Professor Norman Fenton on Covid Vax Statistical Illusions By Brian Simpson

Not wanting to scare the science timid, even though science-fuelled technocracy is moving to complete enslavement, if not to destroy the very essence of humanity in its transhumanism quest, but Professor Norman Fenton, one of the few mathematicians to tackle the fraudulent use of data in the Covid plandemic, tackles the issue of the vax supporters claiming that there is a lower mortality rate for the vaccinated. That is not necessarily so. So-called “survivor bias,” the focus upon a group which has passed some sort of selection test, while another group has not, could indicate that this claim is based upon a statistical illusion. Professor Fenton observes: “The survivor bias is further exaggerated if (as was the case in most Western nations for the Covid vaccines) the initial vaccine roll-out happened during the winter - meaning that fatality rates would inevitably fall anyway as more people were vaccinated. So, irrespective of the vaccine, more deaths were occurring at a time when more people were unvaccinated. Most of those classified as vaccinated would therefore already have survived the initial death peak when first vaccinated.”

There would thus be an over-estimation of the mortality of the unvaxxed population.

https://wherearethenumbers.substack.com/p/never-vaccinated-vs-ever-vaccinated

“In a previous article, we described the concept of survivor bias in studies that claimed better outcomes for Covid vaccinated women in pregnancy: since the greatest risk to babies occur early in pregnancy, the babies of women who are vaccinated during pregnancy must already have survived the riskiest period.

In fact, a similar survivor bias more generally affects mortality rates for the vaccinated. If you see a study claiming much higher mortality rates of the 'never vaccinated' versus the 'ever vaccinated' you need to be sure it's not just a statistical illusion due to survivor bias.

… this particular bias is avoided by using 'person years in each vaccination category' rather than people in each category. So a person who first gets vaccinated 6 months into a one year study and lives until the end of the year will be counted as 6 months never vaccinated and 6 months ever vaccinated.

The example is, of course, extremely simplified. Ideally, to calculate the correct number of person years in each category we need to know, for each person in the study, the exact date of each vaccination. And we also need to take account of the varying infection rate at different time intervals. That’s because the survivor bias is further exaggerated if (as was the case in most Western nations for the Covid vaccines) the initial vaccine roll-out happened during the winter - meaning that fatality rates would inevitably fall anyway as more people were vaccinated. So, irrespective of the vaccine, more deaths were occurring at a time when more people were unvaccinated. Most of those classified as vaccinated would therefore already have survived the initial death peak when first vaccinated.

The ONS attempt to avoid survivor bias, but most reporting organisations and published studies do not

The ONS data on deaths by Covid vaccine status uses person years to avoid this kind of survivor bias (although there are other biases not avoided in the ONS data as explained here). However, most studies and reports comparing mortality rates of vaccinated and unvaccinated (whether it is for Covid deaths or all-cause deaths) fail to make the adjustment and are therefore overestimating the mortality rate of the unvaccinated while underestimating the mortality rate of the vaccinated.

Consider, for example, the most widely used web site for Covid data, “Our World in Data”. Its page describing the comparison in Covid mortality rate for vaccinated and unvaccinated states:

Death rates are calculated as the number of deaths in each group, divided by the total number of people in this group. This is given per 100,000 people.

So, all of the graphs shown there, such as this one for the USA, are subject to survival bias (one of the tell-tale signs of survivor bias is that the overestimation of the unvaccinated mortality rate will be highest during the time when large numbers of people are still being vaccinated and lowest during periods when there are few new vaccinations):

The regular CDC reports such as this most recent one not only fail to adjust for survivor bias but fail to mention this among the many listed limitations of their analysis. Since, as our simple video example shows, survivor bias makes it inevitable that a placebo vaccine can be shown to reduce mortality and will do so the more jabs you have. Therefore, it is unsurprising that these reports all have to assert the following to keep up the illusion:

All persons should stay up to date with COVID-19 vaccination

Survival bias is just one of the many biases and flaws that have led to massively exaggerated claims of vaccine efficacy and safety

As we have explained several times before there are many biases and flaws in the way Covid data is collected and analysed which (curiously) all favour exaggerated claims of vaccine efficacy and safety.”

https://wherearethenumbers.substack.com/p/how-to-create-the-illusion-your-vaccine