.
Considering the problem of seasonal commodities, it is noted that the construction of year over year (superlative) indexes for each month of the year should be free of seasonal influences. Moreover, the business community is typically quite interested in this class of index numbers so the presentation recommends that statistical agencies produce them. This approach leads to another two stage aggregation of the micro price information into an overall annual index: first aggregate across commodities holding the month constant and then aggregate across months. It is noted that the alternative two stage annual indexes can be quite close to each other.
The two annual indexes are on a calendar year basis; i.e., the price and quantity data pertaining to all 12 months in 1999 are compared to the corresponding prices and quantities for the base year, say 1995. However, we can also construct a moving year or rolling year annual index, using price and quantity information collected each month. Thus the statistical agency could produce a new rolling year index every month, which of course would lag behind its present very timely CPI index due to the lags involved in collecting the relevant quantity (or expenditure) information. The real advantage of these moving year superlative indexes is that they are both timely and do not require any seasonal adjustment.
A problem with the indexes discussed so far is that they do not give us any information on short term price movements; i.e., all of these indexes compare prices in a month in the current year with the same month in the base year. Thus, the presentation briefly discusses superlative month to month price indexes.
Topic: AudioCASI: Design and Data Collection Issues
Speakers: Rachel Caspar, Research Triangle Institute
Sid Schneider, Westat
Date/Time: Tuesday, April 25, 2000, 12:30 - 2:00 p.m.
New Location: Room 101, OERI/Dept. of Education, 80 F Street, NW (Red Line: Union Station, cross 1st St. NE, walk north one block on Massachusetts Ave., cross Massachusets and North Capitol St. and walk one block on F St.). Go past guard's desk and through glass doors, turn left and enter 101 through anotherglass door. Registration is not required in advance.
Sponsor: WSS Data Collection Methods Section
Abstract:
Although audioCASI has been around for quite a while, until recently actual large-scale implementations of the technology have been few and far between. During the past few years, however, the software and hardware required for A-CASI have improved significantly, and its advantages for reducing the underreporting of sensitive behavior have become increasingly accepted. Consequently, more A-CASI projects have moved first into development, and then into full-scale production. This session will focus on practical issues and "lessons learned" in designing and fielding ACASI surveys, with special attention to sensitive items and populations with low literacy levels. What is different about the design process, compared to CAPI and CATI studies? What are the impacts on the development process and schedule? How about interviewer training? Are there additional logistical and support issues in the field?
Topic: Further Examination of the Distribution of Individual
Income and Taxes Using a Consistent and Comprehensive Measure of
Income
Speaker: Tom Petska, Internal Revenue Service
Discussant: Fritz Scheuren, The Urban Institute
Chair: Linda Atkinson, Economic Research Service
Day/Time: Wednesday, May 3, 2000, 12:30 - 2:00 p.m.
Location: BLS, Postal Square Building, Room 2990, 2 Massachusetts
Avenue, NE, Washington, DC (Red Line -- Union Station). Enter at
Massachusetts Avenue and North Capitol Street. Send an email with
your name, affiliation, and name of the seminar to wss_seminar@bls.gov, or call 202-691-7524 if you don't have email,
at least 2 days before talk to be placed on the visitors' list, and
bring photo id.
Sponsor: Economics Section
Abstract
Different approaches have been used to measure the
distribution of individual income over time. Survey data, such
as those of the Census Bureau=s CPS and SIPP, have been compiled
with innovative enumeration methods, but underreporting,
inter-temporal consistency and inadequate coverage at the highest
income levels can still jeopardize results. Administrative
records, such as tax returns, may be less susceptible to
underreporting of income but can be limited in scope and
coverage. Record linkage studies have capitalized on the
advantages of both approaches, but are severely restricted by the
laws governing data sharing.
This paper is the third in a series examining trends in the
distribution of individual income and taxes based on a consistent
and comprehensive measure of income derived exclusively from
individual income tax returns. Statistics from 1979 through 1997
on the distribution of individual income, the shares of taxes
paid, and average tax burdens, all by size of income, are
presented, and analyzed. In addition, Lorenz curves and Gini
coefficients have been estimated to assess trends in income
inequality, both before- and after taxes, and some conclusions
are made on these trends and the overall redistributive effects
of the Federal income tax system.
Topic: The Foundation of AIC and Its Use in Multi-Model Inference
Speaker: Kenneth P. Burnham, Colorado Cooperative Fish and
Wildlife Research Unit, Colorado State University,
KenB@Lamar.ColoState.Edu
Chair: Mark Otto, U.S. Fish and Wildlife Service
Date/Time: Monday, May 8, 2000, 10:30 - 11:30 a.m.
Location: 228 Gabrielson Hall, Patuxent Wildlife Research Refuge,
Laurel, MD 20708
DIRECTIONS: From the NE portion of the beltway, go north on the
Baltimore Washington Parkway (295). Go east at the third exit,
Powder Mill Road (212), and go to the end. Cross 197 into the
Patuxent Wildlife Research Refuge. Go about a mile curving around
to the right until you drive into a parking lot. There will be a
pond on the right and two buildings on the left. Park there & walk
between the two buildings to Gabrielson, the larger, modern
building. Conference room 228 is upstairs at the end of the main
hall. For more information, contact Mark Otto (301) 497-5872,
Mark_Otto@FWS.Gov.
Sponsor: U.S. Fish & Wildlife Service and WSS Methodology
Section
Abstract:
Today, model selection is most often the search for the
"best" model (often using hypothesis testing), followed by
inference conditional only on the selected model. This process
ignores the fact that multiple models often provide competitive
explanations of the data. Using Akaike's Information Criterion
(AIC), model selection could account for the uncertainty in
selecting a model, providing more realistic inferences. This
talk outlines the philosophical and mathematical basis for AIC as
a model selection criterion, and shows that AIC can be used to
make model-averaged inferences over the set of models considered.
A strong case can be made for basing model selection on
likelihood and Kullback-Leibler (K-L) information theory. This
approach leads to AIC and its important variations and does so
without assuming the "true model" is even considered. Because of
this, only the relative AIC differences between each model and
the best model in the set are what matter. These differences
measure the relative support for competing fitted models.
