> optimal prediction models achieved accuracies of 0.75±0.22 for women and 0.70±0.10 for men
For a clinician, sensitivity and specificity are much more useful. It's too bad they didn't publish these.
For a clinician, sensitivity and specificity are much more useful. It's too bad they didn't publish these.
That is to say, don't compare to the accuracy of an even coin flip; compare to the accuracy of a coin flip that flips according to the proportion of the people with the attribute you care about.
I don't think that's right. Always answering yes is going to have 75% accuracy if the prevalence is 75%, but always answering no will have 25% accuracy, and the coin flip will pick both of those equally (and uncorrelated with whether the individual has diabetes or not).