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James Lyons-Weiler whines about his “vaxxed/unvaxxed” study retraction

James Lyons-Weiler published a “vaxxed/unvaxxed” study with antivax pediatrician Paul Thomas. The paper was recently retracted, and his whining about it is epic.

It is always amusing to me to see the reaction of antivaccine quacks and pseudoscientists when their attempts at achieving some measure of scientific credibility for their ideas in the form of getting their papers published in bottom-feeding (albeit ostensibly “peer-reviewed”) journals ends up biting them in the hindquarters. For example, it happened with Anthony Mawson and his risibly incompetent “vaxxed/unvaxxed” study, which, after a history of disappearing and reappearing, was retracted, much to the sadness of antivaxxers, only to reappear again (I’m guessing after Mawson’s check finally cleared). I was thinking this as I was informed that former actual scientist turned antivaxxer James Lyons-Weiler, who co-authored an equally bad “vaxxed/unvaxxed” study with antivax pediatrician Dr. Paul Thomas (whose license was suspended in December), is very unhappy that it, too, has been retracted—and retracted by MDPI, which is not exactly known for publishing what one would call the best journals.

Indeed, Lyons-Weiler is so upset that he published an epic rant about the retraction entitled MDPI’s “The International Journal of Environmental Research and Public Health” does not publish unbiased research or advances in methodology. Reading the rant, the first thing that disappointed me was that my deconstruction of his awful study back in November apparently had nothing to do with MDPI’s decision to retract the paper. More deliciously, this is apparently what happened (that is, if you believe Lyons-Weiler):

After 250,000 reads, the journal retracted our study, Relative Incidence of Office Visits and Cumulative Rates of Billed Diagnoses Along the Axis of Vaccination (2020 Nov 22;17(22):8674. doi: 10.3390/ijerph17228674) after one reader submitted a poorly written email (with typos and grammatical errors) about an imagined confounder they thought might explain the results.

We asked the Editor-in-Chief and the Editorial Board of the journal to publish the readers’ comments, and our reply. They did not respond to that request. Instead, they decided to retract it without further discussion of our reply.

We had published an Erratum, and wanted to publish a small Corrigendum for an error we had reported to the Editor-in-Chief. These issues were unrelated to the anonymous readers’ concerns.

Lyons-Weiler’s woo-ful whine led me to think a couple of things. First, how is it that, before readers sending me links to his article, hadn’t I known that his and Thomas’ paper had been retracted? Mea culpa. More amusingly, I note how Lyons-Weiler is bragging about how many downloads/reads his incompetent paper had received, as though popularity equals validity in science. We all know that it does not. Indeed, the worst conspiracy mongering and pseudoscience often garner the most engagement on social media, which is the whole reason in the first place that social media companies are coming under criticism for their algorithms that prioritize engagement when deciding what content to show in their users’ feeds.

After his false appeal to popularity, unsurprisingly Lyons-Weiler turns to attacking the person who had written to the MDPI journal’s editor with their concerns, portraying whoever it was as having nefarious motives:

Our concerns are not vainglorius. It is unfortunate that they allowed themselves to be duped by a ghoul. A ghoul is one who haunts journals working to retract only studies that include results they don’t want published). This imparts a ghouling bias, also known as retraction bias, into the literature, preventing unbiased meta-analyses. In our cases, it also prevents advances in the methodology of the analysis of data from vaccine safety studies from being adopted and tried out by other scientists.

We would have preferred rational discourse so the scientific community could make their own assessment of the issues at hand. Instead, we have to assess the journal’s integrity, or at least their ability to discern that they have been defrauded by the ghoul.

I must admit that, before Lyons-Weiler used the term, I hadn’t heard of “ghoul” applied to writers complaining about crappy studies, explaining why they’re crappy, and suggesting retraction, much less “ghouling bias.” Google searches for the term and variants didn’t really help either (although a fair amount of anime content showed up in some of my searches, much to my puzzlement—I’m old). So I figured that maybe the ever-reliable Retraction Watch might be able to help, but, alas, a search of the blog for “ghoul” did not turn up anything, much less “ghouling bias.” I also searched for “retraction bias,” but that particular Google search turned up nothing helpful either, nor did searching Retraction Watch for the term. Basically, Lyons-Weiler sounds more than a little conspiratorial in that he seems to be saying that there are a bunch of “ghouls” out there just waiting to try to get papers like his retracted because they “don’t like” their findings. Of course, what Lyons-Weiler neglects to consider is that it is incredibly difficult to get a paper retracted. Just ask Retraction Watch.