Normalized weights derived from these relative differences allow
unconditional inferences based either on the selected model or on
averages over the model set. In both cases, the inferences
account for the model selection uncertainty, i.e., they are
conditional on more than the one best model.
Topic: Time-Use Surveys: What Are They? Why Are We Interested?
Speaker: Linda L. Stinson, Research Psychologist, Office of
Survey Methods Research, Bureau of Labor Statistics
Day/Time: Tuesday, May 9, 2000, 12:30 - 2:00 p.m.
Location: BLS, Postal Square Building, Room 2990, 2 Massachusetts
Avenue, NE, Washington, DC (Red Line -- Union Station). Enter at
Massachusetts Avenue and North Capitol Street. Send an email with
your name, affiliation, and name of the seminar to
wss_seminar@bls.gov, or call 202-691-7524 if you don't have email,
at least 2 days before talk to be placed on the visitors' list, and
bring photo id.
Sponsor: Co-sponsored by DC AAPOR and WSS Data Collection
Methods Section
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Abstract:
The last half of the twentieth century has been witness
to enormous social change and shifts in patterns of time use, both
in the workplace and in the home. A variety of
methodological approaches have been used to systematically
collect information about the activity patterns of modern life.
But it is the detailed chronological reporting procedure of the
time-use survey that is valued by many social researchers because
it provides a way to measure changes in behavior while avoiding
many of the pitfalls associated with other survey collection
procedures. This talk will introduce the Atime-use survey@
method of data collection. It will also include an overview of
the essential features of a time-use interview and present the
types of customers who are (or might be) interested in the data.
Chair: Virginia de Wolf, Office of Management and Budget
Date/Time: Wednesday, May 10, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics, Conference Center, Room
440, Postal Square Building, 2 Massachusetts Avenue, NE,
Washington, DC. Please use the First St., NE, entrance to the
PSB. The names of all seminar attendees must be on "the list" to gain
entry to BLS. To be placed on the visitor list at BLS, either
(1) e-mail name, affiliation, and name of seminar to
wss_seminar@bls.gov (underscore after 'wss') by noon 1 day ahead or
(2) call Karen Jackson at 202-691-7524 at least 2 days ahead.
Please bring a photo ID when you come to the talk.
Sponsor: WSS Methodology Section
Abstract:
Developments in statistical computing over the last
10-15 years have led to a substantial increase in interest in the
Bayesian approach to statistical inference. There remain many,
however, that are concerned about the Bayesian approach's
reliance on prior information. In this introductory level talk
we review the Bayesian approach and discuss the various issues
(advantages and disadvantages) associated with its use.
Topic: Comparing IVR, CATI, and Mail to Collect Demographic
Information
Speaker: Roger Tourangeau (SRC, Michigan) and Darby Miller
Steiger (The Gallup Organization).
Day/Time: Wednesday, May 10, 2000, 12:30 - 2:00 p.m.
Location: BLS, Postal Square Building, Room 2990, 2 Massachusetts
Avenue, NE, Washington, DC (Red Line -- Union Station). Enter at
Massachusetts Avenue and North Capitol Street. Send an email with
your name, affiliation, and name of the seminar to
wss_seminar@bls.gov, or call 202-691-7524 if you don't have email,
at least 2 days before talk to be placed on the visitors' list and
bring photo id.
Sponsor: Social and Demographics Section
Abstract:
This talk describes a study that compared three methods
of collecting demographic information. (The questionnaire used the
same items that will be administered on the Census 2000 Long Form.)
One version of the questionnaire was administered by a computer
program, which played digitized recordings of the questions over
the telephone. This methodology--known variously as interactive
voice response (IVR) or telephone audio-CASI (TACASI)--was compared
with mail data collection and CATI interviews. With the long
questionnaire we used, many respondents may broke the IVR
interviews before they finished the questionnaire. Even ignoring
these breakoffs, item nonresponse rates were also higher in IVR
than with CATI or mail. Still, IVR may produce more accurate
reports about sensitive topics, such as the receipt of welfare.
Speaker: Thomas A. Louis PhD, Division of Biostatistics, School
of Public Health, University of Minnesota
Discussant: Sam Greenhouse, George Washington University
Chair: Sandy West, Bureau of Labor Statistics (retired)
Date/Time: Thursday, May 11, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics, Room 2990, Postal Square
Building (PSB), 2 Massachusetts Avenue, NE, Washington, DC.
Please use the First St., NE, entrance to the PSB. The names of all seminar attendees must be on "the list" to gain
entry to BLS. To be placed on the visitor list at BLS, either
(1) e-mail name, affiliation, and name of seminar to
wss_seminar@bls.gov (underscore after 'wss') by noon 1 day ahead or
(2) call Karen Jackson at 202-691-7524 at least 2 days ahead.
Please bring a photo ID when you come to the talk.
Sponsor: WSS Methodology Section
Abstract:
By structuring complicated models and providing a
formalism for bringing in objective and subjective information,
Bayes and empirical Bayes methods have the potential to produce
more efficient and informative designs and analyses than those
based on traditional approaches. However, realization of this
potential requires that the methods be robust to departures from
assumptions and be credible to the community that will use
findings. To set a framework for discussing the role of Bayesian
statistics, I outline the approach, including its potentials and
prerequisites. Then, I discuss frequentist performance for
Bayesian procedures, addressing non-standard goals, accommodating
multiplicity, clinical trial monitoring and Bayesian design for
frequentist analysis. Each topic includes both the necessary
statistical formality and applied examples.
Title: Structural Modeling in Time Series and an Analysis
of Fatal Road Accidents
Speakers: Keith Ord, Georgetown University and Sandy Balkin,
Ernst & Young
Discussant: William Bell, Census Bureau
Chair: Mary K. Batcher, Ernst & Young & WSS President
Date/Time: Thursday, May 11, 2000, 2:15 - 4:00 p.m.
Location: Bureau of Labor Statistics, Postal Square Building,
Room 2990, 2 Massachusetts Avenue, NE Washington, DC 20212 (Metro
Red Line; exit at Union Station). Please use the First St. NE
entrance. To attend send E-mail name, affiliation, and name of
seminar to wss_seminar@bls.gov (underscore after 'wss') by noon 1
day ahead or call Karen Jackson at 202-691-7524 at least 2 days
ahead to be placed on the visitor list. Bring photo ID.
