I visited my GP (family physician) last week on a minor matter which I am glad to say is now cleared up totally. However, the receptionist was very eager to point out that I had not taken up my earlier invitation to a cardiovascular assessment. I suspect there was some financial incentive for the practice. I responded that I was uninterested. I knew the general lifestyle advice being handed out and how I felt about it. However, she insisted and it seemed she would never book me in for my substantive complaint unless I agreed. So I agreed.
I had my blood pressure measured (ok), and good and bad cholesterol (both ok which was a surprise). Finally, the nurse gave me a percentage risk of cardiovascular disease. The number wasn’t explained and I had to ask if the number quoted was the annual risk of contracting cardiovascular disease (that’s what I had assumed) or something else. However, it turned out to be the total risk over the next decade. The quoted risk was much lower than I would have guessed so I feel emboldened in my lifestyle. The campaign’s efforts to get me to mend my ways backfired.
Of course, I should not take this sort of thing at face value. The nurse was unable to provide me with any pseudo-R2 for the logistic regression or even the Hosmer–Lemeshow statistic for that matter.
I make light of the matter but logistic regression is very much in vogue at the moment. It provides some of the trickiest issues in analysing model quality and any user would be naïve to rely on it as a basis for action without understanding whether it really was explaining any variation in outcome. Issues of stability and predictability (see Rear View tab at the head of this page) get even less attention because of their difficulty. However, issues of model quality and exchangeability do not go away because they are alien to the analysis.
When governments offer statistics such as this, we risk cynicism and disengagement if we ask the public to take them more glibly than we would ourselves.