# H-L Test: Looking at the data

Can you just eyeball the Hosmer-Lemeshow test (e.g. just look at observed and expected values in each group and see if they agree more or less)? Even if the Hosmer-Lemeshow statistic is significant...can I still say the model fits the data well for my purposes just by observing the observed and expected values in each group?

In my experience, the H-L test is rubbish, and I wouldn't rely on it as an assessment of model calibration, at all. I've managed to get H-L p-values of $10^{-300}$ to near 1 using the same classifier and dataset just by varying the sample size, even though the calibration was nearly perfect visually in all cases.