Apologies but I should have elaborated on one crucial point.
This study is the epitome of correlation not being causation. The issue with this paradigm is that the study doesn't provide any ability to differentiate vaccination from other variables. It is the author, and reporters such as Moynihan, that infer that these results are associated with vaccination, essentially taking correlative data and infer some sort of causative feature in lieu of no variable control.
The fact that many people are reporting on this study without looking at some egregious issues in the methodology is rather concerning as they are making bold assertions when the evidence shouldn't allow for it.
Early in the vaccine distribution comments were made on multiple Substack discussions about how more potent & greater adverse reaction vaccine lots appeared to be distributed to conservative states.
I've heard of the hot lots although I haven't looked into it too deeply. I haven't heard of the hot lots being distributed to conservative states though since that would be a pretty difficult feat to pull off and target the right people in my opinion, unless it's a very broad approach that doesn't quite care to be slightly nuanced.
So the researchers makes a few remarks through the article in regards to an "age bin". The bin is pretty much their shortcut to lump people into different, well, bins so it makes the analysis easier I believe.
The biggest issue is that the bin is pretty wide aside from the higher ages which even hints that age is critical here:
"The age bins used were 25-64, 65-74, 75-84, and 85-and-older"
So this was likely done to age-match via the bin, then the numbers were likely aggregated together to come up with their results.
So it could very well be that age and health is far more critical in these results, and that vaccination may have slightly helped more. I'm not sure, since the data is so messy that it's just polluted by so many confounding variables, which is why I can't see any value in this study to be quite honest.
The left chart really doesn't make sense since I really don't know how you can construct a curve without any data points. The right one does run counter to the researchers since it already controls for vaccination as marked by the x-axis. Therefore, we would assume that if the hypothesis that low vaccination is the main factor in excess deaths, we would expect a similar curve similar to that of the left chart. However, the wide gap would mean that it can't just be low vaccination alone, hence why this would at least suggest other variables at play here.
That's at least my assessment based on that value. The researchers make no note about the discrepancy only to argue that the discrepancy disappears at higher vaccination rates, which again runs counter to the argument that they are making.
Apologies but I should have elaborated on one crucial point.
This study is the epitome of correlation not being causation. The issue with this paradigm is that the study doesn't provide any ability to differentiate vaccination from other variables. It is the author, and reporters such as Moynihan, that infer that these results are associated with vaccination, essentially taking correlative data and infer some sort of causative feature in lieu of no variable control.
The fact that many people are reporting on this study without looking at some egregious issues in the methodology is rather concerning as they are making bold assertions when the evidence shouldn't allow for it.
Ideology>>>Truth, in a post-truth world.
Early in the vaccine distribution comments were made on multiple Substack discussions about how more potent & greater adverse reaction vaccine lots appeared to be distributed to conservative states.
I've heard of the hot lots although I haven't looked into it too deeply. I haven't heard of the hot lots being distributed to conservative states though since that would be a pretty difficult feat to pull off and target the right people in my opinion, unless it's a very broad approach that doesn't quite care to be slightly nuanced.
Since it is all a DOD 'OP' as we found out from Sage's latest, it actually wouldn't be hard at all. https://substack.com/inbox/post/77641917
So the researchers makes a few remarks through the article in regards to an "age bin". The bin is pretty much their shortcut to lump people into different, well, bins so it makes the analysis easier I believe.
The biggest issue is that the bin is pretty wide aside from the higher ages which even hints that age is critical here:
"The age bins used were 25-64, 65-74, 75-84, and 85-and-older"
So this was likely done to age-match via the bin, then the numbers were likely aggregated together to come up with their results.
So it could very well be that age and health is far more critical in these results, and that vaccination may have slightly helped more. I'm not sure, since the data is so messy that it's just polluted by so many confounding variables, which is why I can't see any value in this study to be quite honest.
The left chart really doesn't make sense since I really don't know how you can construct a curve without any data points. The right one does run counter to the researchers since it already controls for vaccination as marked by the x-axis. Therefore, we would assume that if the hypothesis that low vaccination is the main factor in excess deaths, we would expect a similar curve similar to that of the left chart. However, the wide gap would mean that it can't just be low vaccination alone, hence why this would at least suggest other variables at play here.
That's at least my assessment based on that value. The researchers make no note about the discrepancy only to argue that the discrepancy disappears at higher vaccination rates, which again runs counter to the argument that they are making.