This page collects news and information on CNA trainings, conferences, and online talks.
Fuzzy-set CNA analyses of organizational-level occupational health and safety data often yield very large numbers of solutions. Sørensen and Backhausen present a set of visualizations developed to make such solution sets interpretable, and invite the CNA community to discuss how they can be used to interrogate and present CNA results.
Katharina Sterr applies CNA to data from 113 German primary schools taking part in a nationwide health promotion programme, analysing eleven contextual and process-related factors, among them organizational health literacy, staffing levels, and PDSA cycle implementation. The final model identifies two alternative pathways to successful implementation.
This hands-on online course introduces Coincidence Analysis (CNA), a configurational method for causal data analysis and modeling widely used in the health and social sciences. CNA is uniquely designed to capture causal complexity and context-sensitivity: it bundles multiple factors into complex causes in which every element is indispensable for producing an outcome, and places these bundles on the same or on alternative causal paths to one or more outcomes.
Taught by CNA’s main developer, Michael Baumgartner, the course covers the conceptual foundations, the search algorithm, hands-on data analysis using the cna R package, model evaluation, and strategies for robustness analyses. No prior knowledge of CNA is required, though familiarity with R is an asset.
Registration is now open via the KOMEX registration page.