In this article, I put together a list of evidence showing a causal effect between the COVID-19 injectable products and adverse events reported to VAERS.

You are so smart and this is way above my comprehension level, but I enjoy making my brain do gymnastics as I try to understand it. I get the gist. I do wish I was smart enough to truly grasp this!

I would add that when comparing two time series that are by definition monotonic, meaning that they always go up, the correlation between strictly unrelated series is hard to tease appart. The correct way is to make the series stationary, which can be done by using log and the difference of X_t and X_{t-1}, or even differencing multiple times (or fractional # of times!!). This way you can compare the *changes* in the time series in order to understand if there is any statistical relationship between the two time series. I would either remove this data or correct it with the appropriate transformations, since I think it weakens the overall strength of this article. I appreciate your work and the message you're communicating!

Jan 22, 2022·edited Jan 22, 2022Liked by Jessica Rose

Jessica, AEs are a function of injection, so R2 arbitrarily close to 1 must result in the last example. More injections must give more AEs, just as cases are a function of testing. What about using Granger causality to see what predictive value the vax rate has on the prevalence of each AE as a condition/diagnosis in the general population? (Sorry, econ not bio stats) I don't think R2 has much explanatory power here. Thank you so much for your hard work.

*I guess what's missing is the magnitude of the increase. Yes, your point is AE is a function of the shots, but vaxxers will counter than anything has an accepted rate of side effects, and these shots carry a very tiny risk of these particular side effects. What's a comparison of generally accepted side effect rate of common meds or shots compared to this rate with these shots? That would make a point, I think. Magnitude of effect.

Third dose drop in myocarditis reports could be behavioral. E.g., doctor observes it, then says, “oh yeah, we know about that.” Then they don’t report it, thinking it a low priority. Or similarly.

Can’t stop thinking about the third dose “drop”. I wonder if it could be lower due to a kind of saturation in that most of the susceptible are removed from the pool? But then I’m also thinking about the delay in the youth getting the booster. And now, as students return to college campuses following winter break, with universities requiring boosters, I wonder if we’ll see another bump in the next month-ish? Scared to see what stories the data tell in the next few weeks.

Sometimes I am bummed that all this great effort to prove how messed the 'official' figures are would be so better spent, ideally, on something more beautiful. But good work is good work and I commend it. Perhaps new friends offset the stupidity of all this damage.

There is one more, since jabs were given for given ages at different months, deaths should also peak at different months following the jab planning ...

I freaking love you, Jessica. We are so fortunate to have a data/truth/freedom warrior like you on the side of the Resistance.

You can get even better Dose response effect by comparing moderna vs Pfizer. Modern give 100mg per dose. Pfizer gives 30mg per dose.

SUPERSTAR!

Concise and Clear. Thank you, Jessica.

You are so smart and this is way above my comprehension level, but I enjoy making my brain do gymnastics as I try to understand it. I get the gist. I do wish I was smart enough to truly grasp this!

Lovely work, Jessica, please keep chipping away.

God bless the work you are doing. These are evil people you are exposing and i hope you are not in danger.

I would add that when comparing two time series that are by definition monotonic, meaning that they always go up, the correlation between strictly unrelated series is hard to tease appart. The correct way is to make the series stationary, which can be done by using log and the difference of X_t and X_{t-1}, or even differencing multiple times (or fractional # of times!!). This way you can compare the *changes* in the time series in order to understand if there is any statistical relationship between the two time series. I would either remove this data or correct it with the appropriate transformations, since I think it weakens the overall strength of this article. I appreciate your work and the message you're communicating!

Jessica, you are wonderful. What is a loo-loo dose? I assume the one that harms, but I find the term confusing.

Great work, Jessica. Hope you and all your followers will be with us Sunday in Washington, DC! #End the Mandates (which should be #end the killing)

Excellent work!

edited Jan 22, 2022Jessica, AEs are a function of injection, so R2 arbitrarily close to 1 must result in the last example. More injections must give more AEs, just as cases are a function of testing. What about using Granger causality to see what predictive value the vax rate has on the prevalence of each AE as a condition/diagnosis in the general population? (Sorry, econ not bio stats) I don't think R2 has much explanatory power here. Thank you so much for your hard work.

*I guess what's missing is the magnitude of the increase. Yes, your point is AE is a function of the shots, but vaxxers will counter than anything has an accepted rate of side effects, and these shots carry a very tiny risk of these particular side effects. What's a comparison of generally accepted side effect rate of common meds or shots compared to this rate with these shots? That would make a point, I think. Magnitude of effect.

Third dose drop in myocarditis reports could be behavioral. E.g., doctor observes it, then says, “oh yeah, we know about that.” Then they don’t report it, thinking it a low priority. Or similarly.

Can’t stop thinking about the third dose “drop”. I wonder if it could be lower due to a kind of saturation in that most of the susceptible are removed from the pool? But then I’m also thinking about the delay in the youth getting the booster. And now, as students return to college campuses following winter break, with universities requiring boosters, I wonder if we’ll see another bump in the next month-ish? Scared to see what stories the data tell in the next few weeks.

Sometimes I am bummed that all this great effort to prove how messed the 'official' figures are would be so better spent, ideally, on something more beautiful. But good work is good work and I commend it. Perhaps new friends offset the stupidity of all this damage.

There is one more, since jabs were given for given ages at different months, deaths should also peak at different months following the jab planning ...