Before I get to Lyons-Weiler’s complaints, let’s just recap a bit about his and Thomas’ study and what made it so bad. As I noted at the time, this was supposedly a retrospective comparison of all patients who were born into Dr. Thomas’ practice between June 1, 2008 and January 27, 2019, with a first visit before 60 days of life and a last visit after 60 days. The inclusion/exclusion criteria whittled down over 21,000 records to 3,324 patients, of whom 2,763 were “variably vaccinated,” defined as “having received 1 to 40 vaccines.” But what is the primary outcome studied? For this, Thomas and Lyons-Weiler make up a brand new metric that I’d never heard of before, the Relative Incidence of Office Visit (RIOV).

Never having heard of RIOV as a validated, I did some PubMed searches and couldn’t find a single paper that used it. Certainly, the authors did not cite any papers that had used this particular made-up metric before to justify its use, to demonstrate its advantages and disadvantages, and in general to provide the sort of information that any clinical investigator would want about an unfamiliar metric. Again, as I said before, I’m always suspicious when I see a metric like RIOV. It strongly suggests to me, particularly in the case of a retrospective study, that the authors tried to do an analysis looking at more defined, traditional primary outcomes and failed to find any statistically significant results. In other words, to me this paper reeked of of p-hacking, the practice of doing comparison after comparison until a “statistically significant” result is tortured out of the data.

One other thing I wrote:

Similarly (and perhaps most importantly) the children in Dr. Thomas’ practice are likely to be quite different than children in a typical pediatrics practice, as I discussed before. For instance, there’s likely to be ascertainment bias, which is the systematic distortion in measuring the true frequency of a phenomenon due to the way in which the data are collected. How could this happen? Think about it. Dr. Thomas believes that vaccines cause autism. That right there introduces unconscious bias that could affect how likely he and his staff are to investigate subtle signs of autism and refer out to for evaluation based on vaccination status and how likely he is to ascribe various diagnoses to “unvaxxed” children compared to “vaxxed” children. One can easily imagine this bias leading to unvaccinated children to be less likely to be given an autism diagnosis than vaccinated children or to be—dare I say?—brought in to the office as often for various conditions that Dr. Thomas attributes to vaccines.

I also noted:

At this point, I’d also like to make a general sort of comment about epidemiological studies (and, make no mistake, that’s what this study is, as it is, in essence, a retrospective cohort study). If you’re going to do a study like this, you need a competent statistician involved before you collect the data. The only two authors listed are Thomas and Lyons-Weiler, and the statistical methods are not well-described. It really also would have behooved them to have an epidemiologist or at least a clinical investigator with experience doing retrospective analyses to help them. Clearly, they did not. Margulis claims that they did, but this “independent statistician” (as she puts it) is not identified anywhere that I can see.

A non-representative study population diagnosed with nonstandard techniques plus no good statistician or epidemiologist who would put his or her name on the paper? What could possibly have gone wrong?

Which brings us back to Lyons-Weiler’s complaint, which quotes one of the “ghoul’s” criticisms:

As he has had a possibility to influence all the essential elements – recommendations for vaccination, information on who is vaccinated, diagnoses made and number of office visits – it is not obvious that the data can be treated as neutral. For example, the diagnosis of autism and ADHD are complex as well as culturally dependent. Unintentional positive bias can emerge for a GP that is known to associate vaccination with autism or ADHD.

Precisely! This is a more concise way of saying what I said about the study! The potential for bias in using a single antivax doctor’s practice, a doctor who claims that there’s virtually no autism in his unvaccinated patients, is huge. I will point out that Lyons-Weiler’s answer most definitely does not address the criticism:

When Dr. Thomas approached Dr. Lyons-Weiler with the request to help design the study, Dr. Lyons-Weiler informed Dr. Thomas that his participation in this design and execution of the study was conditional: that any result found would be published, whether the data indicated that exposure to vaccines were associated with increased, or decreased health. The data were drawn from the electronic medical records according to the reported inclusion/exclusion criteria (as reported in the study); no patients were included or excluded using any criteria beyond that were reported.

