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@thett3
That said I’m totally against the mandates,
100% THIS
Scamdemic
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@ILikePie5
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@Stephen
I hate to break it to you but Farage is a shill.
@RM
Please stop posting to me while you have me on block.
And regardless of what you believe of Farage those ONS figures have not been denied by anyone or any public office and are available to view for yourself.
ONS figures on " how many people have died purely of Covid"? ...............from the Office of National Statistics. Since first lockdown (UK) 17,371 #30
@RM
From Dr John Campbell and his Freedom Of Information Request
Freedom of information revelation
Office of National Statistics. Since first lockdown (UK) 17,371
So regardless of what you believe of Farage those ONS figures have not been denied by anyone or any public office and are available to view for yourself.
Stop posting to me while you have me on block!
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@oromagi
The logic is the loyalty test. Anti-vaxxers get extra credit on their conspiracy theory credentials for risking their family's life and well-being in order to demonstrate club membership. Club membership gets you a feeling of belonging in an age of alienation and gives less educated folks the opportunity to speak authoritatively and expertly (if inaccurately) on a topic they can understand. Anti-vax belief reinforces the losers' conviction that they would be winners if society were not out to get them and grants them justification for just about any anti-societal act or belief those losers care to demonstrate.
Do you have any appreciation for the "risks" involved with not getting a vaccine?
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@Athias
Do you have any appreciation for the "risks" involved with not getting a vaccine?
I lost the majority of my hearing to a childhood case of measles for which a vaccine was available. I guess that is where my appreciation of the risks stems from.
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@Danielle
Now what I don't get about the vaccine skeptics is why they think politicians and doctors all over the world are conspiring to poison or needlessly jab their citizens just for the hell of it. There are other ways to keep Big Pharma profitable. Why would every single country, including our enemies, be espousing the same lies -- and how did they convince the overwhelming majority of the science community across the globe to go along with it? (I get that Sweden was one very unique country, as in small and homogenous, that avoided lockdowns; however, they are nearly 90% vaccinated against Covid now.)
Because you're assuming that these entities are separate. They are ALL answerable to their sponsors. As for the reason the medical/science community would go along with it, well let me just point this out: physicians sport on their lab coats the caduceus, or the winged staff of mercury (a.k.a. Hermes) which is associated with the Baphomet. [I know this for a fact because there are many physicians in my own family.] Why would they do that? And who would want them to do that, especially in an allegedly JUDEO-CHRISTIAN nation?
But even if we were to forget the "conspiracy theories," one needs only apply critical thinking, right? Why were they pushing the vaccine just after a few months of trials despite the fact that vaccines typically undergo years of trials? Why were lockdowns being implemented despite the enormous benefits of Vitamin D intake from sunlight and the ventilation from being out in the open especially as it concerns a respiratory infection? Why did they exaggerate the mortality rates? Or failed to specify the susceptibility of those with compromised immune systems, the elderly, and the obese? Why have there been patents--and this is a verifiable fact--for this virus spanning back to 1984? Or that current strains can be modified? Why is it that after two years of exposure, despite the overwhelming majority of the unnvaccinated having not succumbed to the virus, the media is still being pushing for vaccination?
I'm currently unvaccinated, and outside of my seasonal allergies, I haven't had so much as a sniffle. As a child, I used to read my mother's books on pathology and the number one countermeasure to the contraction of infection is GOOD HYGIENE. Even the CDC will admit as much. I've known people who've been vaccinated--both shots and the booster--and they still caught the virus, so what does vaccination actually accomplish (with quantifiable measure) other than a placebo to this media-induced paranoia?
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@oromagi
I lost the majority of my hearing to a childhood case of measles for which a vaccine was available. I guess that is where my appreciation of the risks stems from.
And you're certain that a Measles vaccine would have prevented this?
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@Athias
And you're certain that a Measles vaccine would have prevented this?
Nothing in medicine is certain. The second dose of measles vaccine is 97% effective at preventing the kind of virulent manifestation that took my hearing. It's like having a shield in battle- it doesn't guarantee you'll survive but when arrows are raining down you will always wish you had one. I wish I'd had a chance at taking those 97% odds.
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@oromagi
Nothing in medicine is certain. The second dose of measles vaccine is 97% effective at preventing the kind of virulent manifestation that took my hearing. It's like having a shield in battle- it doesn't guarantee you'll survive but when arrows are raining down you will always wish you had one. I wish I'd had a chance at taking those 97% odds.