Sponsor: WSS President's Invited Address
Abstract:
The statistical analysis of time series tends to be
dominated by ARIMA (Autoregressive Integrated Moving Average)
models. In the first part of this talk we consider the
structural approach to time series modeling and identify some of
the advantages and disadvantages of this framework relative to
ARIMA. We also consider briefly some recent results that enable
us to broaden the structural class in various ways. In
particular, we find that exponential smoothing procedures are
model-based and have a much wider range of applicability than
previously thought.
In the second part of the talk we describe a study on numbers of
fatal accidents on the interstate system using monthly data for
individual States over the period 1975-98. The goal is to
examine the impact of changes in speed limits upon the incidence
of fatal accidents. These series were analyzed using the STAMP
package for structural modeling. The analysis, summarized in
Consumer Reports (April 2000), reveals some interesting
differences when compared to previous studies.
About the speakers:
J. Keith Ord is a professor at the McDonough School of Business
at Georgetown University. His research interests include
business forecasting, inventory planning, and the statistical
modeling of business processes. Dr. Ord is a co-author of
Kendall's Advanced Theory of Statistics, a two-volume reference
work now in its sixth edition; he is also an editor of the
International Journal of Forecasting. Dr. Ord is a fellow of the
American Statistical Association and an elected member of the
International Statistical Institute.
Sandy Balkin is a Senior Consultant in Statistics Group of the
Policy Economics and Quantitative Methods Group of Ernst & Young
LLP. He recently received his Ph.D. in Business Administration
from Penn State University. Dr. Balkin specializes in business
statistics, marketing, finance, and operations research. He has
published articles on statistical design of experiments, neural
networks, and time series methodology.
Title: Hierarchical Bayesian Nonresponse Models for
Binary Data with Uncertainty about Ignorability
Speaker: Balgobin Nandram and Jai Choi
Discussant: Donald Malec, U.S. Bureau of the Census
Chair: Myron Katzoff
Date/Time: Tuesday , May 23, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics, 2 Massachusetts Ave. NE,
Room 2990 (Cognitive Laboratory), Enter at Massachusettes Avenue
and North Capitol Street (Red line: Union Station). Visitors
outside the BLS, please call Karen Jackson at (202) 691-7524
(email:Karen_Jackson@bls.gov) at least two days in advance to
have name placed on the guard's list for admittance. Please
bring a photo id.
Sponsor: WSS Public Health and Biostatistics Section and
National Center for Health Statistics.
Abstract:
We consider three Bayesian hierarchical models for
binary nonresponse data which are clustered within a number of
areas. The first model assumes the missing-data mechanism is
ignorable, and the second assumes it to be nonignorable. We
argue that discrete model expansion is inappropriate for modeling
uncertainty about ignorability. Then we use a single model
through continuous model expansion on an odds ratio ? (odds of
success among respondents versus odds of success among all
individuals) for each area. When ? =1, we have the ignorable
model, otherwise there is nonignorability. By constructing a
Bayesian credible interval, we can decide which areas have
nonignorable nonresponses. We use data from two different
household surveys, National Health Interview Survey (NHIS) and
the National Crime Survey (NCS), to illustrate our methodology
which is implemented using Markov chain Monte Carlo methods.
There are differences among the three models for estimating the
proportion of households with a characteristic (doctor visit in
NHIS and victimization in NCS), and the missing data mechanism
for some of the areas can be considered ignorable.
Key words: Model uncertainty, Model expansion, Nonignorability,
Proportion, Selection model
Topic: Stable Distributions: Models for Heavy Tailed Data
Speaker: John Nolan, American University
Chair: Bob Jernigan, American University
Day/Time: Wednesday, May 24, 2000, 12:30 - 2:00 p.m.
Location: BLS Conference Center, Room 1, Postal Square Building,
2 Massachusetts Avenue, NE, Washington, DC, 20212 (Metro Red
Line-Union Station). Use the First St. NE entrance. To be
placed on the visitor list, e-mail name, affiliation, and name of
seminar to wss_seminar@bls.gov (underscore after 'wss') by noon 1
day ahead or call Karen Jackson at 202-691-7524 at least 2 days
lead. Bring photo ID.
Sponsor: Statistical Computing Section
Abstract:
Stable random variables are the r.v.s that retain
their shape when added together. These distributions generalize
the Gaussian distribution and allow skewness and heavy tails -
features found in many large data sets from finance,
telecommunication and hydrology. We give an overview of
univariate and multivariate stable laws, focusing on statistical
applications. Examples of financial and other data sets will be
given. These distributions are now computationally accessible
and should be added to the toolbox of the working statistician.
Title: A Comparison of the Household Sector from the Flow of Funds
Accounts and the Survey of Consumer Finances
Speaker: Rochelle L. Antoniewics, Federal Reserve Board
Discussant: Barry W. Johnson, Statistics of Income, IRS
Chair: Arthur Kennickell, Federal Reserve Board
Date/Time: Thursday, May 25, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics, 2 Massachusetts Ave. NE,
Room 2990 (Cognitive Laboratory). Enter at Massachusettes
Avenue and North Capitol Street (Red Line: Union Station).
Visitors outside the BLS will need to do one of the following to
have their names put on the guard's list for admission: Call Karen
Jackson at (202) 691-7524 at least two days in advance, or email
wss_seminar@bls.gov by noon the day before the seminar and provide
the name of the seminar, a return email address and an affiliation.
Please bring a photo ID.
Sponsor: Economics Section
Abstract:
This paper compares figures on selected assets and
liabilities from the flow of funds accounts (FFA) household
sector with survey-based estimates from the 1989, 1992, and 1995
Survey of Consumer Finances (SCF). Previous studies compared
definitionally inconsistent FFA and SCF measures and, thus,
arrived at incorrect conclusions about the validity of the
estimates. This analysis addresses common misperceptions about
the definitions of the FFA household sector's assets and
liabilities and reconciles more fully the FFA and SCF wealth
components. The results show that for aggregate assets,
aggregate liabilities, and specific wealth components, such as
owner-occupied real estate, consumer credit, and home mortgage
debt, the FFA and SCF estimates are quite close in 1989 and 1992
but move apart in 1995. Also, when placed on a comparable
basis, differences between the FFA and SCF measures of savings
deposits and publicly traded corporate shares shrank from those
documented in previous studies but, nevertheless, still remain
substantial.
