365 days * 75 years = 54,750 chambers. 365.25 days (for leap years) gets to 54,788.
Where did the two days go?
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365 days * 75 years = 54,750 chambers. 365.25 days (for leap years) gets to 54,788.
Where did the two days go?
The worst case is a risk that has a low ensemble HR and low life years impact, but will kill you personally very soon if you take the wrong action. Eating peanuts has an HR of 1, unless you are prone to fatal anaphylaxis from peanuts. HRs are useful for (and biased towards) doctors protecting as many humans as possible, but as an individual you should try to discover your peanut allergies as early as possible and protect yourself against them.
Statistics and other lies. One interesting point the article touches - there was a study concluding that if you quit smoking at 40 your life expectancy basically equalizes with people who did not smoke in their life. It is an encouraging message that it is never too late to quit. Then again it also sends a different message - you can smoke as you wish in your 20s. Just yesterday I saw an article on Instagram that the…
My understanding is that this is a statement of how confident we are in the evidence that smoked meats and sausages are carcinogenic. Essentially, we are very sure that smoking is very carcinogenic and we are also very sure that smoked meats and sausages are a tiny bit carcinogenic.
The most important part of this for a living human being is touched on at the end. You only die once. Life expectancy is an ensemble mean over a population, and "you are not a population". You need to try to avoid risks that are going to kill you personally, not risks that affect aggregate life expectancy (there's overlap of course). Tinkering with HR-translated-to-life-years I think actually blurs that focus for ind…
At any instant, only about 1/6th will get shot. However, your own probability will rapidly converge to 1 of being shot.
The places where proportional hazards gets squirrely (very long observation times, crossing curves) are a small fraction of the use cases of survival analysis, and dunking on them for "not being Bayesian" or whatever misses this broader context.
The most important part of this for a living human being is touched on at the end. You only die once. Life expectancy is an ensemble mean over a population, and "you are not a population". You need to try to avoid risks that are going to kill you personally, not risks that affect aggregate life expectancy (there's overlap of course). Tinkering with HR-translated-to-life-years I think actually blurs that focus for ind…
Relatedly, a common confusion is the use of probability in ergodic and non ergodic processes. The best example I have come across is that of a million people playing Russian Roulette with a six chamber revolver, in repeat mode. At any instant, only about 1/6th will get shot. However, your own probability will rapidly converge to 1 of being shot.
This is missing the most important thing which is why HRs are so damn useful . It's because (a) survival analysis is very statistically powerful, but (b) many survival curves do not follow a very well-described parametric function. The genius of David Cox was in realizing that, when proportional hazards hold, you can just cancel out the unknown survival function and get the multiplicative hazard ratio immediately, in…
They are extremely useful for that, yes.
Earlier quoted context omitted.
> Just yesterday I saw an article on Instagram that they are putting smoked meats and sausages and similar products in the came cancerogenic category as smoking. But not the same lung capacity impact category .. the emphysema rates from smoked meats are considerably lower than those from smoking.
I think it was just cancer overall. One kills you lings, another kills you gut, heart and etc. We know that smoke itself is really really bad for you. Open fire is bad for you. Sitting around campfire with a glass in your hand and a guitar might be really really bad for you.
The most important part of this for a living human being is touched on at the end. You only die once. Life expectancy is an ensemble mean over a population, and "you are not a population". You need to try to avoid risks that are going to kill you personally, not risks that affect aggregate life expectancy (there's overlap of course). Tinkering with HR-translated-to-life-years I think actually blurs that focus for ind…
Describing a benefit (or cost) over a population doesn’t directly translate to decision making at the individual level.
We can say that you should alway take a bet that has an 80% probability of a 10x payout, because the outcome is positive, it wouldn’t be smart to bet your entire network as many outcomes are negative.
> This is essentially the observation Keyfitz made in his 1977 paper, “What Difference Would It Make if Cancer Were Eradicated?” Cancer is responsible for 18 percent of deaths, so does that mean eradicating it would increase lifespan by 18 percent, or around 13.6 years? Nope, Keyfitz says, it’s only 2.3 years.
A very interesting thought!