The International Total Survey Error Workshop (ITSEW) brings together survey researchers, practitioners, and methodologists (especially in national statistics offices) to foster exchange of ideas and preliminary research findings toward a better understanding of total survey error. It has been held annually since 2005 and typically gathers 50-60 attendees.
The goals of the workshop include
- Reviewing progress on important TSE problems
- Defining current data quality problems in detail, and articulating a research agenda to address them
- Forming research collaborations to carry out needed research
- Identifying emerging research needs at an early stage
ITSEW 2018 in Durham, North Carolina
The 2018 ITSEW was held June 4-6 in Durham, North Carolina. Hosted by the Duke Initiative on Survey Methodology and The Odum Institute for Research in Social Science at the University of North Carolina, the event was held in vibrant downtown Durham at MDC.
The workshop featured a keynote address by Dr. Roger Tourangeau, Vice President at Westat and past president of the American Association for Public Opinion Research (AAPOR).
The theme of the workshop was “Approaches for Mitigating Total Survey Error (TSE) and Its Effects.” Consistent with this theme, we are especially interested in topics such as adaptive design and data collection strategies, methods for combining and analyzing data from multiple sources, and minimizing TSE when using non-probability surveys.
D. Sunshine Hillygus, Professor of Political Science and Public Policy, Duke University
Ruben Bach, University of Mannheim
Annamaria Bianchi, Department of Management, Economics, and Quantitative Methods, University of Bergamo, Italy
Paul P. Biemer, RTI International, The Odum Institute for Research in Social Science at the University of North Carolina
Alexandra Cooper, Duke’s Social Science Research Institute, Duke Initiative on Survey Methodology
David Dolson, Statistics Canada
Teresa P. Edwards, The Odum Institute for Research in Social Science at the University of North Carolina
Alan Karr, RTI International
Reports and Presentations from ITSEW 2018
Panel 1.1: Data Quality
- A Methodological Framework for the Analysis of Panel Conditioning Eﬀects
- Dependent Interviewing
- Understanding the Determinants of Reliability
Panel 1.2: TSE and Managing the Interviewing Process
- Is interview length associated with propensity to consent to blood draw?
- Improving Adherence to Area Probability Sample Designs
- Interviewer Effects on Responses to Sensitive Questions
Panel 1.3: Social Media and New Uses of Media Tools
- Can Big Data provide good quality statistics?
- Presentation: Comparison Between Redirected Inbound Call Sampling Surveys and Outbound Telephone Surveys
Panel 1.4: Measurement
- Total Error and Variability Measures with Integrated Disclosure Limitation for Quarterly Workforce Indicators and LEH
- So many questions, so little time
Panel 2.1: TSE: Education & Applications
- Further Raising Awareness of Survey Practitioners on the Usefulness of the Total Survey Error Paradigm
- The Total Survey Error Paradigm and Challenges to its Application in the Arab World
- How Big of a Problem is Analytic Error in Secondary Analyses of Survey Data?
- Presentation: The Problem of Analytic Error in Secondary Analysis of Survey Data
Panel 2.2: Understanding Survey Response and Panel Attrition
- Designing Surveys to Account for Endogenous Non-Response
- Presentation: Nonresponse Bias in a Nationwide Dual-Mode Survey
Panel 2.3: Non-response, Coverage Errors, and Imputation
- Polling bias and undecided voter allocations
- Presentation: Polling bias and undecided voter allocations in US Presidential elections, 2004–2016
- Estimating Smooth Country-Year Panels of Public Opinion
- How Respondent Demographics and Survey Design Interact to Affect Item Nonresponse
- Presentation: How Respondent Demographics and Survey Design Interact to Affect Item Nonresponse and Data Quality
Panel 2.4: Propensity Scores in TSE
- Estimating mode Effects Using Propensity Score Methods in Community Life Survey
- Measurement Error in Contact Para Data and its Relationship to Response Propensity
Panel 3.1: Linkage