Yes, but those 97% odds are contingent on ecological inferences. It would not have depended on the "odds" and more so your own constitution. For example, I could state according to the numbers that there's a 99% chance that not only one would not catch COVID-19, but also wouldn't succumb to it, but that doesn't mean being unvaccinated insures anything even with a modicum of confidence. Maybe the vaccine would have helped you; maybe it wouldn't.
The statistics of vaccines are heavily misinterpreted and often abused by perceived intellectual authorities (i.e. doctors, scientists, etc.) because seldom do they understand what statistics actually capture and the conclusions which can be rendered from them. If anyone tells you that a vaccine has a 97% chance, for example, of preventing a virus's most virulent manifestation, then they are lying to you--unwittingly or not. Because those odds aren't determined by your own physiology.
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@Athias
Exactly. If you are at risk at losing hearing from measles or at-risk from dying to Covid, then the general statistic of efficacy to you personally is absolutely meaningless. The Moderna vaccine won't save you from being old and morbidly obese. Certainly not at a 99.5 percent rate.
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@Athias
Yes, but those 97% odds are contingent on ecological inferences.
Yep, decades of excellent peer-reviewed studies but yes, those odds are based on inferences made from the general population and not calculated based on my personal charts as a three year old child.
they are lying to you--unwittingly or not. Because those odds aren't determined by your own physiology.
As Twain said- there are lies, damned lies, and then there are statistics. We can agree that a statistic cannot account for your individual circumstances but its a choice between some information that reflects reality as accurately as possible (while being entirely unable to account for your individual circumstance) and no reliable information at all. Its not like there's some option to have science calculate your individual odds based on DNA testing or something. The choice is some real information on which to make a decision or no real information on which to make an decision. And that absence of real information is a vacuum that sucks up a whole lot of stupid, money-grubbing bullshit. Anybody who is telling you that getting a vaccine doesn't improve your chances of surviving a virulent infection by that disease is lying to you.
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@Athias
You should watch a few minutes of this prophet.
We have all made ourselves compromised by relying on medicine over improving our immune systems.
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@oromagi
Yep, decades of excellent peer-reviewed studies
Not even decades of excellent peer-reviewed studies can escape logic.
We can agree that a statistic cannot account for your individual circumstances but its a choice between some information that reflects reality as accurately as possible
It can reflect a reality as accurately as possible, but that doesn't necessarily inform on your reality. At the end of the day, the vaccine "works" or it "doesn't work"; one either contracts the virus, or doesn't contract the virus; after contracting the virus, one either survives or dies; the "odds" remain unchanged.
Its not like there's some option to have science calculate your individual odds based on DNA testing or something.
Limited options do not speak to fact. And that's part of my point. There are conclusions being made about the effects of the vaccine that are beyond anyone's pay-grade--educated or not. Stating that the vaccine will prevent the contraction of the virus is non-factual and irresponsible; stating that an unvaccinated individual is putting others at an unquantifiable "risk" is non-factual and irresponsible; Stating the vaccine "reduces" an unquantifiable risk of contracting and spreading the virus is non-factual and irresponsible. And that has little to do with limited technology, and more to do with a limited grasp on reasoning. Statistics have not informed the aforementioned because it's impossible to provide sufficient controls.
The choice is some real information on which to make a decision or no real information on which to make an decision. And that absence of real information is a vacuum that sucks up a whole lot of stupid, money-grubbing bullshit.
Money-grubbing bullshit unfortunately lies in both information and disinformation.
Anybody who is telling you that getting a vaccine doesn't improve your chances of surviving a virulent infection by that disease is lying to you.
Any one who tells you that a vaccine will save your life is categorically lying to you. And this is not a matter of political division, or even being "Anti-vax." It's a subject of logic: in order for someone to tell you that a vaccine would save your life, they would have to observe that a virus would kill you. And in order for them to determine that, they would have to observe the virus killing you. So how would a person be able to determine a vaccine's efficacy while having to sufficiently control for both your survival and your death? They can tell you that Virus X has killed this many people in this span of time, and I know of a concoction that would boost your immune system enough where post hoc rationalizations make me feel confident you will survive its contraction and manifestation, but that's not Science. That's guesswork.
