I’ve finished an analysis of the New Zealand vax data. But since tempers are hot on this, and the subject is important, I want to be sure I haven’t missed something glaringly obvious. Which would be just like me. I was going to run the analysis today, but I decided to wait a day or two to think.
That being so, I have no other post.
Here’s a link to (one of) Steve Kirsch’s words on the data. It was Steve who asked me (a few weeks back) to look at the data.
Let me ask this: what do you, dear readers, see in any of the analyses out there? Strengths and weaknesses. Of the analyses alone.
We don’t here care about the politics of the thing. Yes, NZ arrested the whistleblower, and, I read, were originally denying him bail. I gather they might have weakened that. But whatever. That NZ is a tyrannical Expertocracy we already knew. Remember when their Regime claimed to be the only source of Truth? This arrest has no direct bearing on the data itself, except to suggest it is genuine.
In any case, like all statisticians, we take the data as it is given to us. And all analyses, like all probability, is conditional on the assumptions made. Data are always part of these assumptions. Data are the model.
Here’s Normal Fenton on the data: “The New Zealand vaccine data: what I actually saw and analysed and what the limitations are”.
My data, unlike Fenton’s, is not summary, but is record level: the whole data set (anonymized). Each date of each shot, and each date of each death (if any), for each person (identified by only by record numbers). There is also age and some other information on batch number and specific vaccines. But there is no no-shot data. That is, this is data only on people who have had a least one dose. People who no shots are not represented. The data spans about a two and a half year span, and all during the time frame of the panic.
There are no causes of death given: just death date for those who died.
There are many threads arguing about the data and the analysis, which are easy to find. Here’s one.
When I woke up this morning, too early, it was thinking of a particular feature of the data I do not think I explained adequately. Maybe. Or maybe I did.
So I decided to sit on this for a bit to try and see if I did anything idiotic. No small chance of that, my friends. As regular readers know, I do not care who I make happy or who I make angry with any opinion. Except myself. I hate to be wrong. Especially on something for which I have a blind spot but which is obvious to everybody else.
Meanwhile, I am eager to see if any of you have already considered any of this.
Regular posting recommences tomorrow.
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