Topic: Bank Failures, Household Income Distribution, and
Robust Mixture Modeling
Speaker: David Scott, Rice University
Chair: Bob Jernigan, American University
Day/Time: Wednesday, May 31, 2000, 12:30 - 2:00 p.m.
Location: BLS Conference Center, Room 1, Postal Square Building,
2 Massachusetts Avenue, NE, Washington, DC, 20212 (Metro Red
Line-Union Station). Use the First St. NE entrance. To be
placed on the visitor list, e-mail name, affiliation, and name of
seminar to wss_seminar@bls.gov (underscore after 'wss') by noon 1
day ahead or call Karen Jackson at 202-691-7524 at least 2 days
lead. Bring photo ID.
Sponsor: Statistical Computing Section
Abstract:
We investigate the use of the popular nonparametric
integrated squared error criterion in parametric estimation. Of
particular interest are the problems of fitting normal mixture
densities and linear regression. We discuss some theoretical
properties and comparisons to maximum likelihood. The robustness
of the procedure is demonstrated by example. The criterion may be
applied in a wide range of models. Two case studies are given:
an application to a series of yearly household income samples as
well as a more complex application involves estimating an
economic frontier function of U.S. banks where the data are
assumed to be noisy. Extensions to clustering and discrimination
problems follow.
Title: Response Variance in the Current Population Survey Income Supplement
Speakers: Jennifer W. Reichert and John C. Kindelberger, U.S. Census Bureau
Discussant: Janice Lent, Bureau of Labor Statistics
Chair: Virginia A. de Wolf, Office of Management and Budget
Date/Time: Monday, June 5, 2000, 12:30 - 2 p.m.
Location: Bureau of Labor Statistics, Postal Square Building, Room 2990, 2 Massachusetts Avenue, NE Washington, DC 20212 (Metro Red Line; exit at Union Station). Please use the First St. NE entrance. To attend send e-mail name, affiliation, and name of seminar to wss_seminar@bls.gov(underscore after 'wss') by noon 1 day ahead or call Karen Jackson at 202-691-7524 at least 2 days ahead to be placed on the visitor list. Please bring photo ID when you come to the talk.
Sponsor: WSS Methodology Section
Abstract:
The Annual Demographic Supplement to the Current Population Survey (CPS) is the source of the annual estimate of the national poverty rate. In 1998, for the first time ever, the Census Bureau used reinterview to evaluate response error in the Supplement. Response error results from respondent errors in reporting or interviewer error in recording information in an interview. In categorical data, response error virtually guarantees bias.
The goal of the reinterview was to assess the reliability of the data from the Supplement. We describe the reinterview methodology and discuss overall results for five general sets of questions: income, public assistance, work experience, health insurance, and migration. We will highlight some specific questions from those sets and we will compare the response error for poverty and non-poverty households.
Title: Spatial and temporal trends in cancer incidence..
Speaker: Ted Holford, Professor, Division of Biostatistics, Yale University
Chair: Linda Pickle, National Cancer Institute
Date/time: Monday, June 12, 2000, 12 noon-1pm
Location: Executive Plaza North, National Cancer Institute, 1st floor Conference room G; 6130 Executive Blvd., Rockville, MD, near White Flint metro stop.
Sponsor: NCI GIS Special Interest Group and the WSS Public Health & Biostatistics section
Abstract:
Empirical Bayes and Markov Chain Monte Carlo (MCMC) methods for fitting the conditional autoregressive model are known to offer a useful way of smoothing spatial patterns in disease rates. These methods are extended to incorporate time trends, thus offering additional insight into the spread of disease over space and time. Alternative ways of graphically displaying trends in disease maps will be presented. This model can also be used to identify geographic areas that are experiencing rapid change in disease incidence. These statistical techniques will be demonstrated using breast cancer incidence data from the 169 towns of Connecticut during the years 1984-1994.
Title: A (Latin) Square Deal for Voters: Fixing a Flaw
in the Australian Preferential Voting System
Speaker: K.R.W. Brewer, Australian National University
Discussant: Lawrence R. Ernst, BLS
Chair: Mary K. Batcher, Ernst & Young (and President, WSS)
Date/Time: Tuesday, June 13, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics, Postal Square Building, Room 2990, 2 Massachusetts Avenue, NE Washington, DC 20212 (Metro Red Line; exit at Union Station). Please use the First St. NE entrance. To attend send e-mail name, affiliation, and name of seminar to wss_seminar@bls.gov(underscore after 'wss') by noon 1 day ahead or call Karen Jackson at 202-691-7524 at least 2 days ahead to be placed on the visitor list. Please bring photo ID when you come to the talk.
Sponsor: WSS President's Invited Address
Abstract:
Australian parliamentary elections use preferential voting. A candidate who has insufficient votes for election on first preferences may receive lower preference votes from candidates with still fewer votes, who have been "excluded," and eventually be elected "on preferences." If, as is often the case, more than one vacancy is being filled at the same time, candidates may also receive lower preference votes from the "surpluses" of candidates who have more than fulfilled the requirement that they must have at least the required "quota" to secure election.
Complications arise where voters are essentially indifferent between rival candidates from the same party and vote "1, 2, 3, ..." down their chosen party's list ("party linear" voting). In 1979 a scheme called "Robson Rotation" was introduced in the State of Tasmania in which the party's list would be presented in c column orderings, where c is the number of candidates in the party's list, the columns being headed by each of the party's candidates in rotation, and the remaining names in each column being determined by a Latin square design.
When the Australian Capital Territory also adopted Robson Rotation in 1995, the extent of party linear voting was much greater than in Tasmania, and evidence soon appeared that a single Latin Square was inadequate to put candidates on an equal footing. In 1998 it was obvious that two and probably three out of the 17 successful candidates for the ACT's Legislative Assembly had been elected "by the luck of the draw" over candidates with greater popular support. The Canberra Branch of the Statistical Society of Australia took the initiative to find optimal experimental designs for the purpose, and it seems probable that these (or schemes closely based on the same idea) will be used in the 2001 elections.
