The article compares different ways to estimate models when the factors you're studying might be connected to each other or measured incorrectly. They looked at four methods to see which one works best for situations where treatment isn't randomly assigned and outcomes are binary. The researchers found that the average index function is a better choice for calculating choice probabilities and regressor effects compared to the average structural function.