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@Greyparrot
You should watch a few minutes of this prophet.We have all made ourselves compromised by relying on medicine over improving our immune systems.
This is among the reasons I find Comedians to be incredibly intelligent. George Carlin was no exception.
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@Athias
Limited options do not speak to fact. And that's part of my point. There are conclusions being made about the effects of the drunk driving that are beyond anyone's pay-grade--educated or not. Stating that driving sober will prevent injury is non-factual and irresponsible; stating that a drunk driver is putting others at an unquantifiable "risk" is non-factual and irresponsible; Stating driving sober "reduces" an unquantifiable risk of killing others is non-factual and irresponsible. And that has little to do with limited technology, and more to do with a limited grasp on reasoning. Statistics have not informed the aforementioned because it's impossible to provide sufficient controls.
Any one who tells you that driving sober will save your life is categorically lying to you. And this is not a matter of political division, or even being "Anti-sober." It's a subject of logic: in order for someone to tell you that driving sober would save your life, they would have to observe that a given drive would kill you. And in order for them to determine that, they would have to observe the drive you take,. So how would a person be able to determine drunk driving risk while having to sufficiently control for both your survival and your death? They can tell you that Drunk driving has killed this many people in this span of time, and I know of a driving sober is sufficient for post hoc rationalization make me feel confident you will survive a sober drive, but that's not Science. That's guesswork.
And this is why you’re argument is absurd: and I don’t believe you fully understand what statistics mean.
In two randomized sample of people, one vaccinated and one not - if data shows the one side has higher rates of survival and lower rates of infection - it means the vaccination is saving peoples lives across that population, and reducing infections across that population m - or that the study just so happens to have chosen a broad selection of people who are at inherently lower risk.
But given the data we have fairly decent data on the risk factors of death and disease, much of this can be controlled for; and with large enough sections of the population, with so consistent results in vaccination studies that the probability of just so happening to get less at risk populations across every single vaccine study - bias in selection can be ruled out.
By science and logic: it is demonstrable fact that the vaccines do indeed reduce risk of both infection and death in populations m
Now imagine that you are part of a given population of people with known risk, or survival factors - age, obesity, etc; we can quantify the benefits of the vaccine on that population, and attribute it to the vaccine based on the information above.
On that basis, we can scientifically say that someone like you, has a lower chance of contracting Covid, and dying from it than someone who hasn’t.
Whenever anyone says the vaccine will reduce your risk of contracting Covid, or dying; it’s on that basis of that population. We can’t tell your personal change in risk - only the change in broader comparable controlled populations who are like you.
Hidden risk factors that are unknown only matter in judging efficacy if they are not shared between the control and target groups. There maybe 10% of the population with some specific hidden unknown factor that means that they will die even with the vaccine - or survive without it; provided those individuals are shared between control and target groups - the efficacy factors take it into account. Even if such factors exist - unless they are known, and unless you know whether you have them - that risk factor is indistinguishable from randomness; given that all major clear cut risk factors are controlled for.
That’s not bad science, or guess work - that’s the logical application of statistical analysis.
I mean, let’s take an extreme example. Imagine a vaccine for a virus with 99% mortality. A study on 19,500 deaths out of 20k, and a vaccinated group has only 500 deaths out of 20k.
I cannot tell you for certain whether your actual secret hidden risk of dying goes down or up after taking the vaccine because you maybe special, or have some hidden features that put you in that 500; but I can tell you that a population of people similar to you died 99% of the time before the vaccine, and only 1% of the time with; that’s a clearly valid scientific conclusion and the argument that you shouldn’t argue for the efficacy of the vaccine because the hidden risk factors that maybe spread over both samplings.
Indeed, the very fact that you’re complaining that statistics of a population don’t take into consideration granular unknowable individual personal risk changes or you specifically completely misses the entire point of statistics in the first place.
We can’t tell your personal change in risk - only the change in broader comparable controlled populations who are like you.
That's false. CDC has identified high risk groups. You can tell if you are old or obese, it's not hidden.
Touting a statistic that includes skinny and young people does them no good. It's deliberately misleading. False hope.
We can’t tell your personal change in risk - only the change in broader comparable controlled populations who are like you.That's false. CDC has identified high risk groups. You can tell if you are old or obese, it's not hidden.
The sentence after you said “that’s false” is describing the exact thing you just said is false.
I mean - it’s not like “old and obese” is not a broader comparable population now is it…
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@Ramshutu
What's the efficacy of vaccines on the old and obese?
