This workshop offers an intensive four-day introduction to causal modeling with Coincidence Analysis (CNA), a novel configurational comparative method of data analysis geared towards causal complexity, which has seen a considerable uptick in applications in recent years (click here for references). No prior knowledge of CNA is required. 

In plenary lectures, the main developer of CNA, Michael Baumgartner, and a team of experienced CNA methodologists and practitioners (Drs. Cragun, Freitas, Huang, and Miech) will guide participants through the nuts and bolts of configurational data analysis and cutting-edge methodological innovations, as well as offer advice on practical issues such as getting funded and published with CNA. In smaller practice groups, understanding of the material will also be deepened through applied exercises and the instructors will demonstrate how to make the most of current software for CNA.

From Boolean algebra and the philosophical roots of regularity theories of causation, over the basic ideas behind CNA’s search algorithm, and measures of fit to multi-outcome structures, model ambiguities, and robustness analyses, this introduction will enable participants to conduct CNA analyses themselves and review those of other researchers in a sophisticated manner. This will also be an opportunity to get to know researchers working with and on CNA from all over the world.

The workshop agenda is available here. You can register for the conference here.

Costs:

• Early bird fee for registration prior to January 31, 2026 is $850.
• Standard registration (February 1, 2026 – April 15, 2026) is $950.
• Late registration (April 16th 2026 – May 15th, 2026) is $1050.