Slide presentations are linked into the IASS webinars below.   

The  IASS Webinar Video Recordings can be accessed here.

IASS Webinar 40: An Estimation of Variance of Random Effects to Solve Multiple Problems in Small Area Estimation 

IASS Webinar 39: Model-Based Optimal Designs for a Multipurpose Farm Survey

IASS Webinar 38: Data Integration, Data Linkage, and Linked Data Analysis

IASS Webinar 37: New Developments in Small Area Estimation: A Practitioner’s Perspective

IASS Webinar 36: Latent Variable Models for Finite Population Inference

IASS Webinar 35: Enhancing the Credibility of Survey Data: Old Tricks and New Techniques in Improving the Respondent Experience

IASS Webinar 34: Three Extensions of the Basic Unit-Level Model

IASS Webinar 33: Missing Voices: Whose Perspectives are Missing in Household Survey Data

IASS Webinar 32: An Extension of the Weight Share Method when using a Continuous Sampling Frame, with Application to the French National Forest Inventory

IASS Webinar 31: Producing Small Area Estimates for Labour Market Indicators in Latin America: A Bayesian Perspective

IASS Webinar 30: Inter-Secretariat Working Group on Household Surveys: What We Have Achieved and What’s Next? 

IASS Webinar 29: Fitting Classification Trees to Complex Survey Data

IASS Webinar 28: The Production of Microdata on Household Income, Consumption and Wealth at ISTAT: Experiences, Methods, Perspectives 

IASS Webinar 27: Designed Big Data in Surveys and Official Statistics: Augmenting Surveys with Sensors, Apps, Wearables and Data Donation

IASS Webinar 26: Integrating Survey and Non-survey Data in the Production of U.S. Official Agricultural Statistics: A Progress Report

IASS Webinar 25: Unemployment Estimates for the Brazilian Labour Force Survey Using State-Space Models

IASS Webinar 24: Developing the Sample Design for the New Annual Integrated Economic Survey

IASS Webinar 23: Bridging BigData and Sampling Methodology: What is “big” and where is the “bridge”?

IASS Webinar 22: Hukum Chandra Prize 2022: Small area estimation: a novel approach on estimation of mean squared prediction error of small-area predictors

IASS Webinar 21: Design-based Analysis of Experiments Embedded in  Probability Samples

IASS Webinar 20: Adjusting for Selection Bias in the Volunteer Sample of the 2021 Lithuanian Census – Part I and Part II

IASS Webinar 19: Substitution of Nonresponding Units in Probability Sampling

IASS Webinar 18: Spatial Sampling and Geospatial Information for Monitoring Agriculture

IASS Webinar 17: On calibration and balanced sampling. Webinar in memory of Jean-Claude DevilleMatei_Slides Goga_Slides    Tille_Slides  

IASS Webinar 16: Three-Form Split Questionnaire Design for Panel Surveys

IASS Webinar 15: Approaches for Combining Data from Multiple Probability Samples

IASS Webinar 14: Rescuing Non-probability Samples: an Experience with Model-based Inference from a Web-panel Survey

IASS Webinar 13: Making Inferences from Non-probability Samples through Data Integration

IASS Webinar 12: Robust Analysis of Linked Sample Data

IASS Webinar 11: Positioning Household Surveys for the Next Decade

 IASS Webinar 10: Theory and Practice of Adaptive Survey Design at Statistics Netherlands

IASS Webinar 9: Targeted or lagged walk sampling for estimation of finite-order graph parameters

IASS Webinar 8: Building a Sample Frame of SMEs Using Patent, Search Engine, and Website Data

IASS Webinar: Population size estimation using administrative data

IASS Webinar: Survey and Big Data Interactions

World Statistics Day: On the Importance to Society of High Quality Public Statistics – Joint IAOS-IASS Webinar 


IASS Webinar: Population size estimation using administrative data

IASS Webinar: Survey and Big Data Interactions

World Statistics Day: On the Importance to Society of High Quality Public Statistics – Joint IAOS-IASS Webinar 

IASS Webinar:

11am CET on September 3rd, 2020

Measuring the socio-economic impact of coronavirus in Asia and the Pacific. The coronavirus has been a major wake-up call for national statistical organisations. Survey operations have been impacted, new data sources are being used, data gaps are being filled by whoever is able to fill them, and best practices are being tested. In Asia and the Pacific, nearly 75% of National Statistical Offices have had to postpone fieldwork for planned censuses and there is thirst for information on what to do and how to do it. ESCAP, the UN Economic and Social Commission for Asia and the Pacific, has collated information on socio-economic surveillance surveys being undertaken in Asia and the Pacific and convened several dialogues to share expertise and experiences on these activities. In this presentation, ESCAP will share their findings and the common questions being asked by countries in relation to these surveys.

