Overview
The main profile of the Survey Methods Room Budapest (SMRB) research group is the methodological foundation of empirical social science, and the future opportunities in survey data. This includes projects on sampling methods, weighting and data correction procedures and estimation strategies. We focus on probability and non-probability samples, survey experiments and new methods in survey data collections such as online surveys and hybrid technologies. The research group has interests in bringing survey methodology to machine learning. SMRB was established in 2022 and open to work with other academic units within and outside the university and seeking new collaborations.
Our main research methods are survey methods, probability theories, statistical modelling, simulation, mathematical-statistical analytical tools, and machine learning.
Grants
University Excellence Fund
Blanka Szeitl: Predicting the Vote – Statistical Innovation for Evidence-Based Electoral Research (2025-2026)
National Laboratory for Social Innovation (“A” component – Experimental developments)
Blanka Szeitl: Validation collaboration – Measurement error project (2025-2026)
National Laboratory for Social Innovation
Blanka Szeitl, Eszter Katona: ELTE Survey Reliability Criteria System (MeKri)
University Excellence Fund
-Blanka Szeitl: A new method to improve the accuracy of estimates in empirical social research: accessibility-based post-stratification (2024-2025)
-Blanka Szeitl, Eszter Katona: Survey Anatomy – Understanding polls (2024-2025)
National Laboratory for Social Innovation
Blanka Szeitl: Survey research methods in a new technological and social environment II. (2023-2024)
Sylff Association – The Tokyo Foundation for Policy Research
Blanka Szeitl: New methods of survey data collections in empirical social sciences (2023)
National Laboratory for Social Innovation
Blanka Szeitl: Survey research methods in a new technological and social environment I. (2022)
Internal projects
Blanka Szeitl – Zita Fellner: The opportunity of Respondent-Driven Sampling to improve survey estimates - a case study on income distribution (2023-2024) intern: Hanka Lajos (survey statistics MSc)
Blanka Szeitl – Buda Jakab: Understanding survey nonresponse-bias by generating additional information based on GEO-codes and Machine Learning methods (2023-2024) intern: Tamás Mákos (survey statistics MSc)
Research group members
Blanka SZEITL – head of Research Group, Department of Statistics, Faculty of Social Sciences, ELTE, Budapest, Hungary
Eszter KATONA – researcher, Department of Social Research Methodology, Faculty of Social Sciences, ELTE, Budapest, Hungary
Emese TÚRY-ANGYAL – researcher, Department of Statistics, Faculty of Social Sciences, ELTE, Budapest, Hungary
junior researchers
Otília BISZÁK – junior researcher, Faculty of Social Sciences, ELTE, Budapest, Hungary
Bernadett NAGY – junior researcher, Faculty of Social Sciences, ELTE, Budapest, Hungary
Tamás POGRÁNYI – junior researcher, Faculty of Social Sciences, ELTE, Budapest, Hungary
Rebeka TÓTH – junior researcher, Faculty of Social Sciences, ELTE, Budapest, Hungary
interns
Csenge DOMJÁN – intern, Faculty of Social Sciences, ELTE, Budapest, Hungary
Tamara TÓTH – intern, Faculty of Social Sciences, ELTE, Budapest, Hungary
Zalán KERTÉSZ – intern, Faculty of Social Sciences, ELTE, Budapest, Hungary
Kincső TEMESSZENTANDRÁSI – intern, Faculty of Humanities and Social Sciences, KRE, Budapest, Hungary
Annamária ZSIROS – intern, Faculty of Social Sciences, ELTE, Budapest, Hungary
Keywords
empirical social science, data science, survey research, sampling methods, estimation strategy, survey error, biased data
Outputs
https://surveyanatomia.elte.hu
Biszák Otília, Szeitl Blanka, Túry-Angyal Emese
Választási részvétel és a válaszhiány típusai – klasszikus tipológia új szempontokkal
STATISZTIKAI SZEMLE 103 : 10 pp. 931-953. , 23 p. (2025)
Katona Eszter, Szeitl Blanka, Túry-Angyal Emese
A kutatás ára: Az empirikus társadalomkutatás ökológiai lábnyoma és ennek mérési lehetőségei a természetesnyelv-feldolgozás példáján keresztül
REPLIKA : 134 pp. 23-34. , 12 p. (2024)
Contact information (leader)
Blanka SZEITL (leader)
Department of Statistics
Faculty of Social Sciences, Eötvös Loránd University of Budapest (ELTE)
szeitl.blanka@tatk.elte.hu