One notes that Dr. Lyons-Weiler is neither a biostatistician nor an epidemiologist, and to do a retrospective study like this requires, ideally, both, but at the very least a competent biostatistician. Then, while denying such bias (albeit with a disclaimer that he and Thomas had, in fact, noted that Thomas’s practice might not be representative), Lyons-Weiler goes off with a non sequitur in which he invokes “informed consent” (or, as I like to refer to “informed consent” when invoked by antivaxxers about vaccines, “misinformed refusal”):

The universal adherence by all of the physicians in the practice to Oregon State Law to provide informed consent is, sadly, relatively unique. In spite of laws that protect informed consent, and Federal Regulations that forbid coercion for inclusion in clinical research, the American Academy of Pediatrics supports dismissal of patients from practices (AAP, Edwards, 2016). In so doing, the AAP sanctions coercion, including dismissal of entire families from pediatric practices in violation of state and Federal laws protecting patient rights to informed consent.

After citing the AAP’s position on informed consent and complaining that some pediatrics practices are dismissing patients whose parents refuse to vaccinate them, Lyons-Weiler continues:

From this, it can be seen that the decision to not vaccinate is not undertaken by families without due consideration of stated risks and benefits. It also demonstrates that the parents’ decisions to accept or deny a specific vaccine are not, in the end, in the final control of the physicians of any practice in Oregon providing lawful pediatric medical care. To do otherwise would be unlawful.
The standard of care for the diagnoses of autism and ADHD involves referrals to physician specialists outside the practice, and the final diagnosis was not made by the physicians in Integrative Practice over the 10-year period from which the data were drawn.

As I like to say, “informed consent” according to antivaxxers is in reality “misinformed refusal.” After all, if parents believe the antivaccine misinformation that portrays vaccines as not just ineffective but downright dangerous and causing autism, autoimmune disease, and all manner of other health issues up to and including death, then their refusal of vaccines for their children is not “informed.” It is misinformed, hence my term “misinformed refusal.” True informed consent, which is what doctors who are not antivaccine provide, involves a rigorously science-based discussion of the risks and benefits of any intervention, including vaccines. That is the farthest from what antivaxxers provide.

As for the part about specialists diagnosing autism and ADHD, here Lyons-Weiler is showing how little he knows about the practice of medicine. It is the primary care practitioner who is the gatekeeper and who, in most cases, controls referral to the relevant specialists. If that gatekeeper (like Dr. Thomas) is biased, then his referral pattern will be similarly biased. It’s not just the primary care doctor, though. Parents have to agree. If the antivaccine or highly vaccine-hesitant parents catered to by practices like Dr. Thomas’ don’t believe that their unvaccinated child could have autism, then even if referrals to the appropriate specialists are recommended, they might balk, preferring alternative treatments for whatever diagnosis is given to their children. Then there’s the issue of Dr. Thomas’ referral base, which is likely to consist of parents and physicians who think he’s good, parents recommending him to other parents and physicians referring patients to him. Why would they think Thomas is a good doctor? Most likely it would be because they share Thomas’ antivaccine proclivities and like his use of alternative medicine. Basically, Lyons-Weiler doesn’t address the valid criticisms at all.

The “ghoul” also echoed another one of my criticisms:

The authors have invented a non-standard measure (Relative Incidence of Office Visit (RIOV)) for the health problems. The measure has several weaknesses compared to the diagnoses (sic) data. For example, it is more easily manipulated, the visit can take place because of false expectations of the parent, the link between the reason of the visit and the health problem is vaguer(sic) and at one visit several health problems can be assessed, which complicates the classification of the reason for the visit.

The first part of Lyons-Weiler’s response cracked me up:

In 1934, Sir Ronald Fisher invented a non-standard approach to analysis called null hypothesis testing (Fisher, 1935) In 1973, Nei invented the non-standard method for studying genetic differentiation in populations (Nei, 1973). In 2020, Lyons-Weiler and Thomas invented the non-standard measure RIOV. Science progresses by the introduction of “non-standard methods”. ANONYMOUS claims that the RIOV test has several “weaknesses”; however, they fail to provide any explicit theoretical derivation of “weakness” in the method, nor any data or evidence of any kind to support that these supposed weaknesses are indeed correctly surmised, nor that they apply to the implementation of the RIOV measure in our study.

