When people say that outliers ($\neq$ experimental error) shouldn't be removed, but that analysis should be done both with and without them, do they mean that I should use the same model for both cases, and then report on potential differences? Even if the model with outliers is not satisfying the assumptions of e.g. normality?
Is that what people usually do? Or do people usually use different models?