For more information, see Professor Brewer's report of Robson rotation on the Statistical Society of Australia, Canberra Branch, webpage: http://www.ozemail.com.au/~ssacanb.
Topic: Automated Multivariable Time Series Analysis of Industrial and Econometric Data
Speaker: Wallace E. Larimore, Adaptics, Inc.
Discussant: Nancy J. Kirkendall, Energy Information Administration
Chair: Linda Atkinson, Economic Research Service
Day/Time: Wednesday, June 14, 2000, 1:00 - 2:30 p.m. (NOTE SPECIAL TIME)
Location: Bureau of Labor Statistics, Postal Square Building, Room 2990, 2 Massachusetts Avenue, NE Washington, DC 20212 (Metro Red Line; exit at Union Station). Please use the First St. NE entrance. To attend send e-mail name, affiliation, and name of seminar to wss_seminar@bls.gov(underscore after 'wss') by noon 1 day ahead or call Karen Jackson at 202-691-7524 at least 2 days ahead to be placed on the visitor list. Please bring photo ID when you come to the talk.
Sponsor: Economics Section
Abstract:
Automatic statistical methods have recently been developed for modeling multivariable time series from observational input/output data. This has been applied to a number of difficult industrial and econometric problems resulting in major improvements. In this presentation, a tutorial is given of the primary elements of this new technology, followed by a discussion of some significant applications. The statistical modeling involves linear, time invariant dynamical processes with noise disturbances, possibly inputs and feedback, and includes determination of the system state order.
The basic method involves a canonical variate analysis that, for each potential state order, gives an optimal statistical selection of the system states. The computation involves primarily a singular value decomposition that is always computationally stable and accurate. For model state order selection, an optimal statistical procedure is used, namely a small sample version of the Akaike information criterion. The accuracy of the method is close to the optimal lower bound achieved by maximum likelihood for large samples. The resulting procedure is completely automatic and suitable for online time series analysis of high-order dynamic processes.
This technology has been widely applied in both academic and industrial settings to a variety of problems involving high-order multivariable processes that are possibly unstable, non-minimum phase, and/or involve nonstationary noise, stiff dynamics, unknown feedback and delays. This presentation describes a number of applications to the analysis of causality and feedback in monetary data, detection of abrupt system changes, industrial process monitoring, and adaptive modeling and online adaptive control. Automated multivariable time series analysis is a critical technology that is necessary to enable wide scale industrial automation and data mining of time series.
Title: The Influence of Environmental Characteristics on Survey Cooperation: A Comparison of Metropolitan Areas
Speakers: Brian A. Harris-Kojetin, The Arbitron Company, and
Scott S. Fricker, U.S. Bureau of Labor Statistics
Discussant: To be announced
Chair: Virginia de Wolf, Office of Management and Budget
Date/Time: Monday, June 26, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics, Postal Square Building, Room 2990, 2 Massachusetts Avenue, NE Washington, DC 20212 (Metro Red Line; exit at Union Station). Please use the First St. NE entrance. To attend send e-mail name, affiliation, and name of seminar to wss_seminar@bls.gov(underscore after 'wss') by noon 1 day ahead or call Karen Jackson at 202-691-7524 at least 2 days ahead to be placed on the visitor list. Please bring photo ID when you come to the talk.
Sponsor: WSS Methodology Section
Abstract:
A request for survey participation takes place within a broad context - a social and economic environment that can vary over time, across societies, or even across different geographic areas within a society. There are many examples of differences in nonresponse across different areas within a country, particularly distinctions observed between urban and rural; however, there is much less documentation of the varying social and economic conditions that may underlie these environmental differences in response rates. Recent research in social psychology has focused on specific characteristics of communities to try to understand some of the aspects of the environment that underlie differences in people's helping behavior. For example, Levine and his colleagues (1994) examined six different types of helping behavior in 36 cities and identified demographic, social, and economic characteristics of these communities that was related to the level of helping behaviors observed.
In this paper, we examine a number of indicators of the demographic, social, and economic environment from a number of sources, including Census data, to construct composite indicators that reflect social psychological attributes of metropolitan areas in the United States. We will then examine how well these indicators are related to differing levels of survey cooperation rates across metropolitan areas in the United States in two major national surveys. Finally, we discuss the implications of these findings for theories of survey cooperation and for improving data collection procedures.
Day/Time: Wednesday, June 28, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics, Postal Square Building, Room 2990, 2 Massachusetts Avenue, NE Washington, DC 20212 (Metro Red Line; exit at Union Station). Please use the First St. NE entrance. To attend send e-mail name, affiliation, and name of seminar to wss_seminar@bls.gov(underscore after 'wss') by noon 1 day ahead or call Karen Jackson at 202-691-7524 at least 2 days ahead to be placed on the visitor list. Please bring photo ID when you come to the talk.
Co-Sponsors: Social & Demographics Section And DC-AAPOR
Abstract:
The explosive growth of information on the World Wide Web has revolutionized personal, professional, and business practices. Five years ago, demographic data were only accessible to a limited audience of issue specialists. Today, anyone with access to the Internet can view and download demographic data from a wide variety of government and private Web sites (e.g., American Factfinder, FedStats, Ferret, PDQ-Explore, Ameristat). With increased access to data, there are also greater risks of misinterpreting important economic, social, and demographic trends, especially among non-technical users. The Population Reference Bureau is working in collaboration with Bill Frey of SUNY, Albany to develop a new Web site, Ameristat.org, a summary of the latest U.S. demographic trends and their consequences. The goal is to use Internet technologies to increase public awareness and understanding of demographic data.
Speakers: Ismael Flores Cervantes, Westat
Gary Shapiro, Westat
Paula Weir, Energy Information Agency
Nileeni Meegama, Survey Research Center,
University of Maryland
Date: July 10, 2000, Monday 12:30-2:00 p.m.
Location: Bureau of Labor Statistics, Postal Square Building, Room 2990, 2 Massachusetts Avenue, NE Washington, DC 20212 (Metro Red Line; exit at Union Station). Please use the First St. NE entrance. To attend send e-mail name, affiliation, and name of seminar to wss_seminar@bls.gov(underscore after 'wss') by noon 1 day ahead or call Scott Fricker at 202-691-7390 at least 2 days ahead to be placed on the visitor list. Please bring photo ID when you come to the talk.