Yes, but Fisher also validated that approach and showed why it was superior. Lyons-Weiler and Thomas did not validate their approach or show its superiority. It is not up to critics to show “theoretical weakness” of Lyons-Weiler’s construct. It is up to Lyons-Weiler to show its validity and at least equivalence to existing measures. He did not.

Lyons-Weiler appeared particularly incensed at the criticism that his new metric (RIOV) might produce a biased result. You might recall that I said a similar thing, pointing out how it could amplify differences between the groups and suggesting that the reason Lyons-Weiler and Thomas created it was because they couldn’t find any statistically significant differences between the vaccinated and unvaccinated groups—even in a practice as nonstandard as that of Dr. Thomas—without creating such a metric. Lyons-Weiler also seems oblivious to how such a practice could result in a serious selection bias, all his mental contortions to deny selection bias notwithstanding.

I must admit here to feeling a bit of schadenfreude. James Lyons-Weiler was once a legitimate scientist but, for some reason, embraced antivaccine pseudoscience. I don’t know why. Likely only he knows. Whatever his reasons, he has joined antivaccine physicians like Paul Thomas to spread antivaccine disinformation. Worse, in the age of COVID-19, like so many antivaxxers he’s effortlessly pivoted to spreading antivaccine misinformation as well. Indeed, he started doing this in January 2020, nearly two months before the pandemic really hit the US in a big way. MDPI might be a dodgy scientific publisher. Indeed, MDPI has been accused of being a predatory publisher, and, whether it’s predatory or not, definitely publishes low quality journals. That MDPI actually retracted his paper has got to hurt.

Good.

By Orac

Orac is the nom de blog of a humble surgeon/scientist who has an ego just big enough to delude himself that someone, somewhere might actually give a rodent's posterior about his copious verbal meanderings, but just barely small enough to admit to himself that few probably will. That surgeon is otherwise known as David Gorski.

That this particular surgeon has chosen his nom de blog based on a rather cranky and arrogant computer shaped like a clear box of blinking lights that he originally encountered when he became a fan of a 35 year old British SF television show whose special effects were renowned for their BBC/Doctor Who-style low budget look, but whose stories nonetheless resulted in some of the best, most innovative science fiction ever televised, should tell you nearly all that you need to know about Orac. (That, and the length of the preceding sentence.)

DISCLAIMER:: The various written meanderings here are the opinions of Orac and Orac alone, written on his own time. They should never be construed as representing the opinions of any other person or entity, especially Orac's cancer center, department of surgery, medical school, or university. Also note that Orac is nonpartisan; he is more than willing to criticize the statements of anyone, regardless of of political leanings, if that anyone advocates pseudoscience or quackery. Finally, medical commentary is not to be construed in any way as medical advice.

To contact Orac: [email protected]

107 replies on “James Lyons-Weiler whines about his “vaxxed/unvaxxed” study retraction”

A. Your description of Lyons-Weiler’s comments about the physicians in Thomas’ clinic believing in his version of informed consent sounds to me like Lyons-Weiler, after denying bias, is admitting it.

B. Also, I would suspect that someone like Thomas would be referring to physicians that may also not be representative, for example, believers in biomedical interventions.

C. I suspect his “ghoul” language derives from previous discussions he had about what he calls retraction bias – retracting bad anti-vaccine papers. He had a whole video on that using the “ghoul” term he mentions here: https://www.facebook.com/watch/live/?v=351012246589540&ref=notif&notif_id=1626354714618142&notif_t=live_video Based on this study, which is basically a set of interviews with people who had bad anti-vaccine papers retracted and think the retraction was unfair (if anyone thinks I’m not being fair to the study, I’m open to hearing that, but that’s my current reading): https://www.tandfonline.com/doi/abs/10.1080/09581596.2021.1878109

So, Lyons-Weiler has come up with two, count’em, two new terms. “Ghoul” for anyone pointing out problems in a published article and “(Relative Incidence of Office Visit (RIOV)), and whines that he is not recognized for the obvious brilliance of his shiny new metric. Does this count as a variation of the “Galileo Gambit?”

