So roughly speaking, Roberts had maybe a 50% chance of surviving from publishing his diet book to a ripe old age.
If his actuarial life expectancy was 80 and he had died at 79 it wouldn’t have looked particularly suspicious. But according to your data, his probability of dying between 52 and 60 was only about 7.5%, which is not terribly low, but still enough to warrant reasonable doubt, especially considering the circumstances of his death.
But according to your data, his probability of dying between 52 and 60 was only about 7.5%, which is not terribly low, but still enough to warrant reasonable doubt, especially considering the circumstances of his death.
I think the more interesting question is the probability of a man in his age range (who is not obese; not a smoker; and has no serious self-reported history of health problems) suddenly collapsing and dying. I don’t know the answer to this question, but it’s a pretty unusual event.
By the way, here is a video of Seth Roberts speaking about his butter experiment a few years ago. Seth Roberts mentions that he eats a half a stick of butter a day on top of his Omega-3 regimen. (And probably this is on top of daily consumption of raw olive oil).
At around 11:00, an apparent cardiologist concedes that the butter regimen may very well improve brain function but he warns Roberts that he is risking clogging up the arteries in his brain and points out that Roberts brain function won’t be so great if he has a stroke. Roberts is pretty dismissive of the comment and points out that there is reason to believe the role of fat consumption in atherosclerosis over-emphasized or mistaken.
Still, if someone suddenly collapses and dies, from what I understand it’s usually a cardiovascular problem—a blood clot; stroke; aneurism; heart attack, internal bleeding, etc. And Roberts was consuming copious amounts of foods which are widely believed to have a big impact on the cardiovascular system.
It’s silly to ignore this information when assessing probabilities. Here’s an analogy: Suppose that Prince William has a newborn son and you are going to place a bet on what the child’s name will be. You might reason that the most common male given name in the world is “Mohamed” and therefore the smart money is on “Mohamed.” Of course you would lose your money.
The flaw in this type of reasoning is that when assessing probabilities, there is a requirement that you use all available information.
I imagine Gwern would respond that he is merely setting an upper bound. But that’s silly and pointless too. If 90% of male children in Saudi Arabia are named “Mohamed,” we can infer that the probability the Royal Baby will be named “Mohamed” does not exceed 90%. But so what? That’s trivial.
but still enough to warrant reasonable doubt, especially considering the circumstances of his death.
I disagree (reasonable doubt under what assumptions? in what model? can you translate this to p-values? would you take that p-value remotely seriously if you saw it in a study where n=1?), and I’ve already pointed out many systematic biases and problems with attempting to infer anything from Roberts’s death.
I’m not saying we can scientifically infer from his premature death that his diet was unhealthy.
I’m saying that his premature death is informal evidence that his diet at best didn’t have a significant positive impact on life expectancy, and at worst was actively harmful. I can’t quantify how much, but you were the one who attempted a quantitative argument and I’ve just criticized your argument, namely your strawman definition of “suspicious death”, using your own data and assumptions, hence it seems odd that you now ask me for assumptions and p-values.
If his actuarial life expectancy was 80 and he had died at 79 it wouldn’t have looked particularly suspicious. But according to your data, his probability of dying between 52 and 60 was only about 7.5%, which is not terribly low, but still enough to warrant reasonable doubt, especially considering the circumstances of his death.
I think the more interesting question is the probability of a man in his age range (who is not obese; not a smoker; and has no serious self-reported history of health problems) suddenly collapsing and dying. I don’t know the answer to this question, but it’s a pretty unusual event.
By the way, here is a video of Seth Roberts speaking about his butter experiment a few years ago. Seth Roberts mentions that he eats a half a stick of butter a day on top of his Omega-3 regimen. (And probably this is on top of daily consumption of raw olive oil).
http://vimeo.com/14281896
At around 11:00, an apparent cardiologist concedes that the butter regimen may very well improve brain function but he warns Roberts that he is risking clogging up the arteries in his brain and points out that Roberts brain function won’t be so great if he has a stroke. Roberts is pretty dismissive of the comment and points out that there is reason to believe the role of fat consumption in atherosclerosis over-emphasized or mistaken.
Still, if someone suddenly collapses and dies, from what I understand it’s usually a cardiovascular problem—a blood clot; stroke; aneurism; heart attack, internal bleeding, etc. And Roberts was consuming copious amounts of foods which are widely believed to have a big impact on the cardiovascular system.
It’s silly to ignore this information when assessing probabilities. Here’s an analogy: Suppose that Prince William has a newborn son and you are going to place a bet on what the child’s name will be. You might reason that the most common male given name in the world is “Mohamed” and therefore the smart money is on “Mohamed.” Of course you would lose your money.
The flaw in this type of reasoning is that when assessing probabilities, there is a requirement that you use all available information.
I imagine Gwern would respond that he is merely setting an upper bound. But that’s silly and pointless too. If 90% of male children in Saudi Arabia are named “Mohamed,” we can infer that the probability the Royal Baby will be named “Mohamed” does not exceed 90%. But so what? That’s trivial.
I disagree (reasonable doubt under what assumptions? in what model? can you translate this to p-values? would you take that p-value remotely seriously if you saw it in a study where n=1?), and I’ve already pointed out many systematic biases and problems with attempting to infer anything from Roberts’s death.
I’m not saying we can scientifically infer from his premature death that his diet was unhealthy.
I’m saying that his premature death is informal evidence that his diet at best didn’t have a significant positive impact on life expectancy, and at worst was actively harmful. I can’t quantify how much, but you were the one who attempted a quantitative argument and I’ve just criticized your argument, namely your strawman definition of “suspicious death”, using your own data and assumptions, hence it seems odd that you now ask me for assumptions and p-values.
Isn’t the p-value simply 100%-7.5%?