Sponsor: WSS Data Collection Methods Section and AAPOR-DC
Abstract:
There will be four papers presented in the by the panel members on recent CATI and RDD developements:
Evaluation of the Use of Data on Interruption in Telephone Service (Ismael Flores-Cervantes, J. Michael Brick, Kevin Wang and Tom Hankins)
Bias From Excluding Households without Telephones in Random Digit Dialing Surveys - Results of Two Surveys (Gary Shapiro, Ismael Flores-Cervantes, John Hall, and Genevieve Kenney)
A Comparison and Evaluation of Two Survey Data Collection Methodologies: CATI vs. Mail (Paula Weir, Sherry Beri and Benita O'Colmain)
The Effects of Telephone Introductions on Cooperation: An Experimental Comparison (Nileeni Meegama and Johnny Blair)
Title: Construction of efficient one-level rotation sampling
designs
Speaker: You Sung Park, Korea University
Discussant: Patrick Cantwell
Chair: Jai W. Choi
Date/Time: Tuesday, July 11, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics, Postal Square Building, Room 2990, 2 Massachusetts Avenue, NE Washington, DC 20212 (Metro Red Line; exit at Union Station). Please use the First St. NE entrance. To attend send e-mail name, affiliation, and name of seminar to wss_seminar@bls.gov(underscore after 'wss') by noon 1 day ahead or call Karen Jackson at (202) 691-7524 at least 2 days ahead to be placed on the visitor list. Please bring photo ID when you come to the talk.
Sponsor: Public Health and Biostatistics Section, Washington
Statistical Society, Korea University and National Center for
Health Statistics.
Abstract:
We introduce the formal rules how to construct the 2-way balanced one-level rotation design for which balancing is done on interview scheme in monthly sample and in rotation group. We provide the necessary and sufficient condition for 2-way balancing and an algorithm to construct such a design. From this design, we obtain a generalized composite estimator (GCE) and minimum linear unbiased estimator (MVLUE). The variance of GCE and MVLUE are presented when we consider two types of correlations among the subunits of a group, and variables depend on the number of interview times. Minimizing this variance, we derive the optimal coefficients of the GCE. The efficiency of the GCE with the optimal coefficients is compared to that of MVLUE and of other GCE with the fixed coefficients. We generate a family of two balanced one-level rotation designs, and show the efficiency of these and 4-8-4 designs.
Title: Some Practical Aspects of Disclosure Analysis
Speakers: Kenneth Rasinski, National Opinion Research Center, University of Chicago, and Douglas Wright, Office of Applied Statistics, Substance Abuse and Mental Health Services Administration
Discussant: Paul Massell, Census Bureau
Chair: Joseph Clements, Bureau of Labor Statistics
Date/Time: Tuesday, July 18, 2000, 12:30 - 1:45 p.m.
Location: Bureau of Labor Statistics, Postal Square Building, Room 2990, 2 Massachusetts Avenue, NE Washington, DC 20212 (Metro Red Line; exit at Union Station). Please use the First St. NE entrance. To attend send e-mail name, affiliation, and name of seminar to wss_seminar@bls.gov(underscore after 'wss') by noon 1 day ahead or call Karen Jackson at (202) 691-7524 at least 2 days ahead to be placed on the visitor list. Please bring photo ID when you come to the talk.
Sponsor: WSS Methodology Section
Abstract:
Disclosure analysis consists of a set of procedures applied to a data set to (1) ascertain the risk that an individual or organization whose information appears in the data can be identified, and (2) lower that risk to an acceptable level through sampling cases, eliminating variables, or manipulating data. Disclosure analysis is usually conducted when data collected under the promise of confidentiality are to be released to the public. While there has been a substantial amount of statistical theory developed around disclosure techniques (REFS) our concern is with practical solutions to disclosure problems. We base our discussion on our experiences with disclosure analyses we have conducted with files of different types and levels. In this paper we discuss the purpose of disclosure analysis and types of disclosure problems, focusing on the distinction between direct and inferential disclosure. We present a technique for determining which information is potentially disclosive that may help ease the tension between analysts, who want as much information as possible, and data collectors, who want to preserve the confidentiality of their respondents. We also examine the tension between statistical bias and confidentiality. In the course of our work we have come across techniques to apply when conducting disclosure analysis. We discuss each of these techniques and show have they are applicable to large or small data sets and to single or multi-level data.
Topic: Generalized Linear Models for Sample Surveys
Speaker: Stephen J Haslett, Statistics Research and Consulting Centre, Massey University (New Zealand)
Discussant: John Eltinge, Bureau of Labor Statistics
Chair: William Davis, National Cancer Institute
Date: Tuesday, September 12, 2000, 12:30-2:00 p.m.
Location: Bureau of Labor Statistics, Conference Center, Room
G440, Postal Square Building (PSB), 2 Massachusetts Avenue, NE, Washington, DC. Please use the First St., NE, entrance to the PSB. To gain entrance to BLS, please see "Notice" above.
Sponsor: WSS Methodology Section
Abstract:
Generalized linear models provide an important extension to linear models. The general class includes as some special cases: linear models with uncorrelated or correlated error structure, multilevel models, loglinear models, and Poisson and logistic regression. A number of papers over the last twenty years have considered fitting regression models or small area estimates. This previous research has looked at using the inverse selection probabilities as weights, but the joint selection probabilities have been ignored. How best to incorporate both the unequal selection probabilities and the joint selection probabilities (such as occur in clustered or stratified sample designs) when fitting generalized linear models with fixed, random or mixed model parameters has remained a substantially unanswered question. The role of the joint selection probabilities even the linear model case with fixed model parameters has not been clarified previously, except for the simplest case of a pure design error model, for which it will be shown that estimation of a mean or total leads to the Horvitz-Thompson estimator. This paper considers the role of both the selection and joint selection probabilities in unbiased estimation for generalized linear models with random, fixed or mixed parameters. The general problem and its solution are discussed in a joint design / superpopulation context, and a class of generalized linear models is developed that allows for incorporation of both superpopulation structure and the first and second order properties of the randomisation distribution induced by the survey design. For optimal design, the relationship between the superpopulation structure and selection and joint selection probabilities will be shown to be of central importance. Some results will be given on choice of selection and joint selection probabilities for a complex sample that ensure good estimates for parameters in generalized linear models.