You can't find that statistic. We can't even have a rational discussion about it because CDC won't publish it.
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@Ramshutu
Limited options do not speak to fact. And that's part of my point. There are conclusions being made about the effects of the drunk driving that are beyond anyone's pay-grade--educated or not. Stating that driving sober will prevent injury is non-factual and irresponsible; stating that a drunk driver is putting others at an unquantifiable "risk" is non-factual and irresponsible; Stating driving sober "reduces" an unquantifiable risk of killing others is non-factual and irresponsible. And that has little to do with limited technology, and more to do with a limited grasp on reasoning. Statistics have not informed the aforementioned because it's impossible to provide sufficient controls.Any one who tells you that driving sober will save your life is categorically lying to you. And this is not a matter of political division, or even being "Anti-sober." It's a subject of logic: in order for someone to tell you that driving sober would save your life, they would have to observe that a given drive would kill you. And in order for them to determine that, they would have to observe the drive you take,. So how would a person be able to determine drunk driving risk while having to sufficiently control for both your survival and your death? They can tell you that Drunk driving has killed this many people in this span of time, and I know of a driving sober is sufficient for post hoc rationalization make me feel confident you will survive a sober drive, but that's not Science. That's guesswork.
Is this supposed to be a reductio ad absurdum? Because it's not. And I would just as well apply my reasoning to drunk driving, too.
And this is why you’re argument is absurd
Oh, so it is supposed to be a reductio ad absurdum? Please demonstrate the logical absurdity.
and I don’t believe you fully understand what statistics mean.
Couldn't be further from the truth but that's a subject for another time.
In two randomized sample of people, one vaccinated and one not - if data shows the one side has higher rates of survival and lower rates of infection - it means the vaccination is saving peoples lives across that population, and reducing infections across that population m - or that the study just so happens to have chosen a broad selection of people who are at inherently lower risk.
No it doesn't. These are post hoc rationalizations which do not account at all any sufficiently controlled measures. You don't have to explain the reasoning of these misinterpretations because my argument is that they're misinterpretations which are premised on fallacious reasoning. Repeating it doesn't make it any less fallacious.
But given the data we have fairly decent data on the risk factors of death and disease, much of this can be controlled for;
No they cannot. These controls operate using ecological inferences.
and with large enough sections of the population, with so consistent results in vaccination studies that the probability of just so happening to get less at risk populations across every single vaccine study - bias in selection can be ruled out.
I'm being generous and characterizing the arguments premised on this fallacious reasoning as "misinterpretations."
Whenever anyone says the vaccine will reduce your risk of contracting Covid, or dying; it’s on that basis of that population. We can’t tell your personal change in risk - only the change in broader comparable controlled populations who are like you.
Once again, you need not repeat to me the reasoning. I'm familiar with the reasoning; it doesn't change that the reasoning is fallacious.
That’s not bad science, or guess work - that’s the logical application of statistical analysis.
No it's not. The logical application of statistical analysis must conform to logical consistency not post hoc and/or cum hoc rationalizations and ecological inferences.
I cannot tell you for certain whether your actual secret hidden risk of dying goes down or up after taking the vaccine because you maybe special,
Not just "for certain"; you wouldn't be able to tell me at all because you'd have to quantify my individual risk, which is independent of any demographic you believe is "like me."
but I can tell you that a population of people similar to you died 99% of the time before the vaccine, and only 1% of the time with;
No, you would be able to tell that 99% of your sample who were unvaccinated may have died before a vaccine, and only one percent with the vaccine. "Of the time" is beyond your pay-grade. And your sample "of the population" would mean nothing to the individual because a person will either survive or succumb--both of which cannot br controlled simultaneously, concurrently, or successively. And if my understanding of statistics serve me correctly, your numbers would be exaggerated.
Indeed, the very fact that you’re complaining that statistics of a population don’t take into consideration granular unknowable individual personal risk changes or you specifically
Am I "complaining" or have I presented an argument?
completely misses the entire point of statistics in the first place.
Accepting the dogma of interpretation rather than understanding how conclusions can be logically extended is missing point.
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@Greyparrot
In a review of data available on the Pfizer-BioNTech, Moderna, and Johnson & Johnson vaccines, efficacy was not significantly different between people with obesity versus those without obesity, reported W. Scott Butsch, MD, MSc, of the Cleveland Clinic in Ohio, and colleagues in the journal Obesity.
