JPSM MPSDS Seminar Series: Implementing and Adjusting a Non-probability Web Survey: Experiences of EVENs (Survey on the Impact of COVID19 on Ethnic Minorities in the United Kingdom)
Natalie Shlomo, Professor of Social Statistics, University of Manchester
When:
October 18, 2023
12:00 – 1:00 pm EDT
Where:
1070 ISR-Thompson
426 Thompson St., Ann Arbor
Join via Zoom:
Zoom link
Meeting ID: 97217806877
Meeting Password: 2324
Note: The Zoom call will be locked 10 minutes after the start of the presentation.
Abstract:
This is joint work with Andrea Aparcio-Castro, Daniel Ellingworth, Angelo Moretti, Harry Taylor, Nissa Finney and James Nazroo
We discuss the challenges of implementing and adjusting a large-scale non-probability web survey. For the application, we focus on the 2021 Evidence for Equality National Survey (EVENS) which was led by the Centre on Dynamics of Ethnicity (CoDE) at the University of Manchester in the United Kingdom, in partnership with Ipsos-MORI. The aim was to understand the impact of the COVID19 pandemic on ethnic and religious minority groups in the UK. Standard probability-based surveys, even with ethnic minority group boosts, do not have the sample sizes required to obtain reliable estimates for small group statistics. We therefore designed a non-probability web survey of ethnic minority groups to overcome these limitations. We formed partnerships with community organizations and used innovative recruitment strategies, including digital and social media. Daily monitoring of the data collection against desired sample sizes and R-indicator calculations allowed the team to focus attention on the recruitment of specific groups in a responsive data collection mode. We also supplemented the sample with existing members in both established non-probability and probability-based panels in the UK. We describe the measures applied to improve the quality of the collected data and the statistical adjustments to correct for selection and coverage biases based on estimating the probability of participation in the non-probability sample using combined probability reference samples followed by calibration to auxiliary information from the UK Census 2021. We demonstrate how a pseudo-population bootstrap approach can be designed to obtain bootstrap weights to allow for statistical analyses and inference.
Bio:
Natalie Shlomo is Professor of Social Statistics at the University of Manchester and publishes widely in the area of survey statistics, including small area estimation, adaptive survey designs, non-probability sampling, confidentiality and privacy, data linkage and integration. She has over 70 publications and refereed book chapters and a track record of generating external funding for her research. She is an elected member of the International Statistical Institute (ISI), a fellow of the Royal Statistical Society, a fellow of the Academy of Social Sciences and President 2023-2025 of the International Association of Survey Statisticians. She also serves on national and international Methodology Advisory Boards at National Statistical Institutes.
Homepage: https://www.research.manchester.ac.uk/portal/natalie.shlomo.html