The Hosmer-Lemeshow test divides your dataset into deciles (or groups) based on predicted probabilities. It then compares the observed and expected frequencies of events within each group. A chi-square statistic is calculated to determine if there is a significant difference between observed and expected values. If the p-value is greater than the chosen significance level (often 0.05), the model is considered to have a good fit.
