Hosmer-Lemeshow test

The Hosmer-Lemeshow test is a statistical method used to evaluate how well a predictive model, such as one estimating the likelihood of an event (like disease or success), fits the actual data. It divides data into groups based on predicted probabilities and compares the observed outcomes with what the model predicted in each group. If the differences are small, the model fits well; large differences suggest it may not be accurate. Essentially, it checks whether the model's predictions align closely with real-world observations across different groups.