Using data from FDA briefing documents and peer-reviewed literature, Butsch's group looked at the efficacy for each available vaccine in the overall trial population and subgroups of people with obesity.
"Analysis of COVID-19 vaccine efficacy in certain disease subgroups has been difficult because the number of trial participants with the disease was too small," said co-author Alexandra Hajduk, PhD, MPH, of Yale School of Medicine in New Haven, Connecticut, in a statement.
"This was not the case for obesity. Because the prevalence of obesity among trial participants was high, and because obesity is highly associated with hospital admission and death in COVID-19, the trial results were able to show that, contrary to concerns of reduced vaccine efficacy in people with obesity, that the vaccines were just as efficacious among persons with obesity compared with persons without obesity," she added.
Looking at the Pfizer vaccine first, the overall efficacy in over 36,000 people without prior infection was 95.0% (95% CI 90.0-97.9) compared with placebo.
When this cohort was divided into those with and without obesity, the vaccine efficacy was 95.4% (95% CI 86.0-99.1) in 13,218 participants ages 16 and older (roughly 32% of the cohort) with a BMI of 30 or higher. Conversely, efficacy was 94.8% (95% CI 87.4-98.3) among the participants without obesity.
For the Moderna vaccine, the overall efficacy was 94.1% (95% CI 89.3-96.8) among participants without prior COVID infection. Among those with obesity, which was about 35% of the overall cohort, efficacy was 95.8% (95% CI 82.6-99.0). Taking that one step further, in a subgroup of participants with severe obesity -- a BMI of 40 or higher -- vaccine efficacy was 91.2% (95% CI 32.0-98.9). In the 901 participants with severe obesity, there was only one case of severe COVID-19 that occurred after vaccination versus 11 cases in 884 participants with severe obesity in the placebo group.
Because the prevalence of obesity among trial participants was high, and because obesity is highly associated with hospital admission and death in COVID-19, the trial results were able to show that, contrary to concerns of reduced vaccine efficacy in people with obesity, that the vaccines were just as efficacious among persons with obesity compared with persons without obesity," she added.
So this is obviously a straight up lie from this woman. Skinny young people generally didn't die from Covid, the ones that did are meaningless statistical outliers, so the efficacy of the vaccine on those people is meaningless. To say it's on equal par or as the lie she states "were just as efficacious " is a clear misrepresentation.
It's not like it's hard to get pharmaceutical doctors to lie to help them make billions. Those misleading articles from paid shills are all over the place.
What I would like to see is the CDC stats on how many vaccinated old and fat people died. It sure as hell isn't what you think it is.
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@Ramshutu
the very fact that you’re complaining that statistics of a population don’t take into consideration granular unknowable individual personal risk changes or you specifically completely misses the entire point of statistics in the first place.
That's it in a nutshell. Well said.
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@oromagi
That's it in a nutshell. Well said.
No it isn't. Statistics--in this context--are mathematical snapshots of trending behaviors, not justification for your pseudo-mathematical "psychic readings." You and Ramshutu have presented arguments which are premised on fallacious reasoning (I.E. POST HOC FALLACY AND ECOLOGICAL INFERENCE FALLACY) and no peer-reviewed study--however meticulous--resolves this. I am not nitpicking; it's by reason of my knowing "the entire point of statistics in the first place" that I'm pointing out these irresponsible conclusions.
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@Athias
We are given a choice of two doors with the information that behind one door lies a hungry tiger ready to pounce and behind the other is $100,000. You and I both observe 100 other people choosing between door A and door B. I note that 97 times out of 100, the tiger lies behind door A and the money lies behind door B and only 3% of the time does it happen the other way around. Based on that observation, I decide to go for door B since that is almost always the door with the money behind it. You state that those 100 people do not reflect your individual circumstance and choice and so you will ignore that data and choose door A. While we both agree that there are no guarantees, which of us is more likely to get eaten?
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@Athias
No it isn't. Statistics--in this context--are mathematical snapshots of trending behaviors, not justification for your pseudo-mathematical "psychic readings." You and Ramshutu have presented arguments which are premised on fallacious reasoning (I.E. POST HOC FALLACY AND ECOLOGICAL INFERENCE FALLACY) and no peer-reviewed study--however meticulous--resolves this. I am not nitpicking; it's by reason of my knowing "the entire point of statistics in the first place" that I'm pointing out these irresponsible conclusions.
