Program and contributions - 2021 International Methodology Symposium

The proceedings of the Symposium are available. Please visit the Statistics Canada International Symposium Series: Proceedings catalogue page to access the papers for the presentations.

All times listed in the schedule refer to Eastern Daylight Time (EDT): UTC-4

Friday October 15, 2021

09:15 – 09:30
Opening Remarks

  • Anil Arora, Chief Statistician of Canada, Statistics Canada, Canada

09:30 – 10:30
Session 1 -- Keynote Address

Chairperson: Sevgui Erman

  • Recent progress and upcoming challenges for research in machine learning
    Yoshua Bengio, Mila - Québec Artificial Intelligence Institute, Canada

10:30 -- 10:45
Morning Break

10:45 -- 12:00
Session 2A -- Inference from non-probability samples

Chairperson: Jean-François Beaumont

  • Survey data integration for regression analysis using model calibration
    Jae-Kwang Kim, Iowa State University, USA
  • Robust Bayesian inference for count data with varying exposures in non-probability samples using Gaussian processes of propensity prediction
    Ali Rafei, University of Michigan, USA
  • Advances in the use of auxiliary information for estimation from nonprobability samples
    Ramon Ferri Garcia, Universidad de Granada, Spain

10:45 -- 12:00
Session 2B -- Visualization and Mapping of Image Data

Chairperson: Hélène Bérard

  • Modernizing Construction Indicators Through Machine Learning and Satellite Imagery
    Aidan Smith, U.S. Census Bureau and Hector Ferronato, Reveal Global Consulting, USA
  • Statistics Canada's Seasonal Adjustment Dashboard
    François Verret, Statistics Canada, Canada
  • Diagnosis of Connectivity in Brazilian Education, an approach to support the formulation of public policies for connectivity in education.
    Paulo Kuester Neto, Brazilian Network Information Center, Brazil
  • Multifactor Productivity Interactive Tool
    Ken Peng, Ryan Macdonald and Claudiu Motoc, Statistics Canada, Canada

12:00 – 12:30
Afternoon Break

12:30 – 13:45
Session 3A -- Quality Considerations when Using Machine Learning in the Production of Statistics

Chairperson: Wesley Yung

  • With machine learning comes great power, let's be responsible!
    Keven Bosa, Statistics Canada, Canada
  • Design-unbiased statistical learning
    Li-Chun Zhang, University of Southampton, United Kingdom
  • Random Forest models, a proposal for the analysis of selective editing strategies
    Roberta Varriale, ISTAT, Italy

12:30 – 13:45
Session 3B -- Innovative solutions in social applications

Chairperson: Martin Renaud

  • Leveraging the power of administrative data through the Longitudinal Social Data Development Program
    Larry MacNabb and Jenneke Le Moullec, Statistics Canada, Canada
  • Predicting transitions into and out of poverty using machine learning
    Joep Burger and Jan van der Laan, Statistics Netherlands, the Netherlands
  • Bridging the gap between the displaced and in-demand occupations
    Vishal Subramanian Balashankar, Badri Venkataraman and Chris Astle, Cybera, Canada
  • Machine Learning for estimating heterogeneous treatment effects in program evaluations
    Yves Gingras, Leeroy Tristan Rikhi and Andy Handouyahia, Employment and Social Development Canada, Canada

13:45 – 14:15
Networking Event

Friday October 22, 2021

10:00 – 11:00
Session 4 -- In Memoriam of Professor Chris Skinner

Chairperson: Danny Pfeffermann

  • Statistical Disclosure Control and Developments in Formal Privacy – Notes from Chris Skinner's Waksberg Lecture
    Natalie Shlomo, University of Manchester, United Kingdom

11:00 – 11:15
Morning Break

11:15 -- 12:30
Session 5A -- Issues of Ethics and Privacy in the Application of Data Science in Official Statistics

Chairperson: Martin Beaulieu

  • Explaining Explanations for Trustworthy Decision Making
    Leilani Hendrina Gilpin, Sony AI / MIT Computer Science and Artificial Intelligence Laboratory, USA
  • Mitigating Algorithmic Discrimination in AI
    Golnoosh Farnadi, HEC Montreal, Canada
  • Empowering analysts to consider the ethics of their work: A case study of the UK Statistics Authority's data ethics framework
    Simon Whitworth, United Kingdom Statistics Authority, United Kingdom

