It makes sense that wouldn’t have much effect on how much exercise people said they did, doesn’t it?

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Your earlier question about edge effects doesn’t apply, what they did was to randomly offer people different insurance plans. Practically everybody who was offered the plan with no copayments at all took it. Three quarters of the ones who were offered the plan with the most expensive copayments took it. They compared the people who took the plays with copayments against those without and couldn’t find any important difference. Also they tried to cmopare the people who took the copayment plans against the ones who refused and couldn’t tell a difference there either.

So it was random by insuree and not by area. You get insurance from them and they offer you a plan at random, you take it or leave it.

One bias I haven’t examined closely is that for 60% of their patients they did physical exams at the start and at the end to base their statistics on, but for a randomly-chosen 40% they did the exams only at the end, and they guessed the numbers for the beginning. I haven’t seen why they chose to do that. I’d expect the result would be to make any changes less statisticly significant. Imagine that they guessed at baselines for all the patients, and then they looked at the difference at the end compared to the beginning. Imagine that they assigned everybody the same initial state (which they didn’t, they guessed from questionnaires and very general data). Imagine that everybody changes by 2%, but they measure it as 48% decreasing from the universal baseline while 52% increase. The extra noise would make the result look weaker than it is.

The study was too small to do much about actual deaths. So they predicted deaths based on obesity, smoking, etc and used the predictions as a measure. Since medical care as of 1982 did not do much to reduce obesity or smoking etc the predicted mortality was not changed much, except the observed small blood pressure decrease.

In this case, I don’t mean *controlling* for obesity, but trying to empirically (or theoretically for that matter) estimate to what extent healthcare and healthy living are substitutes. To what extent do increases in medical technology enable people to be more obese? Is obesity endogenous?

Maybe that’s what you meant, but I wasn’t sure.

They allow medical care at various costs, free, $150/year, $1000/year (or some percentage of income, whichever is less).

They note that without free care there were 2/3 as many doctor visits and 2/3 as many hospitalisations.

And with 2/3 the care, they got no significant difference on most of their metrics. However, when they tried to do that for subgroups — just poor people or just sick people etc — the confidence intervals got too big. There could have been important benefits to extra care for some subgroups and it wouldn’t show up as statisticly significant.

For a rich person the difference between free care and $150/year or even $1000/year might not matter, they would reduce the significance for the whole study, and there weren’t enough poor people to get a good baseline.

The eleven measures were “physical health”, “role functioning”, “mental health”, “social contacts”, and “general health measures”: smoking behavior, weight, cholesterol level, diastolic blood pressure level, visual acuity, and a death index.

Right offhand I wouldn’t expect free psychiatry to quickly affect mental health, social contacts, or role functioning. And over 1975 through 1981, would we expect more medical care to affect weight, cholesterol, blood pressure, or get people to quit smoking? What did MDs do to get people to quit smoking in 1981 besides tell them to quit smoking? What did they do to get them to lose weight or gain weight? Would you expect 3 doctors visits to do more about that than 2 visits?

More later.