In a more serious vein, you've hit on a recurring flaw in most analyses supporting the inoculations -- the lack of a proper apples-to-apples comparison.
The consequences of this omission are most visible when one takes a "big data" perspective and looks at the epidemiological data at the country level (state level is best for most of the US due to geographic size).
It is at that level that the absurdity of the pro-vaccine clinical research becomes apparent. If the inoculations were as effective as claimed, most if not all of the statistical observations I write about would be IMPOSSIBLE.
We would not have Big Data analysis showing the inoculations raise incidence of COVID-19 in almost every country.
"The reason individual studies are able to make their impossible claims is the analytical error of comparing dissimilar groups"
Thats the rub, isn't it? Exactly why I point out every chance I get that the vaccination population is a completely different population than the unvaccinated population. They are not random samples from the same population. The differences in the populations are more prominent in older populations (those who die from COVID) than younger ones (who are more homogenous when it comes to COVID outcomes and comorbidities in the first place). But yeah... It is funny how the indicators changed over time.... Cases, hospitalizations, r values, etc.... Then once the vaccine came it was just vaccinated vs unvaccinated. Nothing else mattered.
In a more serious vein, you've hit on a recurring flaw in most analyses supporting the inoculations -- the lack of a proper apples-to-apples comparison.
The consequences of this omission are most visible when one takes a "big data" perspective and looks at the epidemiological data at the country level (state level is best for most of the US due to geographic size).
It is at that level that the absurdity of the pro-vaccine clinical research becomes apparent. If the inoculations were as effective as claimed, most if not all of the statistical observations I write about would be IMPOSSIBLE.
We would not have Big Data analysis showing the inoculations raise incidence of COVID-19 in almost every country.
https://allfactsmatter.substack.com/p/how-many-red-flags-are-enough
We would not not have epidemiological data showing Omicron rising to dominance even after a majority of a given population was inoculated.
https://allfactsmatter.substack.com/p/vaccine-failure-against-omicron-in
These observed epidemiological phenomena cannot happen with the claimed efficacies of the inoculations.
The reason individual studies are able to make their impossible claims is the analytical error of comparing dissimilar groups.
Sadly, this has become a standard "research" methodology for COVID-19.
"The reason individual studies are able to make their impossible claims is the analytical error of comparing dissimilar groups"
Thats the rub, isn't it? Exactly why I point out every chance I get that the vaccination population is a completely different population than the unvaccinated population. They are not random samples from the same population. The differences in the populations are more prominent in older populations (those who die from COVID) than younger ones (who are more homogenous when it comes to COVID outcomes and comorbidities in the first place). But yeah... It is funny how the indicators changed over time.... Cases, hospitalizations, r values, etc.... Then once the vaccine came it was just vaccinated vs unvaccinated. Nothing else mattered.
This is why the saying goes "there are lies, damned lies, and statistics."
When all else fails, move the goalposts.
Warning: reading sentences like this may cause sudden expulsions of the morning coffee from the mouth, accompanied by wicked laughter.
"Even someone who took a watered down math course like “Math for Doctors” can see why that is a terrible comparison."
(I appreciate well done sarcasm!)