It's more disingenuous than that. It's assuming all hidden factors can't be accounted for or explored, and many are lumped as hidden when they clearly are not.
I'm still waiting for the educated elite on this site to provide me with the CDC statistic I asked for. Still waiting.
which of us is more likely to get eaten?
The elderly and the obese, just like it was with Covid.
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@oromagi
We are given a choice of two doors with the information that behind one door lies a hungry tiger ready to pounce and behind the other is $100,000. You and I both observe 100 other people choosing between door A and door B. I note that 97 times out of 100, the tiger lies behind door A and the money lies behind door B and only 3% of the time does it happen the other way around. Based on that observation, I decide to go for door B since that is almost always the door with the money behind it. You state that those 100 people do not reflect your individual circumstance and choice and so you will ignore that data and choose door A. While we both agree that there are no guarantees, which of us is more likely to get eaten?
Your analogy doesn't capture the argument correctly. In your analogy, the odds are determined not by the 100 people, individually or collectively, who chose between doors A and B, but by the person, organization, entity which placed both the tiger and money behind each door. One's individual circumstances would be irrelevant.
A more apt analogy would be as follows:
Athias is a 6+ ft, 30+ year old, French Polynesian man.
A peer-reviewed study found out that 9.5 out of 10 in their sample (n =15,000) of 6+ ft, 30+ year old French Polynesian men--which did not include Athias--wear white shirts on Saturdays.
Therefore, there's a 95% chance that Athias--whose description meets the parameters of this peer-reviewed study--wears white shirts on Saturdays.
Why is this reasoning fallacious? Because the extension of this reasoning to its conclusion operates on factors that are independent of my individual behavior. It attempts an ecological regression while assuming ceteris paribus that behavior within restrictive parameters is homogeneous. And it should be noted that I do not own a white shirt. So even if the findings of that hypothetical peer-reviewed study were true, my chances of wearing a white shirt on Saturdays would not be informed by it.
So how can we extrapolate this reasoning and place it within the context of a corona virus vaccine?
Athias is a 6+ ft, 30+ year old, unvaccinated French Polynesian man.
A peer-reviewed study found out that 9.5 out of 10 in their sample (n =15,000) of 6+ ft, 30+ year old French Polynesian men--which did not include Athias--succumbed to COVID-19.
Therefore, there's a 95% chance that Athias--whose description meets the parameters of this peer-reviewed study--will succumb to COVID-19.
How is the reasoning for the second any less fallacious than the first? Isn't this also an attempt at ecological regression which ASSUMES ceteris paribus that immunological responses are homogeneous? How is the sample data "predictive" and not just subject to instance? Rendering conclusions about one's mortality using fallacious reasoning is irresponsible, oromagi. This may be the norm in academia, but that doesn't make it right.
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@Athias
No, you would be able to tell that 99% of your sample who were unvaccinated may have died before a vaccine, and only one percent with the vaccine. “Of the time" is beyond your pay-grade. And your sample "of the population" would mean nothing to the individual because a person will either survive or succumb--both of which cannot br controlled simultaneously, concurrently, or successively. And if my understanding of statistics serve me correctly, your numbers would be exaggerated.
Putting aside the obnoxious quote ladders that make it near impossible to engage In a discussion for a moment; the above post entirely, and the quoted section specifically illustrates that your understanding of statistics is profoundly failing you at a fairly fundamental level - so much so it’s hard to know where to begin. But let me try.
A regular dice with six sides, has a 1/6 chance of turning up any of the individual numbers. You can assess the overall likelihood by statistically analyzing multiple rolls. A specific roll, may have force, angle, direction, etc; that gives it a 99.99% chance of rolling a 6 at that specific time.
If you weight the dice, the same is true; the dice may show a 6 at least 50% of the time, but a given roll may have a 99.9% chance of rolling a 3 given a specific subset of conditions that are unknown.
Weighting a dice changes the probability of a given roll - even though the unknown conditions of that specific roll may only generate one outcome.
The same is true whether you have a single dice rolled 1000 times, or 1000 die rolled once - with the only caveat with the latter is for those dice to inform the probability of another they must be drawn from a similar population.