11:15 -- 12:30
Session 5B -- Quality and Measurement Error

Chairperson: Fritz Pierre

  • Creation of a Composite Quality Indicator for Estimates Based on Administrative Data Using Clustering
    Roxanne Gagnon, Martin Beaulieu, Danielle Lebrasseur, Wei Qian and Anthony Yeung, Statistics Canada, Canada
  • Urban Tree Measurement Error and the Additional Uncertainty in Estimates of Ecosystem Services
    James Westfall, Jason G. Henning and Christopher B. Edgar, U.S. Forest Service, The Davey Institute and University of Minnesota, USA
  • Administrative data for the estimation of population: statistical learning from the first waves of the Italian Permanent Population Census
    Angela Chieppa, Nicoletta Cibella, Antonella Bernardini, Silvia Farano and Giampaolo de Matteis, ISTAT, Italy
  • Measuring the Undercoverage of Two Data Sources with a Nearly Perfect Coverage through Capture and Recapture in the Presence of Linkage Errors
    Abel Dasylva, Arthur Goussanou and Christian Olivier Nambeu, Statistics Canada, Canada

12:30 – 13:00
Afternoon Break

13:00 – 14:15
Session 6A -- Data Visualization for Official Statistics

Chairperson: France Labrecque

  • Find, explore and export data with the Canadian Statistical Geospatial Explorer
    France Labrecque, Statistics Canada, Canada
  • Ireland's innovative approach to monitoring the SDGs and the COVID-19 Outbreak through geospatial visualisation
    Kevin McCormack, Central Statistics Office, Ireland
  • INEGI's strategies towards a user-centric approach to dissemination
    Andrea Fernandez Conde, Instituto Nacional de Estadística, Geografía e Informática, Mexico

13:00 – 14:15
Session 6B -- Health and COVID-19

Chairperson: Julie Bernier

  • Physician experiences during the COVID-19 pandemic in the United States: Adapting an annual survey to assess pandemic-related challenges
    Zachary J. Peters and Danielle Davis, National Center for Health Statistics, USA
  • Applying the data science approach to COVID-19 epidemiological modelling to inform PPE demand and supply in Canada
    Deirdre Hennessy, Jihoon Choi, Joel Barnes, Christina Tucker, Kayle Hatt, Gillian Dawson and James Van Loon, Statistics Canada and Health Canada, Canada
  • Harnessing Natural Language Processing and Machine Learning to Enhance Identification of Opioid-Involved Health Outcomes in the National Hospital Care Survey
    Amy M. Brown and Nikki Adams, National Center for Health Statistics and Centers for Disease Control and Prevention, USA
  • The importance of data integration and automation for interactive web applications
    Peter Solymos and Khalid Lemzouji - Analythium Solutions Inc., Canada

Friday October 29, 2021

10:00 – 11:00
Session 7 -- Waksberg Award Winner Address

Chairperson: Bob Fay

  • Multiple-Frame Surveys for a Multiple-Data-Source World
    Sharon L. Lohr, Arizona State University, USA

11:00 – 11:15
Morning Break

11:15 -- 12:30
Session 8A -- Integrating Multiple Data Sources

Chairperson: François Brisebois

  • Methodological challenges of smart surveys – some case studies
    Barry Schouten, Statistics Netherlands/Utrecht University, the Netherlands
  • On a Bayesian approach to improving probability sample estimators using a supplementary non-probability sample
    Abel DaSylva, Yong You and Jean-Francois Beaumont, Statistics Canada, Canada
  • Imputation Methods for the Experimental Monthly State Retail Sales Report
    Stephen J. Kaputa, US Census Bureau, USA

11:15 -- 12:30
Session 8B -- Response Burden, Synthetic Data and Privacy Protection

Chairperson: Steven Thomas

  • Growing Regression Trees that Use Sampling Frame Covariates to Explore Response Burden for Use in Survey Design
    Yeng Xiong, Laura Bechtel, Diane Willimack and Colt Viehdorfer, US Census Bureau, USA
  • Evaluation of respondents' participation in the survey of Information and Communication Technologies usage in Enterprises (ICT)
    Samanta Pietropaoli, Damiana Cardon, Claudio Ceccarelli, Gabriella Fazzi and Alessandra Nurra, ISTAT, Italy
  • Generating smart deep files: the example of synthesizing hierarchical data
    Héloïse Gauvin, Statistics Canada, Canada
  • Supervised Text Classification with Leveled Homomorphic Encryption
    Zachary Zanussi, Benjamin Santos and Saeid Molladavoudi, Statistics Canada, Canada

