The 2019 ITSEW will be held on June 10-12 at the University of Bergamo, Italy. Before the start of the workshop on Monday 10, there will be a short primer on Total Survey Error. The workshop will feature a keynote address by a keynote speaker to be defined.

ITSEW is aimed at statisticians, survey managers and methodologists, pollsters, public opinion researchers, and marketing research professionals focused on survey quality and the challenges of combined data products. Through presentations and exchange of information the workshop aims to support a better understanding of total survey error.

The theme of the 2019 workshop is Integration of surveys and alternative data sources.

We welcome submissions on any topic related to total survey error, but especially encourage contributions on:

• Total error frameworks for Big Data, integrated data sets and products
• "Total statistical uncertainty" frameworks for estimates derived from nonprobability samples
• Statistical disclosure limitation error
• Uses of administrative data to reduce TSE
• Methods for addressing specification errors in integrated data sets
• Minimizing TSE by adaptive design and data collection strategies.

If you would like to present research at the workshop, please submit an abstract (max. 400 words) to itsew2019@unibg.it by the end of February. Please indicate whether you would like to present a paper or a poster. Presentations on research still in progress are highly encouraged. Be prepared to share a (preliminary) paper with the organizers prior to the workshop so that all attendees can prepare for discussion. Futher information are available at the 2019 ITSEW website.
 

Deadlines
Abstracts submission: February 28, 2019
Authors notifications: March 31, 2019
Paper submission: May 31, 2019
Registration: to be defined
Hotel reservation: rooms availability guaranteed until April 30, 2019

Organizing Committee

• Annamaria Bianchi - Department of Management, Economics, and Quantitative Methods, University of Bergamo, Italy
• Silvia Biffignandi - Department of Management, Economics, and Quantitative Methods, University of Bergamo, Italy
• Ruben Bach - University of Mannheim
• Paul P. Biemer - RTI International, The Odum Institute for Research in Social Science at the University of North Carolina
• D. Sunshine Hillygus - Duke University
• Alan F. Karr - RTI International
• Olga Maslovskaya - University of Southampton
• Kathrin Thomas - Princeton University