It sounds to me like you are wrapped up in some, what did you call it,,? oh yea, conspiracy mongering, much like you claim for Lyons-Weiler to be. Its like reading the story of two school aged boys who were competing in a science fair. Utterly ridiculous. You’re so closed minded and arrogant that you wouldn’t believe vaccines cause autism even if it were proven without a doubt. You would just claim that the process in which the results were determined were wrong. Much like a conspiracy monger would do.
People in glass houses…. all I have left to say.

Funny, but you sound like someone who wouldn’t believe that vaccines DON’T cause autism, even if it were proven beyond a doubt (which, actually, for all practical scientific intents and purposes it has).

You’re so closed minded and arrogant that you wouldn’t believe vaccines cause autism even if it were proven without a doubt.

The question of whether vaccines cause autism has been investigated to the point that there is a meta-analysis wth over 14 million subjects in it. The verdict from the meta-analysis and from every well-designed and properly run study? No correlation.
At this point it would take extraordinary evidence to prove vaccies cause autism.

He compares himself to FISHER! Priceless! AND baseless as well!

In other news..
anti-vaxxers are about to explode into ( even more) hissy fits ( than usual) because
— about 500 US universities will require Covid vaccination for students in September
— NEW YORK CITY will require all city workers to be vaccinated by 13 September ( anti-vaxxers can’t attack him too much longer because there will soon be a new mayor, Mr Adams) and he is investigating a vaccine pass similar to that which will be issued in France.

Watching several lawsuits about the university mandates.

Note that the vaccine pass made the news in France (where the law imposing limits based on it was just passed), but there are several European countries using one.

I think it was just yesterday or the day before that I saw someone still trying to pass off the 2018 FIFA World Cup photo as an antivaccine demonstration.

Actually, the vaccine pass has been used in the whole EU since 1 July – if you have one, it’s easier to get on a plane and you usually don’t have to do an additonal Covid test / are exempt from a mandatory quarantine period if the country you are travelling to demands one. That’s the general framework but EU counties are free to introduce other functions for the passes.

So is this a valid stance to take, are they onto something in how we should view all research or is it an over reaction based on nonsense such as these fringe publications peddle?

Time to assume that health research is fraudulent until proven otherwise?

July 5, 2021

Health research is based on trust. Health professionals and journal editors reading the results of a clinical trial assume that the trial happened and that the results were honestly reported. But about 20% of the time, said Ben Mol, professor of obstetrics and gynaecology at Monash Health, they would be wrong. As I’ve been concerned about research fraud for 40 years, I wasn’t that surprised as many would be by this figure, but it led me to think that the time may have come to stop assuming that research actually happened and is honestly reported, and assume that the research is fraudulent until there is some evidence to support it having happened and been honestly reported. The Cochrane Collaboration, which purveys “trusted information,” has now taken a step in that direction.

https://blogs.bmj.com/bmj/2021/07/05/time-to-assume-that-health-research-is-fraudulent-until-proved-otherwise/

If you’re going to go to the trouble of adding the “RN,” it would help if the name before it actually connected the two. Manitol and the rest of the litany don’t do much to support Roberts’s and Smith’s apparent failure to grasp that yes, people pay attention to retractions and more.

It’s nice that they go to the trouble of whining about Thomas’s losing out on a million dollars a year in “administrative fees” for not vaccinating. It also has more than a whiff of the Old Chattel Routine.

After snidely commenting about how the complaint by “Anonymous” contained typos and grammatical errors, you just knew that Lyons-Weiler’s response would validate Gaudere’s Law, which states that any post attacking another for spelling or grammar errors will itself contain at least one spelling or grammar error (“vainglorius” (sic) is actually spelled vainglorious).

I’m puzzled at Lyons-Weiler’s contention that dropping non-compliant parents and their children from pediatric practices is somehow a violation of informed consent. By that tortured logic, MDs couldn’t sever relations with patients who procure addictive drugs from multiple physicians or otherwise engage in dogged self-destructive behaviors, because that would be a “violation of informed consent”.