Overview of the design and estimation methods in the ONS Covid Infection Survey. ONS has been running a survey to measure prevalence and incidence of Covid-19 infection in the household population since April 2020. It was initially limited to England but it has now been extended to the whole UK, and the sample is being increased substantially with the aim to achieve 150000 responding individuals in a fortnight by October 2020. I will describe the challenges we have encountered in collecting and processing the data, as well in estimation and analysis.

Statistical Design for Covid-19 monitoring and control. The Covid-19 pandemic has affected countries differently. In New Zealand all incoming international travellers are put in isolation for two weeks and any cases found are quarantined. There has been limited community transmission. Contact tracing of community cases remains exhaustive. There is a Statistical Advisory Group to the NZ Ministry of Health. The underlying strategy has been elimination rather than eradication, via a scale of alert levels that utilise lockdowns and bubbles.

Although the NZ situation is not always replicated elsewhere where Covid-19 prevalence is higher, there remain common underlying statistical themes and issues. • The need for government Ministries and Departments of Health to prepare by commissioning design of prevalence surveys as soon as possible, even if implementation is delayed. • Recognition of the potential to integrate sound sampling with contact tracing by using repeated adaptive cluster and network sample designs, which make it possible to track all contacts of known cases, have a chance of detecting unknown community cases, monitor special groups (such as those at the border) and get prevalence estimates with standard errors over time. • The need to understand better the effect of the survey design on specificity of lab tests. • To recognise how pooling laboratory tests using even simple experimental designs could improve test sensitivity.

Gemma Van Halderen is Director of the Statistics Division in the United Nations Economic and Social Commission for Asia and the Pacific (ESCAP). Prior to joining the United Nations, Gemma was a member of the Australian Bureau of Statistics (ABS) Executive Team focusing on data sharing, data integration and microdata access and ABS’ contribution to the Australian Government’s Data Integration Partnership for Australia. In 2017, Gemma was seconded to the Commonwealth Department of the Prime Minister and Cabinet to lead preparation of the Government’s response to the Productivity Commission Inquiry into Data Availability and Use. Gemma has extensive global experience. She was inaugural co-chair of a UN Expert Group on the Integration of Statistical and Geospatial Information, is an elected member of the International Statistics Institute, a member of the International Association of Official Statistics (IAOS) Executive Committee, the regional editor of the Statistical Journal of the IAOS and an advocate for young statisticians. Gemma holds a Bachelor of Science with Honours from the Australian National University.

Salah Merad has been at the Office for National Statistics for over 10 years. He had led sampling and estimation development projects for several ONS surveys, including the Labour Force Survey and the Opinions and Lifestyle Survey, and the recent Covid-19 Infection Survey.

Stephen Haslett is Emeritus Professor of Statistics at Massey University New Zealand, Professorial Fellow at the National Institute for Applied Statistics Research Australia (NIASRA) at the University of Wollongong, and Visiting Fellow at the Research School of Finance, Actuarial Studies and Statistics (RSFAS) and former Professor / Director of the Statistical Consulting Centre at the Australian National University. He has theoretical interests in linear and mixed linear models, sparse contingency tables, sample design and analysis, and small area estimation. He has undertaken extensive small area estimation and survey design projects for the UN for poverty estimation, food security, nutrition and health, often related to emergency situations. Linked principally with these projects, he has worked in or for central government statistical agencies in more than two dozen countries mainly in Asia, Africa and the Pacific. He is currently involved in research at the Centre for Public Health Research in New Zealand and is a member of the NZ Ministry of Health (MoH) Statistical Advisory Group which is providing statistical advice for Covid-19 to MoH. He began his professional career during the late 1970s, designing sample surveys at Statistics New Zealand.

IASS Webinar:


Other Links

International Statistics Institute [YouTube]