IASS aims to develop the theory and practice of surveys and censuses, and increase interest in surveys and censuses among statisticians, governments and the public around the world.

SEVEN ISI ASSOCIATIONS

Since 1973

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IASS: International Association of Survey Statisticians

→ Know reality as it is, through numbers

The International Association of Survey Statisticians aims to develop the theory and practice of surveys and censuses, and increase interest in surveys and censuses among statisticians, governments and the public around the world. Our challenge as survey statisticians is to help shape public opinion and inform government policies to know reality as it is, through numbers.

We evolve as the society and the science evolves. The International Association of Survey Statisticians's contribution to the International Statistical Institute is to promote good survey theory and practice around the world. These contributions are even more imperative as we move forward with increasing use of new forms of digital and administrative data that suffer from imperfections. Through the use of surveys, we can adjust these new sources of data prior to their use in statistical systems to ensure that everyone counts.
Objectives
Promoting good survey theory and practice around the world.

Important Links
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Events Calendar

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Executive Committee
President: Natalie Shlomo (See picture)
President-Elect: Partha Lahiri
Vice-President: Eric Rancourt
Vice-President: Annamaria Bianchi
Vice-President: Andres Gutierrez Rojas
Vice-President: Jiraphan Suntornchost
Ex officio Member: Conchita Kleijweg (Director ISI)
"IASS's aim is to promote good survey theory and practice around the world. Through surveys we can correct under and over coverage within new forms of data sources and ensure that everyone counts in our statistical systems." — Natalie Shlomo, President, IASS

→ Participation in the 64th WSC 2023.

Fourteen Invited Papers Sessions covering traditional statistical research in survey statistics and new developments related to new forms of data and innovation:

» Better ways to address non-response in social surveys
» Longitudinal observation of human populations
» Measurement Error Modelling: Advances and Applications
» Recent Advances in Data Anonymization and Data Modelling for Education and Poverty Research
» Unlocking Microdata: Experience from International Organizations
» Inference under Informative Sample Designs
» Harnessing data by citizens for public policy and SDG monitoring: a conceptual framework and what is next?
» Monitoring Progress towards Sustainable Development Goals with Small Area Estimation over Space and Time
» The use of alternative data through modelling in Official Statistics
» Innovative statistical methods for large-scale surveys
» Developments in Small Area Statistics Leveraging Non-Random Sampling
» Sample surveys in the era of Big Data and Machine Learning
» Advanced inference on mixed effects models for SAE
» Data Integration in Survey Sampling Three Special Invited Paper Sessions:
» SIPS Waksberg Award with a presentation by the 2023 Waksberg Award Winner, Prof. Ray Chambers. The title of Ray’s talk was ‘The Missing Information Principle - A Paradigm For Analysis Of Messy Sample Survey Data’.
» Special Invited Paper Sessions of The International Association of Survey Statisticians' President’s Invited Speaker session was delivered by Prof. Fulvia Mecatti. The title of her talk was: ‘Bridging Big Data and Sampling Methodology: a Sampling Statistician Perspective’.

» Special Invited Paper Sessions, Cochran-Hansen Prize session with presentations by our two Cochran-Hansen prize winners: Alejandra Arias-Salazar (Costa Rica) with her paper: “Small Area Estimates of Poverty Incidence in Costa Rica under a Structure Preserving Estimation (SPREE) Approach” and Ziqing Dong (China) with his paper: “Linearization and Variance Estimation of the Bonferroni Inequality Index”.

Cochran-Hansen Prize 2023, Joint Prize Winners

+ Alejandra Arias-Salazar (Costa Rica): “Small Area Estimates of Poverty Incidence in Costa Rica under a Structure Preserving Estimation (SPREE) Approach.”

+ Ziqing Dong (China): “Linearization and Variance Estimation of the Bonferroni Inequality Index.”