Just because I don’t know what the true probability of rolling a six given the specific conditions at the time, or for a specific dice for which the probability of its population is known does not alter the fact that the chance is 1/6; nor does it alter the fact that the chance increases to, say, 1/2 if the dice is weighted, facts you can determine on any individual dice no matter whether it’s ever been rolled before; before you roll it. That is true of a dice that you roll once, or 1000 die that you roll once each. The probability is the sum of all rolls in all potential conditions - many of which cannot be known or controlled.
Probability is not rendered invalid because of unknown conditions and factors - probability is literally an expression of those unknown conditions and factors when only composite data is known
Or to be more specific to vaccines, given that I can smell a strawman coming : You could take a warehouse full of random second-hand dice; each of which you can only roll only once; take a large random sample; weight half and roll them all. You have to make generalizations about an individual based on population without being able to control for outcome at an individual level. The most important thing is we know people vary so we need to know whether a sample is appropriate. If I take from one side of the warehouse, I may not get an accurate representation of the dice. Likewise the age of dice, may play a role, top or bottom of a box, Color, size; but we can adjust for factors we know make a difference, if we do that and randomly sample account for this; the remaining subset of randomly chosen dice should be representative - and will include enough of various factors of all individuals to be representative - exemplars are only missed out or under sampled if sufficiently rare to not appreciably impact the outcome. This is not to say the sampling is perfect; but it’s testable and, thus far, is based on known biological factors yielding predictive power - scientific.
Taking this control sample allows you to establish baseline probability of the warehouse - it provides an understanding of the overall state of the dice in the warehouse - with high levels of confidence that any specific dice will be represented by the population, or to be such a rare outlier that its existence doesn’t change the population probability - this baseline probability takes into account the underlying state and conditions of all the dice the sample - some dice may already be weighted, or weighting will not work on them, as an example.
The second weighted sample allows you to establish the change in baseline probability after the controlled parameter has been added. Both samples will contain similar populations of weighted dice, or ones for which the weighting will not work - you’ve corrected for age and size and colour, so providing picking any random 100 large black dice from the bottom of boxes at the far end of the warehouse is equally likely to turn up loaded size as any other random selection of 100 large black size from the bottom of boxes at the far end of the warehouse - those numbers won’t be appreciably different
If you pull a new random dice from the pile ; you can say with some confidence that the chance of you rolling a six increases by a certain amount if you weight the dice. This is true even if you don’t know the specific conditions of that dice. This is because the possible specific conditions and their probability of that dice being non standard is part of the baseline.
The increase in chances of rolling a six incorporates both of the possibility of you picking up a dice for which weighting has no impact, and one for which it does.
For example - if there are no weighted dice in the warehouse, weighting would improve chances of rolling a six by 100x, if there are weighted dice that are unaffected by more weighting - that number would go down to say - 80x.
Rolling Any given dice would be 80x more likely to turn up a six: a probability which incorporates the probabilities of a.) a weighted dice not rolling a six by chance, b.) a weighted dice turning up a six because of the intended action of weighting and c.) a weighed dice not showing a 6 because of some ineffectiveness if the weighting process due to the dice. The statistics applied to the individual is based on the principle that this dice is a member of the broader sample population; and is an expression of the break down of various conditions in that population. When you talk about the probability of the individual - that probability incorporates all those unknowns due to that sampling.
For Covid, if the illness and survival rate for your risk group (age, weight, etc), is 10% to become sick, and 0.1% to die, and that same risk group reduces to 1% and 0.01% - then your risk has dropped by a factor of 10.
You could have some unknown predispoition that means you will die with or without the vaccine; but it’s also more likely you have a predisposition that means you will live with the vaccine and die without; the statistics tells us that the prevelance of the former is at most 0.1% and latter is around 0.9%.
Unless you actually know what that predisposition is, and whether you have it - it’s only possible to express it as a probability determinable by a population - a probability incorporated into the quantified risk reduction. Your risk has still reduced by 0.9% because that is the probability of having a vaccine preventable disposition - even while the 0.1% remains.
Likewise with seatbelts. Seatbelts will improve your chances of survival. Not because any specific crash you are in yield less chance of dying, but because some types of crashes you can get in will be survivable with a seatbelt; the chances of occurrence of those types of crash can be determined, with the probability of risk incorporating your chances of getting into one of those, vs one where a seat belt will not help. As it is not possible to tell or control all the individual factors - it must be expressed as a probability based on occurrence within a population controlled for known factors.