12:30 – 13:00
Afternoon Break

13:00 – 14:15
Session 9A -- Making Official Statistics More Open

Chairperson: Claude Julien

  • Building better data to build a better future
    Darren Barnes, Office for National Statistics, United Kingdom
  • The Linkable Open Data Environment: harmonizing open microdata for heterogeneous sources
    Alessandro Alasia and Joseph Kuchar, Statistics Canada, Canada
  • Development of R libraries for common tasks with open Canada data
    Dmitry Gorodnichy, Canada Border Services Agency, Canada

13:00 – 14:15
Session 9B -- Use of Data Science for Modeling

Chairperson: Jean LeMoullec

  • Nowcasting Finnish real economic activity using traffic loop data
    Pontus Lindroos, Henri Luomaranta and Paolo Fornaro, Statistics Finland, Finland
  • Relative Performance of Methods Based on Model-Assisted Survey Regression Estimation
    Erin Lundy and J.N.K. Rao, Statistics Canada and Carleton University, Canada
  • On the path to more timely economic indicators: A comparison of traditional and new machine learning nowcasting methods
    Christian Ritter and Zdenek Patak, Statistics Canada, Canada
  • Automation of Information Extraction from Financial Statements in SEDAR System using Spatial Layout based Techniques
    Anurag Bejju, Statistics Canada, Canada

Friday November 5, 2021

10:00 – 11:00
Session 10 – Poster Session

  • What can we learn from missing data? Examining nonreporting patterns of height, weight, and BMI among Canadian youth
    Amanda Doggett, Ashok Chaurasia, Jean-Phillipe Chaput and Scott Leatherdale, University of Waterloo, University of Ottawa and Children’s Hospital of Eastern Ontario Research Institute, Canada
  • A bridging model to reconcile statistics based on data from multiple sources
    Andreea Luisa Erciulescu, Jean D. Opsomer and F. Jay Breidt, Westat and Colorado State University, USA
  • Combining rules for F- and Beta-statistics from multiply-imputed data
    Ashok K Chaurasia, University of Waterloo, Canada
  • Quality Assurance in Emergencies: Developing a Framework for Reporting on Emergency Performance Statistics in Response to the COVID-19 Pandemic
    Simon Rioux, Anuoluwa Iyaniwura and Chimaobi Amadi, Employment and Social Development Canada, Canada
  • Innovative Use of Mapping Applications to Support Recruitment and Collection Activities of the 2021 Census of Population
    Mark Oswald, Kimberley Easter and Jacob MacLean, Statistics Canada, Canada
  • Improved decision-making in imputation design through data visualization
    Darren Gray, Statistics Canada
  • Estimating hog inventories using traceability data: A feasibility study
    Joshua Gutoskie, Jeremie Spagnolo and Herbert Nkwimi Tchahou, Statistics Canada

11:00 – 11:15
Morning Break

11:15 -- 12:30
Session 11A -- Applying Data Science and Machine Learning Methods in Official Statistics: Opportunities and Challenges

Chairperson: Saeid Molladavoudi

  • Data science for faster, richer insights: opportunities and challenges
    Louisa Nolan, Office for National Statistics, United Kingdom
  • Fair and explainable AI from an official statistics perspective
    M.P.W. (May) Offermans and Barteld Braaksma, Statistics Netherlands, the Netherlands
  • Data science pipelines @ Istat: challenges and solutions
    Monica Scannapieco, ISTAT, Italy

11:15 -- 12:30
Session 11B -- Machine Learning and Modeling for Classification

Chairperson: Steve Matthews

  • Need for Speed : Using fastText (Machine Learning) to Code the Labour Force Survey
    Justin Evans and Javier Oyarzun, Statistics Canada, Canada
  • Testing Covariate Effects for Differences in Text Reviews of Canadian Beers
    Dave Campbell and Gabriel Phelan, Carleton University and Simon Fraser University, Canada
  • Machine Learning Classifier Accepted Criteria: application to price statistics
    Serge Goussev, William Spackman and Daniel Ma, Statistics Canada, Canada
  • Integrating machine learning into coding of the 2021 Canadian Census using fasttext
    Andrew Stelmack, Statistics Canada, Canada

12:30 – 12:45
Afternoon Break

12:45 – 14:00
Session 12 – Panel Discussion

  • Using data science to innovate and address emerging needs in official statistics
    Panelists : Eric Deeben, Office of National Statistics, Data Science Campus, United Kingdom, Wendy Martinez, Bureau of Labor Statistics, USA and Danny Pfeffermann, Central Bureau of Statistics, Israel
    Moderator : Eric Rancourt, Statistics Canada, Canada

14:00 – 14:15
Closing Remarks

  • André Loranger, Assistant Chief Statistician, Statistics Canada, Canada
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