IASS - A Practical Guide for NSOs on Addressing Nonresponse Bias in Social Surveys
| Datum | 19 May 2026 |
| Tijd | 14:30 CEST - 16:00 CEST |
| Level of instruction | |
| Instructor |
Cilanne Boulet
Eric Lesage
Kenza Sallier
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| Registration fee | |
Webinar Abstract
The HLG-MOS ASCENT Project (Advanced Survey Cost-Effectiveness with Nonresponse Treatment) is an international initiative led by Statistics Canada in collaboration with 13 National Statistical Offices (NSOs). It responds to the growing challenge of declining response rates and increasing risks of nonresponse bias in social surveys, within a context of constrained resources and rising demand for timely, disaggregated statistics. This presentation introduces the ASCENT guide, a set of practical, use-case-oriented principles and tools designed to support NSOs in reducing nonresponse bias within existing survey systems. The guide focuses on short- to medium-term, implementable strategies grounded in the Total Survey Error framework and aligned with international statistical standards. It brings together multiple complementary areas of work: multi-mode collection strategies and weighting adjustments, subsampling of nonrespondents with targeted follow-up, and enhanced calibration and responsive design approaches. These methods aim to improve accuracy while maintaining operational feasibility and cost-effectiveness. The objective is to provide NSOs with practical guidance to improve the quality and reliability of social survey outputs, strengthen comparability across countries, and support evidence-based decision-making in an increasingly complex data environment.
Instructors
About the instructor
Section Chief in the Social Statistics Method Division at Statistics Canada
Cilanne Boulet has been working as a methodologist at Statistics Canada since 2011 and is currently Section Chief in the Social Statistics Methods Division. She has worked on a wide range of social statistics programmes. Her team’s current focus is developing the methodology for new social data collection initiatives.
About the instructor
Head of the Statistical Methods Department at INSEE, France’s National Institute of Statistics and Economic Studies
The Statistical Methods Department is a hub for statistical methodology expertise across the public statistics sector. Its areas of specialisation include survey sampling, seasonal adjustment techniques, coding, questionnaire design, statistical disclosure control and geographic information systems. Dr Lesage has held various expert positions in survey methodology at Statistics Canada, ENSAI and INSEE. His areas of expertise include the treatment of non-response, calibration, and conditional inference.
About the instructor
Senior Strategic Advisor – Strategic Data Management, Methods and Analysis Field at Statistics Canada
Kenza Sallier has worked on redesigning how large-scale statistical surveys are planned and produced, with a focus on cost-effectiveness, nonresponse bias, and modernization of official statistics. She leads Canada’s work on defining official statistics and advises senior leadership on AI strategy, governance, and methodological priorities. She also leads the UNECE ASCENT project, coordinating 13 countries to develop practical guidance on improving survey efficiency and addressing nonresponse bias. Her expertise includes synthetic data and advanced statistical methods to support more robust, efficient, and future-ready data production systems.