Thank you for this analysis - the most thorough and balanced review I've seen!

Have you analyzed the serious and adverse reactions between the placebo and vaccinated groups? I'd be curious to know if the results were statistically significant.

Taking my time going through these well researched and presented data Chris. Thank you! I will share the link to your substack. I had the J&J back in April of 2021. Thought it was the lesser of the 3 evils. No issues afterwards and am trying to avoid a booster to go to Italy this summer. I'm 54 fit, metabolically heathly and topped off on my supplements. No Covid infection that I know of and I work in the hospital (pathology)

The trials were a complete sham and useless. The control groups were destroyed on purpose and the limits of length were also designed to eliminate major faults. The FDA and CDC were going to approve this mRNA substance (IT WAS NEVER A VACCINE!) because of the faked emergency and pressure from the DoD and HHS as well as WHO.

It is now more than obvious that covid was not a threat to 99.5% of the population. And only a severe threat to those with other medical difficulties. If you feel that mRNA substances are safe, go ahead and keep getting boosters and good luck.

"Using this calculator, the difference in mortality rates is P=0.41 and is not statistically significant:"

Doesn't P=0.41 mean the odds that the null hypothesis is correct? In other words, the hypothesis that vaccines cause higher rates of all-cause mortality is to be slightly preferred?

If the p-value were 0.05, that would be the odds that the null hypothesis is correct--5%.

If anything, the p-value suggests that the study was underpowered to consider all-cause mortality. As pharma employs statisticians and is not new to the vaccine rodeo, pharma must have known what numbers of participants were needed to power the study sufficiently for all-cause mortality statistics to show a clear signal for either the null hypothesis or for the vaccine increases mortality hypothesis. And the FDA wasn't interested in pursuing this question, which ought to be concerning for everybody.

The phrase, "is not statistically significant," should be banned since it is misleading.

"Doesn't P=0.41 mean the odds that the null hypothesis is correct?"

We don't speak of showing the null hypothesis to be correct, but rather failing to reject it.

"In other words, the hypothesis that vaccines cause higher rates of all-cause mortality is to be slightly preferred?"

It's not a matter of preference but rather an objective statement about the probability of observing these results or ones of greater magnitude if there were no effect. Choosing how confident to be or what to prefer is subjective. It is rational to align them mathematically, such that P=0.41 gives you 59% confidence the vaccines are increasing the risk, but that is a subjective choice and doesn't follow inexorably from the statistics.

"If the p-value were 0.05, that would be the odds that the null hypothesis is correct--5%."

It means the odds you would observe a difference this great or greater if the null hypothesis were true is 5%, and if you subjectively choose that at this probability or lower you will reject the null hypothesis, then due to your subjective choice to do so you can reject the null hypothesis. Conventionally, this is arbitrarily set to be less than but not equal to 0.05.

"If anything, the p-value suggests that the study was underpowered to consider all-cause mortality. As pharma employs statisticians and is not new to the vaccine rodeo, pharma must have known what numbers of participants were needed to power the study sufficiently for all-cause mortality statistics to show a clear signal for either the null hypothesis or for the vaccine increases mortality hypothesis. And the FDA wasn't interested in pursuing this question, which ought to be concerning for everybody."

I believe they would say it was impractical to power the study for mortality, but I agree with you.

"The phrase, "is not statistically significant," should be banned since it is misleading."

Statistical significance in general is misleading. I don't think it should be banned to talk about it but we need more education about its history and why it isn't the best paradigm to use.

It therefore follows that the Pfizer data is weak evidence of cardiac-related mortality, likely ranging from 10 to 80% increased relative risk.

There is evidence of 55% increased relative risk for the vaccinated over the unvaccinated from a Jan. 2022 Nature study by Xu, et. al., as elucidated by Clare Craig at

You show that the extra deaths in the drug group were not significant. But isn't it the case that such a study is supposed to show that the drug is SAFER than the control? Not less safe at a not-significant level? The boot was surely on the wrong foot! THEY be proving safety; why do we have the burden of proving they were not safe?

Nevertheless, instead of 'Safe', the politicians should have, more accurately, proclaimed that the injections were:

'Not significantly unsafe after just a few months, and given that the trial evidence of longer-term harms was eliminated when the placebo group was injected, who knows how unsafe after a longer period. But never mind, we will find out in the real population, after it is too late'.

Perhaps the marketing advisors didn't think this had quite the right ring.

Thank you for this analysis - the most thorough and balanced review I've seen!

Have you analyzed the serious and adverse reactions between the placebo and vaccinated groups? I'd be curious to know if the results were statistically significant.

Yes with notes but haven't look at it in a while. I'll be attacking safety more systemically in the near future.