Likewise, drunk driving ; the absurdity I point out here is down to your failure to appreciate the meaning of the numbers.
The statistics do not imply that on a given drive home on Sunday, where a specific accident - say a truck plows into you from behind - would be more or likely to occur whilst drunk or sober; but because there are a subset of accidents which can be caused by being drunk or prevented by being sober that have a given probability of occurring based on population statistics. The increase in risk from drunk driving incorporates that general change in risk given that it’s not possible to calculate or know all the factors to know the exact per journey risk - in exactly the same way that you can’t calculate all relevant physics for a dice.
That’s how probability works. The boiling down of unknown events in terms of a likelihood of occurring. For risk statistics - it’s all baked into the numbers. It’s the mechanism by which insurance companies can consistently and reproducibly make billions of dollars; by accurately assessing risk of an individual by virtue of analyzing the population they are part of.
I would highly suggest you find an actuary, and suggest that the risk to an individual cannot be determined by assessing occurrence in a population. If you’re lucky, they will be incapacitated from laughter so long you could steal their jaguar.
You can’t complain that your specific set of conditions that determine whether you will live or die are unknown so you cannot speculate as to the efficacy of a vaccine ; because expressing things you don’t know based on their chance of occurrence in a particular scenario is the whole freaking point of having probability and statistics in the first place.
It’s every bit as stupid as suggesting that you cannot say that weighting a dice increases the probability of turning up the weighted number on a given roll - because your cannot account for all conditions of the roll itself. That’s not what probability means.
Probability is inherently expressing differences in unknown or unknowable factors in numerical form based on their occurrence: and the fact that you’re objecting to an expressed probability based on the factors that are unknown or unknowable is showing your issue is not with vaccines, or any medical study - but with what probability actually is. This is why I’m calling your absurd argument absurd.
Quantum physics aside - it should be possible to reasonably determine exactly whether you would live or die with Covid if we had all the information - at which point we would cease to need terms like risk, or probability. We don’t. All we can do work under the testable and confirmed premise that there is some combination of random happenstance we can’t determine and non-random hidden risk factors which we can’t correlate to any discernible criteria.
This means all we can say is you have some derived probability of encountering such happenstance or having said unknown risk factors - a probability verifiably decreases with vaccination.
As shown above it is both accurate, valid and scientific to state that your risk decreases with vaccination - it’s not a statement on your exact specific personal circumstances or saying anything specific about a given outcome: that’s not what probability is - but the probability of you being a member of the population that through whatever hidden parameters or stats- ends up dying from COVID. That probability of being a member of that population after vaccination decreases (a probability derived from testable and falsifiable methodology) - which means that on a logical, mathematical, and scientific basis your risk is reduced.
You can’t complain that your specific set of conditions that determine whether you will live or die are unknown so you cannot speculate as to the efficacy of a vaccine ; because expressing things you don’t know based on their chance of occurrence in a particular scenario is the whole freaking point of having probability and statistics in the first place.
It’s every bit as stupid as suggesting that you cannot say that weighting a dice increases the probability of turning up the weighted number on a given roll - because your cannot account for all conditions of the roll itself. That’s not what probability means.
Probability is inherently expressing differences in unknown or unknowable factors in numerical form based on their occurrence: and the fact that you’re objecting to an expressed probability based on the factors that are unknown or unknowable is showing your issue is not with vaccines, or any medical study - but with what probability actually is. This is why I’m calling your absurd argument absurd.
Quantum physics aside - it should be possible to reasonably determine exactly whether you would live or die with Covid if we had all the information - at which point we would cease to need terms like risk, or probability. We don’t. All we can do work under the testable and confirmed premise that there is some combination of random happenstance we can’t determine and non-random hidden risk factors which we can’t correlate to any discernible criteria.
This means all we can say is you have some derived probability of encountering such happenstance or having said unknown risk factors - a probability verifiably decreases with vaccination.
As shown above it is both accurate, valid and scientific to state that your risk decreases with vaccination - it’s not a statement on your exact specific personal circumstances or saying anything specific about a given outcome: that’s not what probability is - but the probability of you being a member of the population that through whatever hidden parameters or stats- ends up dying from COVID. That probability of being a member of that population after vaccination decreases (a probability derived from testable and falsifiable methodology) - which means that on a logical, mathematical, and scientific basis your risk is reduced.