IASS - Combining Multiple Data Sources with Statistical Modeling
| Date | 27 Aug 2026 |
| Time | 14:00 CEST - 15:30 CEST |
| Level of instruction | |
| Instructor |
Partha Lahiri
|
| Registration fee | |
Demand for diverse socio-economic, agricultural and health statistics is surging, yet survey organisations must navigate increasingly tight budgets. Fortunately, the rise of diverse data sources, including administrative records, geospatial data, non-probability surveys and AI-generated data, offers unprecedented opportunities to tackle complex statistical challenges.
This webinar explores how statistical modelling can successfully combine multiple data sources to extract high-value insights. We will discuss key applications, including generating precise granular estimates, conducting multivariate analyses, reducing non-sampling errors in probability samples, and mitigating self-selection bias in non-probability data.
The session will conclude with an in-depth look at recent statistical developments in poverty mapping, illustrating practical solutions of critical interest to national and international statistical organisations.
Instructors
About the instructor
Prof. Partha Lahiri is a Professor of the Joint Program in Survey Methodology (JPSM) and the Department of Mathematics at the University of Maryland College Park (UMD). He served as the JPSM Director from January 2021 through June 2025. Currently serving as the President of the International Association of Survey Statisticians (IASS), Dr. Lahiri is a globally recognized expert in the field of Small Area Estimation (SAE). He has served on several advisory committees including the U.S. Census Bureau Advisory Committee of Professional Associations (chair in 2006) and a U.S. National Academy of Sciences panel and served as consultant/advisor for international organizations such as the United Nations Statistics Division and the World Bank. An elected Fellow of both the American Statistical Association and Institute of Mathematical Statistics and an elected member of the International Statistical Institute, his pioneering research has been recognized with numerous prestigious awards and honors, including the 2026 Morris Hansen Lecture, 2022 Neyman Medal, and the 2021 SAE Award.