Professor of Computational Social Science and Behavioural Science
Behavioural and Implementation Science Interventions (BISI), Yong Loo Lin School of Medicine
National University of Singapore
Department of Sociology and Social Research
University of Trento
Featured Article
The Effects of Data Preprocessing Choices on Behavioral RCT Outcomes: A Multiverse Analysis
Multivariate Behavioral Research
This study investigates how seemingly routine data preprocessing decisions can significantly influence the outcomes of behavioral randomized controlled trials. Using multiverse analysis—a method that systematically explores many reasonable analytical pathways—the research demonstrates that choices such as outlier handling, missing data treatment, and variable transformations can lead to substantially different conclusions from the same underlying data. The findings highlight the importance of transparent reporting of analytical decisions and advocate for greater methodological rigor in behavioral research.
Read ArticleRecent Publications
Veltri, G. A., & Gilbert, J. (2026). Results from Randomized Controlled Trials are Highly Sensitive to Data Preprocessing Decisions: A Multiverse Analysis of 97 Outcomes. MetaArXiv. Preprint
Veltri, G.A.(2026). Time-Sensitive RCTs in Behavioural Public Policy: A Pragmatic Framework Using Sequence Methods, Personalisation, and Reinforcement Learning. Frontiers in Behavioral Economics. In press. DOI
De Duro, E. S., Franchino, E., Improta, R., Veltri, G. A., & Stella, M. (2025). Cognitive networks identify AI biases on societal issues in Large Language Models. EPJ Data Science. DOI
Veltri, G.A. (2025). The Effects of Data Preprocessing Choices on Behavioral RCT Outcomes: A Multiverse Analysis. Multivariate Behavioral Research. DOI
Veltri, G.A. (2025). From Evidence to Delivery: An Implementation‑Science Blueprint for Behavioural Policy. Behavioural Public Policy. DOI
Andrei, F., & Veltri, G. A. (2025). Signalling strategies and opportunistic behaviour: Insights from dark-net markets. PLOS ONE, 20(3), e0319794. DOI
Banerjee, S., & Veltri, G. A. (2024). Harnessing pluralism in behavioral public policy requires insights from computational social science. Frontiers in Behavioral Economics, 3. DOI