Part 1: What is Coincidence Analysis? · Module 2
A method for combinations, not lone culprits
What Does CNA Do?
Coincidence Analysis (CNA) is a configurational comparative method . In plain terms, it looks for configurations , which are just bundles of conditions that travel together with an outcome, instead of putting each factor on trial one at a time. It was developed by Michael Baumgartner, and it is custom-built for the messy, multi-outcome structures that real programs are made of. It is happiest when causes work in teams.
Most methods assume there is a single best predictor and go looking for it, like a detective convinced there is one culprit. CNA is comfortable with the idea that several different combinations might each lead to the outcome, and it can spot all of them in the same dataset. It can even follow causal chains, where one factor quietly hands off to another.
What You Will Be Able to Do
- Define Coincidence Analysis in one plain sentence.
- Describe what a 'configuration' is.
- List the program situations where CNA fits best.