Well, technically you cannot "prove" effectiveness similar to the way you prove "correctness" in math. All you are saying is that it is unlikely the observed effects happened by chance. However, almost all large clinical trials have been shown to suffer from biased population selection, so that immediately undermines any claims where the effect size is small. Also, that "statistical significance" notion is hardly objective as at its core lie a number of very questionable assumptions (randomness being one of them), and multiple studies have been published arguing that scientists should spend a significant time warning the public that their results are only preliminary and subject to revision after being tested by the ultimate arbiter - time. Needless to say, it is more likely to see pigs fly than a well-funded scientist admonish the public that the billion-dollar clinical trial that he/she just completed is little more than biased data interpretation (and sometimes even outright fraud!). There have been a few recent "controversial" publications calling for completely abandoning the concept of "statistical significance" precisely because of its abuse for political/financial gain, but I don't think those efforts will go anywhere until the public itself learns NOT to trust lofty claims based on statistical "results".
Scientists Call For Abandoning The Concept Of "statistical Significance"
When somebody emailed Peat with the latest study showing a highly statistically significant outcome that immunosuppression was a viable treatment of autoimmune conditions, Peat's response was that most studies with "statistically significant" results are actually quite insignificant and often...
Finally, perhaps one of the best explanations of the mismatch between reality and what clinical trials want us to believe is the work of Dr. Ioannidis, who was a mainstream hero up until a few months ago when he decided to speak against the pandemic and need for lockdowns, and has since become a pariah not unlike HIV discoverer (and Nobel laureate) Luc Montagnier who has spent the last 9+ months telling anybody willing to interview him that the coronavirus is man-made, and now there is evidence backing that claim.
Uncanny similarity of unique inserts in the 2019-nCoV spike protein to HIV-1 gp120 and Gag
We are currently witnessing a major epidemic caused by the 2019 novel coronavirus (2019-nCoV). The evolution of 2019-nCoV remains elusive. We found 4 insertions in the spike glycoprotein (S) which are unique to the 2019-nCoV and are not present in other coronaviruses. Importantly, amino acid...
Montagnier also keeps saying that mRNA vaccines may cause cancer, CVD, and even HIV/AIDS. Aside from Peat's comments on the dangers of mRNA vaccines, a recent Australian trial was stopped because people started tested positive for HIV.
COVID-19 vaccine(s) makes people test positive on an HIV test
As many of the readers here remember, Peat mentioned in several interviews that one of the concerns he had with the various mRNA vaccines developed for COVID-19 was that most of them contain a protein fragment from HIV. He stated that the introduction of such retroviral species in the organism...
Anyways, unfortunately the invaluable work of Ioannidis exposing the bias/fraud in science will now likely be "tainted" by his pandemic comments and people will mostly stop paying attention to it. Needless to say, Ioannidis' work below never came up when the results of the COVID-19 vaccine trials were being presented to the public.
Why Most Published Research Findings Are False - Wikipedia
A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data
A fiasco in the making? As the #coronavirus pandemic takes hold, we are making decisions without reliable data.
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