This Capacity Building session introduces the challenges and opportunities associated with large-N data in political science. As datasets become increasingly larger and more complex, researchers face new issues related to data management and how to conduct meaningful and robust analyses.

The session will outline key strategies for handling large datasets, including data cleaning, scalable analytical approaches, and tools for efficient data processing. It will also introduce participants to commonly used comparative statistical methods suited for large-N research, such as panel regression, difference-in-differences (DiD), multilevel (random effects) models, survival/time-to-event analysis, and large-scale conjoint experiments.

This session is introductory; we warmly welcome participants with little prior experience in quantitative methods who are interested in gaining an introduction to understanding large-N analysis.

Bio

Jérémy Dodeigne is a Professor of Political Science at the University of Namur. Since January 2020, he has also been President of the Transitions research institute.  
His research focuses on the recruitment of political elites and their political behavior, from a comparative and historical perspective. More recently, he has expanded his research agenda to include the personalization of political life and the transformation of political communication in European democracies. In his work, he has used both quantitative analyses (with a recent emphasis on content analysis techniques using deep learning and supervised algorithms) and qualitative methods (including narrative interviews with elites).