This paper investigates predictors of nonresponse rates for a panel survey (i.e.: The Current Population Survey) using logistic models. The types of predictors include interviewer work characteristics (e.g., workload, number of attempted contacts), and household characteristics (e.g., age, gender of respondent). Much previous research has examined simple effects to predict interviewer or household nonresponse rates. A recent review can be found in Groves and Couper (1998). In contrast, the present study examines confounding and interaction effects between the predictors. Confounding effects occur when two predictors share the same relationship with the interviewer nonresponse rate. Interaction effects occur when the relationship between a predictor and the interviewer nonresponse rate depends on another variable.
Note: If you did not get an e-mail notice of this meeting but want one for future meetings, please contact dc-aapor.admin@erols.com.
Title: An Algorithm for the Distribution of the Number of Successes in Fourth- or Lower-Order Markovian Trials
Speaker: Donald Martin, Howard University
Discussant: Benjamin Kedem, University of Maryland
Chair: Michael Greene, Consumer Product Safety Commission
Date: Thursday, September 14, 2000, 10:00-11:30 a.m. (NOTE SPECIAL TIME)
Location: Bureau of Labor Statistics, Conference Center, Room G440, Postal Square Building (PSB), 2 Massachusetts Avenue, NE, Washington, DC. Please use the First St., NE, entrance to the PSB. To gain entrance to BLS, please see "Notice" above.
Sponsor: WSS Methodology Section
Abstract:
Many statistical applications may be modeled as a sequence of n dependent trials, with outcomes that may be classified as either a "success" or a "failure". In this talk we present and algorithm that may be used to compute the distribution of the number of successes in such sequences. We assume that the probability of success on the nth trial depends on the outcome of trials n - v, n - v + 1, ..., n - 1, for some value of v, but is independent of trials before n - v. The algorithm extends algorithms given by Kedem for v = 1 and v = 2 to the case where v = 4. The importance of selecting an appropriate value for v when modeling dependent data is discussed. We also discuss the application of the algorithm to the selection of v, and to the computation of waiting time distributions
Title: Use of Hierarchical Modeling in Substance Abuse Surveys
Speakers: Georgiy Bobashev, Research Triangle Institute; Douglas Wright, Substance Abuse and Mental Health Services Administration; and
Zhiwei Zhang, National Opinion Research Center
Discussant: Michael P. Cohen, Bureau of Transportation Statistics
Chair: Dwight Brock, National Institute on Aging
Date: Friday, September 22, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics, Conference Center, Room G440, Room 9, Postal Square Building (PSB), 2 Massachusetts Avenue, NE, Washington, DC. Please use the First St., NE, entrance to the PSB. To gain entrance to BLS, please see "Notice" above.
Sponsor: WSS Methodology Section
Abstract:
Hierarchical Modeling (HM) is a methodology that recognizes the role that the hierarchical structure can play in analysis and adjusts for this in an appropriate manner. This talk will explore the application of HM to the National Household Survey on Drug Abuse (NHSDA). The initial goal of that research was to determine the impact of ignoring levels of the hierarchy above the person level. Much of the analysis of relationships of other variables to drug use in this field has been limited to simple person-level logistic regressions (using sample weights). The 1997 NHSDA was a nested sample of Primary Sampling Units (typically counties or groups of counties), segments (specially designed combinations of blocks and block groups), households, and persons (one or two per selected household).
We explore some practical considerations as to having sufficient numbers of observations at each level and a brief discussion of use of weights (we don't use them). The discussion will include both continuous drug-related scales and dichotomous variables (use or non-use in the past year of marijuana). The focus is on considerations of variance decomposition, especially for the dichotomous case. The discussion includes a methodology for taking the reported variances from a two-level hierarchy, variances that are in the log odds scale, and converting them to variances in the original scale (reported at the 1999 JSM in Baltimore, MD). We believe we have a way to extend this to 3 or more levels. The relative sizes of variance components are important in the area of Drug Prevention Programs in that they have implications for the relative importance of Drug Programs aimed at the person, family, and neighborhood levels. We will conclude with some of our current research on variance components and the use of sample weights.
Title: Control Charts as a Tool in Data Quality Improvement
Speaker: Carl E. Pierchala and Jyoti Surti, National Highway Traffic Safety Administration
Chair: Amrut Champaneri, Bureau of Transportation Statistics
Date/Time: Tuesday, October 3, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics, Cognitive Laboratory, Room 2990, Postal Square Building (PSB), 2 Massachusetts Avenue, NE, Washington, DC. Please use the First St., NE, entrance to the PSB. To gain entrance to BLS, please see "Notice" above.
Sponsor: WSS Quality Assurance Section
Abstract:
A novel method of using control-charting has been
successfully applied to two National Highway Traffic Safety
Administration data systems to help improve and assure the
quality of their data. The approach, requiring only the existing
data, differs from the data control and data tracking methods
previously described in the literature. Using this method,
problems in data quality may be detected and dealt with far in
advance of the release of a data base to the user community.
This talk describes the methods used, illustrates the approach
through various examples, and discusses various technical issues
in applying control charts to these traffic safety data. The
talk also explains the rationale of the methods in terms of
statistical process control logic. Finally, an example of
nonrandomly missing data is given.
Important Note:
This seminar is to be shown at BLS Conference Center,
Room 1; Census 4, 3225 ; NCHS, Auditorium 11th Floor; and Westat,
IRC Reading Room on RE 40F. The October 5 seminar titled "The
Reluctant Embrace of Law and Science" is to be shown at BLS
Conference Center, Room 9 & 10; Census 4, 3225; and Westat, IRC
Reading Room on RE 40F. The October 10 seminar titled "Data
Presentation B A Guide to Good Graphics and Tables" is to be
shown at BLS Conference Center, Room 9 & 10; Census 4, 3225; USDA
ERS Waugh Auditorium B; Westat, IRC Reading Room on RE 40F; NSF-
Room 350; and NCHS, Auditorium 11th Floor.