Taking my time going through these well researched and presented data Chris. Thank you! I will share the link to your substack. I had the J&J back in April of 2021. Thought it was the lesser of the 3 evils. No issues afterwards and am trying to avoid a booster to go to Italy this summer. I'm 54 fit, metabolically heathly and topped off on my supplements. No Covid infection that I know of and I work in the hospital (pathology)

The trials were a complete sham and useless. The control groups were destroyed on purpose and the limits of length were also designed to eliminate major faults. The FDA and CDC were going to approve this mRNA substance (IT WAS NEVER A VACCINE!) because of the faked emergency and pressure from the DoD and HHS as well as WHO.

It is now more than obvious that covid was not a threat to 99.5% of the population. And only a severe threat to those with other medical difficulties. If you feel that mRNA substances are safe, go ahead and keep getting boosters and good luck.

Interesting read, but I'm afraid the 21-17 of the FDA doc checks out in the raw data.

https://openvaet.substack.com/p/pfizerbiontech-c4591001-trial-deaths

At your disposal if something is unclear !

"Using this calculator, the difference in mortality rates is P=0.41 and is not statistically significant:"

Doesn't P=0.41 mean the odds that the null hypothesis is correct? In other words, the hypothesis that vaccines cause higher rates of all-cause mortality is to be slightly preferred?

If the p-value were 0.05, that would be the odds that the null hypothesis is correct--5%.

If anything, the p-value suggests that the study was underpowered to consider all-cause mortality. As pharma employs statisticians and is not new to the vaccine rodeo, pharma must have known what numbers of participants were needed to power the study sufficiently for all-cause mortality statistics to show a clear signal for either the null hypothesis or for the vaccine increases mortality hypothesis. And the FDA wasn't interested in pursuing this question, which ought to be concerning for everybody.

The phrase, "is not statistically significant," should be banned since it is misleading.

"Doesn't P=0.41 mean the odds that the null hypothesis is correct?"

We don't speak of showing the null hypothesis to be correct, but rather failing to reject it.

"In other words, the hypothesis that vaccines cause higher rates of all-cause mortality is to be slightly preferred?"

It's not a matter of preference but rather an objective statement about the probability of observing these results or ones of greater magnitude if there were no effect. Choosing how confident to be or what to prefer is subjective. It is rational to align them mathematically, such that P=0.41 gives you 59% confidence the vaccines are increasing the risk, but that is a subjective choice and doesn't follow inexorably from the statistics.

"If the p-value were 0.05, that would be the odds that the null hypothesis is correct--5%."

It means the odds you would observe a difference this great or greater if the null hypothesis were true is 5%, and if you subjectively choose that at this probability or lower you will reject the null hypothesis, then due to your subjective choice to do so you can reject the null hypothesis. Conventionally, this is arbitrarily set to be less than but not equal to 0.05.

"If anything, the p-value suggests that the study was underpowered to consider all-cause mortality. As pharma employs statisticians and is not new to the vaccine rodeo, pharma must have known what numbers of participants were needed to power the study sufficiently for all-cause mortality statistics to show a clear signal for either the null hypothesis or for the vaccine increases mortality hypothesis. And the FDA wasn't interested in pursuing this question, which ought to be concerning for everybody."

I believe they would say it was impractical to power the study for mortality, but I agree with you.

"The phrase, "is not statistically significant," should be banned since it is misleading."

Statistical significance in general is misleading. I don't think it should be banned to talk about it but we need more education about its history and why it isn't the best paradigm to use.

It therefore follows that the Pfizer data is weak evidence of cardiac-related mortality, likely ranging from 10 to 80% increased relative risk.

There is evidence of 55% increased relative risk for the vaccinated over the unvaccinated from a Jan. 2022 Nature study by Xu, et. al., as elucidated by Clare Craig at

https://dailysceptic.org/2022/02/09/heart-problems-after-covid-are-much-worse-for-the-vaccinated-nature-study-shows-but-its-hidden-in-the-appendix/

With this evidence, despite the lack of clarity, it is past time to shut down covid vaccines.

Great article. Steve Kirsh linked it in an article today. Norman Fenton has also done some great analyses.

https://pubmed.ncbi.nlm.nih.gov/20332404/

Chris,

You show that the extra deaths in the drug group were not significant. But isn't it the case that such a study is supposed to show that the drug is SAFER than the control? Not less safe at a not-significant level? The boot was surely on the wrong foot! THEY be proving safety; why do we have the burden of proving they were not safe?

No they aim to show it is effective at its specific aim without causing harm.

Thank you. I think I understand.

Nevertheless, instead of 'Safe', the politicians should have, more accurately, proclaimed that the injections were:

'Not significantly unsafe after just a few months, and given that the trial evidence of longer-term harms was eliminated when the placebo group was injected, who knows how unsafe after a longer period. But never mind, we will find out in the real population, after it is too late'.

Perhaps the marketing advisors didn't think this had quite the right ring.

I looked at this a little bit differently.

The lady tasting tea, vaccines and the damage dogmatic doctors do

https://vinuarumugham.substack.com/p/the-lady-tasting-tea-vaccines-and?s=w