I applied a Hosmer-Lemeshow-Test (now named only goodness-of-fit?) provided by the RMS Package by Prof. Harrel. The p-values for my model were not significant, therefor applying the following link: Goodness-of-fit test in Logistic regression; which 'fit' do we want to test?
I fail to reject the Null-Hypothesis, therefor I cannot reject the model if that is correct.
However while applying also a Pseudo-R² measure with extremly low levels (from a different package, but the one from the RMS-package suggest the same) aswell as plotting the ROC and calculating the AUC, I ask myself: How to interpret the Hosmer-Lemeshow-Test?
Is it right to state: While it is not possible to reject the model, there is plenty of room for improving it? Can I state something like: Even though the model isn't significantly or logically false it doesn't represent the data appropiately? What statement can I really conduct from this outcome?
I am still a nooby in this platform, please don't pick on me again.