Since leaving academia long ago, L-W has retreated into an increasingly odd world, marked by denial, embracing of pseudo-research, miraculous (not) cures and fantasy enemies. Given that he’s promoting his own school of advanced (heh) studies (IPAK-EDU), what’s stopping him from launching an online journal (or three) that would guarantee retraction-free publication of his own papers and those of like-minded colleagues?

Add publication charges to $$ from speaking fees and money for being an “expert” witness, and we could be talking about a substantial revenue stream.

“He compares himself to FISHER! Priceless!”

I assume this was an intentional play on words. Fisher-Price Science describes the L-W/Thomas paper nicely.

I’m guessing even JLW realizes how suspect it would be for this article to be published in his “journal”.

There you go, problem solved.

Though he really needs to start an additional journal or two* where he’s not editor-in-chief or on the editorial board, just an Anonymous Supporter.

*suggested titles:

Journal of Revealed Scientific Truth
Acta Vaxa Toxa
Frontiers in Proven Cures They Don’t Want You To Know About
Philosophical Transactions of Pure and Applied Martyrdom

How about:

Journal of Alternative Knowledge and Statistics (JAKAS for short)

I’m guessing even JLW realizes how suspect it would be for this article to be published in his “journal”.

He already has published in his own journal.

I don’t doubt this work will also end up there.

“vainglorius” (sic) is actually spelled vainglorious

A quick glance reveals more. I’m going to bother pedanting the life out of it,, but IIRC, the count of parentheses isn’t an even number.

I was going to give J L-W a few points for using “vainglorious”, as the only other place I can think of it’s use is in Thomas Hardy’s “Convergence of the Twain” (a poem about the sinking of the Titanic).

But he’s still minus a million life points for writing this risible “study” in the first place, and another million for complaining about the retraction.

No article about Joe Biden’s vaccine misinformation?
I’m shocked.

LOL sure…

Well at least now I can give the same exact response to every article on here.

Do you have some articles ‘them/us’ can read to show you how deeply unqualified you are to talk to professionals about vaccines and COVID?

You’re funny!

I’m suspicious (and this could just be me) but maybe there is more that happened in that emaili from “anonymous” than JLW disclosed. The journal’s retraction statement in its entirety is:

The journal retracts the article “Relative Incidence of Office Visits and Cumulative Rates of Billed Diagnoses along the Axis of Vaccination” cited above [1]. Following publication, concerns were brought to the attention of the editorial office regarding the validity of the conclusions of the published research.

Adhering to our complaints procedure, an investigation was conducted that raised several methodological issues and confirmed that the conclusions were not supported by strong scientific data. The article is therefore retracted.

This retraction is approved by the Editor in Chief of the journal.

The authors did not agree to this retraction.

Paul Thomas had disclosed the paper was being retracted June 9 when he spoke at a “medical freedom” rally in Portland. I wrote the IJERPH journal editor after Thomas said this (because the article was not retracted online) who said no, it had not been retracted (exact response: “Thank you for your continued support. We are still investigating the article with the journal’s academic editorial team. If the final decision is to retract the article, our journal will publish the retraction statement written by our Leading Academic Editor.”). Thomas also announced the retraction the next week in June on his “against the wind” anti-vax internet show. Article still not retracted but nothing more from Thomas/JLW except for this “ghouling” facebook meeting discussion last week that was even more tedious than JLW’s usual bombastic bloviating. Then nothing happens for over a month? And in that time that MDPI Wallach paper stupidly claiming 2 COVID-19 vaccine deaths for 1 COVID-19 infection death got pulled really fast by MDPI once rumors started flying.

Something else happened I think that neither party is disclosing. Perhaps they discovered fraud or ethics breeches? If so, there really aren’t any repercussions for Thomas and JLW, neither of whom are academically affiliated or running this research from any US govt grants. Medical board won’t do anything on this against Thomas, I suspect. The Office of Human Research Protections can’t touch them either. If the editors suspected outright fraud or unethical human research, there is no one for them to report it to other than disclose it publicly and MDPI may have simply decided to call it a game at that point, retract the paper and go silent. And perhaps Thomas and JLW have opted for silence as well. Very sad if true, because Thomas will still keep doing this flawed unethical “research” upon his patients.