The site facilitators are Stuart Scott/BLS at (202) 691-7383 and
Glenn White/EY at (202) 327-6414 for BLS, Maribel Aponte at (301)
457-3480 for Census, Linda Atkinson at (202) 694-5046 for USDA
ERS, Hongsheng Hao at (301) 738-3540 for Westat, Ron Fecso at
(703) 292-7769 for NSF, and Joe Fred Gonzales at (301) 458-4239
or Iris Shimazu at (301) 458-4497 for NCHS.
The technical contacts are Mark Wisnieski/BLS at (202) 691-7535
for BLS, Barbara Palumbo at (301) 457-4974 for Census, Bob
Donegan at 692-5063 for USDA ERS, Jane McGrath at (301) 251-4375
at Westat, Edward Yu at (703) 292-8024 for NSF, and Chandra
Singleton at (301) 458-4628 for NCHS.
WSS Data Collection Methods Section
and the
American Association for Public Opinion Research
Washington/Baltimore Chapter
Topic: Interdisciplinary Survey Research Involving the Computer and Cognitive Sciences: Cognitive Issues in the Design of Web Surveys
Date/Time: Tuesday, October 3, 2000, 12:30-1:30 p.m.
Speaker: Roger Tourangeau, University of Michigan
Location: BLS Conference and Training Center, Room #2, Postal
Square Building, 2 Massachusetts Ave., NE Washington, DC (Enter
on First St., NE, and bring a photo ID)
We describe the results of an experiment on Web
surveys. Many studies have demonstrated the advantages of
self-administration, which include increased reporting of
sensitive information and decreased interviewer effects.
Computer administration of survey questions appears to combine
these advantages of self-administration with the added advantages
of computer assistance. Still, a growing body of evidence
suggests that features of the computer interface can elicit
reactions similar to those triggered by human interviewers. Our
experiment examined features of the interface thought to create a
virtual social presence. We varied whether or not the electronic
questioner is identified by name ("Hi! I'm John") and whether or
not it offers explicit reminders of prior answers. The main
hypothesis to be tested in the study is that the more the
interface creates a sense of social presence, the more
respondents will act as if they are interacting with another
human being. The major effects of social presence will be lower
levels of reporting sensitive information; at the same time,
rates of missing data may be reduced. Thus, the analyses examine
both unit and item nonresponse and levels of reporting. The study
is designed to begin to fill an important gap in knowledge about
the impact of Web data collection on data quality and to address
important theoretical concerns about socially desirable reporting
and interacting with computers.
Title: The Reluctant Embrace of Law and Statistics
Speaker: Joe S. Cecil, Ph.D., J.D., Federal Judicial Center
Discussant: Joseph L. Gastwirth, George Washington University
Chair: John Bosley, Bureau of Labor Statistics
Date/Time: Thursday, October 5, 2000, 12:00 - 1:30 p.m.(NOTE SPECIAL TIME)
Location: Bureau of Labor Statistics, Conference Center, Room G440, Postal Square Building (PSB), 2 Massachusetts Avenue, NE, Washington, DC. Please use the First St., NE, entrance to the PSB. To gain entrance to BLS, please see "Notice" at the top of the page.
Sponsor: WSS Methodology Section
Abstract:
In three recent decisions the Supreme Court of the United States has established new standards for considering expert evidence, including evidence offered by statisticians. This presentation will review the emerging legal standards for expert testimony, the problems that arise with such evidence, and opportunities for improving the quality of scientific testimony offered in litigation. Particular attention will be paid to the use of court-appointed experts and the Federal Judicial Center's Reference Guide on Statistics (www.fjc.gov/EVIDENCE/science/sc_ev_sec.html).
Title: TUTORIAL: Data Presentation -- A Guide to Good Graphics and Tables
Speaker: Marianne W. Zawitz, Bureau of Justice Statistics
Chair: Virginia de Wolf, Office of Management and Budget
Date/Time: Wednesday, October 11, 2000, 12:30 - 2:00 p.m.
Location: Bureau of Labor Statistics, Conference Center, Room
G440, Postal Square Building (PSB), 2 Massachusetts Avenue, NE,
Washington, DC. Please use the First St., NE, entrance to the
PSB. To gain entrance to BLS, please see "Notice" at the top of this page.
Sponsor: WSS Methodology Section
Abstract:
Quality data presentations ensure user understanding
by taking advantage of how users already process information,
reduce the number of thought processes required to understand the
data, and breakdown fundamental obstacles to understanding. This
workshop will cover when to use graphics and tables, using your
data to determine the type of graphic or table, the elements of
good graphics and tables, and achieving clarity in presentation.
Based on the principles set forth by Edward Tufte and William
Cleveland, this is a practical workshop to show participants how
to improve their presentations of quantitative data. The
tutorial is presented by Marianne W. Zawitz of the Bureau of
Justice Statistics (BJS), the statistical agency of the U.S.
Department of Justice. She is the creator and content manager
of the BJS Web site (http://www.ojp.usdoj.gov/bjs/).
ASA Seminar Reprise:
Research on Government Survey Nonresponse
Part I
Date and Time: Thursday, November 16, 2000, 12:30-2:00
Location: BLS Conference Center, Room 2, Postal Square Building,
2 Massachusetts Ave.., NE Washington, DC (enter on First St., NE,
and bring photo ID). The Census Bureau will provide video
conferencing at 12:30-2:00 in Room 3225/4.
Metro: Union Station, Red Line
Title: The Last Five Percent: What Can We Learn From Difficult/Late Interviews?
Speaker: Nancy Bates, U.S. Census Bureau
Abstract:
A few studies have examined nonresponse and the impact
it has on survey estimates (e.g., Tucker and Harris-Kojetin 1998;
Harris-Kojetin and Robison 1998). Less research has focused
specifically on the characteristics of late or "difficult" cases
that comprise the last few percentage points of survey response
rates -- particularly for personal surveys. To address this
topic, we examine several characteristic of late/difficult cases
from the Current Population Survey (CPS) and the National Crime
Victimization Survey (NCVS). First, we explore whether the
household and demographic characteristic
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