In this case, he died apparently died suddenly, at an age where sudden death is rather unusual in people with no self-reported history of serious health problems. Also, this kind of sudden death is usually the result of cardiovascular problems, i.e. heart attack or stroke. Last, he was known to be regularly consuming a lot of concentrated fat on a regular basis (half a stick of butter a day; and perhaps olive oil and flax seed on top of it); fatty foods have long been suspected as playing a role in cardiovascular problems, that they cause lipids to build up in the blood stream and clog up the works.
Again, this is post hoc reasoning conjured upon observing the exact particulars of his death, and so suspect even without considering additional questions like whether fat is all it’s cracked up to be, what his medical tests were saying, etc.
Well do you agree that what happened is more ‘suspicious’ than if he had died at the age of 75 from lung cancer?
Yes.
Suit yourself, but it strikes me as confusing that I would make a claim and you would respond with a calculation which seems to address the claim but actually doesn’t.
My calculation addresses a major part of the Bayesian calculation: the probability of an observed event (‘death’) conditional on the hypothesis (‘his diet is harmful’) being false. Since dying aged 52-80 is so common, that sharply limits how much could ever be inferred from observing dying.
Again, this is post hoc reasoning conjured upon observing the exact particulars of his death
Actually I don’t know the exact particulars of the death. But I do agree with what I think is your basic point here—it’s extremely easy to make these sorts of connections with the benefit of hindsight and that ease might be coloring my analysis. At the same time, I do think that—in fairness—the death is pretty high on the ‘suspicious’ scale so I stand by my earlier claim.
My calculation addresses a major part of the Bayesian calculation:
Perhaps, but it seems to me you are throwing the baby out with the bathwater a bit here by ignoring the facts which make this death quite a bit more ‘suspicious’ than other deaths of men in that age range. More importantly, you don’t seem to dispute that your calculation doesn’t really address my claim.
Look, I agree with your basic point—the premature death of a diet guru, per se, doesn’t say much about the efficacy or danger of the diet guru’s philosophy. No calculation is necessary to convince me.
More importantly, you don’t seem to dispute that your calculation doesn’t really address my claim.
I did dispute that:
My calculation addresses a major part of the Bayesian calculation...that sharply limits how much could ever be inferred from observing [Roberts] dying.
(A simple countermeasure to avoid biasing yourself with anecdotes: spend time reading in proportion to sample size. So you’re allowed to spend 10 minutes reading about Roberts’s 1 death if you then spend 17 hours repeatedly re-reading a study on how fat consumption did not predict increased mortality in a sample of 100 men.)
My calculation addresses a major part of the Bayesian calculation...that sharply limits how much could ever be inferred from observing [Roberts] dying.
I wouldn’t call it “major” because (1) you refuse to assign a probability to an event I stated I thought was likely; and (2) the main point of your calculation was pretty non-controversial and even without a calculation I doubt anyone would seriously dispute it.
Let’s do this: Is there anything I stated with which you disagree? If so, please quote it. TIA.
I wouldn’t call it “major” because (1) you refuse to assign a probability to an event I stated I thought was likely;
It puts an upper bound as I said. Plug the specific conditional I calculated into Bayes theorem and see what happens. Or look at a special case: suppose conditional on the diet not being harmful, Roberts had a 50% chance of dying before 80; now, what is the maximal amount in terms of odds or decibels or whatever that you could ever update your prior upon observing Roberts’s death assuming the worsened diet risk is >50%? Is this a large effect size? Or small?
(Now take into account everything you know about correlations, selection effects, the plausibility of the underlying claims about diet, what is known about Roberts’s health, how likely you are to hear about deaths of diet gurus, etc...)
(2) the main point of your calculation was pretty non-controversial and even without a calculation I doubt anyone would seriously dispute it.
So what? One can trivially put an upper and lower bound on any probability: No probability can exceed 1 or be lower than 0. But it ain’t “major” to say so. On the contrary, it’s trivial.
Anyway, please answer my question: Was there anything in my original post with which you disagreed? If so, please quote it. TIA.
Again, this is post hoc reasoning conjured upon observing the exact particulars of his death, and so suspect even without considering additional questions like whether fat is all it’s cracked up to be, what his medical tests were saying, etc.
Yes.
My calculation addresses a major part of the Bayesian calculation: the probability of an observed event (‘death’) conditional on the hypothesis (‘his diet is harmful’) being false. Since dying aged 52-80 is so common, that sharply limits how much could ever be inferred from observing dying.
Actually I don’t know the exact particulars of the death. But I do agree with what I think is your basic point here—it’s extremely easy to make these sorts of connections with the benefit of hindsight and that ease might be coloring my analysis. At the same time, I do think that—in fairness—the death is pretty high on the ‘suspicious’ scale so I stand by my earlier claim.
Perhaps, but it seems to me you are throwing the baby out with the bathwater a bit here by ignoring the facts which make this death quite a bit more ‘suspicious’ than other deaths of men in that age range. More importantly, you don’t seem to dispute that your calculation doesn’t really address my claim.
Look, I agree with your basic point—the premature death of a diet guru, per se, doesn’t say much about the efficacy or danger of the diet guru’s philosophy. No calculation is necessary to convince me.
I did dispute that:
(A simple countermeasure to avoid biasing yourself with anecdotes: spend time reading in proportion to sample size. So you’re allowed to spend 10 minutes reading about Roberts’s 1 death if you then spend 17 hours repeatedly re-reading a study on how fat consumption did not predict increased mortality in a sample of 100 men.)
I wouldn’t call it “major” because (1) you refuse to assign a probability to an event I stated I thought was likely; and (2) the main point of your calculation was pretty non-controversial and even without a calculation I doubt anyone would seriously dispute it.
Let’s do this: Is there anything I stated with which you disagree? If so, please quote it. TIA.
It puts an upper bound as I said. Plug the specific conditional I calculated into Bayes theorem and see what happens. Or look at a special case: suppose conditional on the diet not being harmful, Roberts had a 50% chance of dying before 80; now, what is the maximal amount in terms of odds or decibels or whatever that you could ever update your prior upon observing Roberts’s death assuming the worsened diet risk is >50%? Is this a large effect size? Or small?
(Now take into account everything you know about correlations, selection effects, the plausibility of the underlying claims about diet, what is known about Roberts’s health, how likely you are to hear about deaths of diet gurus, etc...)
One would think so.
So what? One can trivially put an upper and lower bound on any probability: No probability can exceed 1 or be lower than 0. But it ain’t “major” to say so. On the contrary, it’s trivial.
Anyway, please answer my question: Was there anything in my original post with which you disagreed? If so, please quote it. TIA.
Your countermeasure seems to recommend never reading fiction. Feature or bug?