Something smells. Not as bad as before the retraction, but still it’s not roses.

It wouldn’t surprise me in the least if there were fraud involved, but we’ll probably never know for sure if it was incompetence or fraud.

Lyons-Weiler is just pissed because AoA named RFK Jr. as the new Andrew Wakefield instead of him. 🙁

@ Dangerous Bacon–I had Paul Thomas tagged as Wakefraud v2.0, but consistency in thought is not a thing for anti-vaxxers. I missed Dachel’s 7/23 piece in AoA, but it actually gives a nice summary as to why RFKjr is wrong via her summary of all the “hit pieces” on RFKjr.

Wakefraud would never crown a successor given his ego, so probably AJW is the one most annoyed by Dachel’s proclamation.

Also, Wakefield is only in his early 60s, right? He can keep grifting for at least another decade, if not two.

As an editor, you provide the authors of the paper a chance to respond to the concerns about the paper before retracting it. Lyons-Weiler would have been notified about the issues. If he failed to respond or took a long time to respond, then the retraction would have taken some time. I am not going to read too much into Paul Thomas’ comments.

The whole paper is a crock, so I expect fraud is involved among everything else.

Don’t forget to register for the AutismOne conference this upcoming Labor Day weekend. L-W is offering a coupon for 20% off (whether it’s just for his talk on vaccine mandates or for conference registration as a whole is unclear). There’s gonna be a lot of groovy stuff you won’t want to miss, including sessions featuring two different chiropractors and an osteopath, which should offer great promise in adjusting your autistic child for proper brain function. Scoff at your peril.

“We are in the last battle. This is the apocalypse. We are fighting for the salvation of humanity…we have to die with our boots on if necessary.”

RFK Jr. (who will give the keynote address 9/2).

And yes, Kent H. will be there to discuss cancel culture.

http://images-wixmp-ed30a86b8c4ca887773594c2.wixmp.com

I had never even heard of Garrison until a few weeks ago, when the message board for my Cubs friends started ridiculing him. He’s sued the ADL for, among other things, intentional infliction of emotional distress.

Where did you dig this up from?

My guess is this is from a few years ago and yes Australia has decided that they will not allow anti-vaccine liars to tour here giving talks.

We have enough of our own to deal with without importing others.

Those drawings are so bad they had to label them so people could tell who is who.

I think James doesn’t actually understand the criticisms simply because, as you state, he is neither an epidemiologist nor a biostatistician. This is all over his head. And, yes, I bet that does hurt to be informed one is ignorant.

Why can’t antivaxxers just believe a vaccine causes autism and that be fine? Why does one have to be attacked for his/her beliefs? Why are they automatically considered a nut? Isn’t that what everyone has been fighting for for years now?…. is just the ability to form ones own thoughts and opinions based on the evidence? I just don’t understand why there has to be a title for people who don’t believe the mainstream. My theory isn’t a conspiracy theory, its just a theory. And yours is also a theory. And thats it. The end. Who cares if they aren’t the same. One doesn’t make the other crazy for thinking something different. And acknowledging that a different theory may be true doesn’t mean your a crazy conspiracy theorist. It just means that I think the whole truth is not being told and there’s probably more to whatever subject is being discussed. For instance, if im a flat-earther, it doesn’t necessarily mean that I think the earth is a pancake, it just means that I don’t think it is exactly how they’ve taught us it is. Its probably neither a pancake or a marble. For all we know its a pear, as Neil degrasse has stated. ???????????

Criticizing your beliefs that vaccines cause autism as pseudoscientific nonsense and conspiracy theories is not “attacking” you. It’s refuting your misinformation. If you choose to view a science-based deconstruction of your “belief” (which has no scientific basis or grounding in fact) as an “attack,” that’s on you. No one’s saying you’re “crazy” for “believing something different,” just that you are not just wrong, but spectacularly wrong.

Why can’t antivaxxers just believe a vaccine causes autism and that be fine?

Because that belief is not fine.
Because diseases like measles came roaring back and have killed people, thanks to the belief that the MMR causes autism (it doesn’t).
Because that belief was based on a “case study” that turned out to be not only flawed, but fraudulent.
Because people who refuse vaccination pose a danger of infection to those too young to be vaccinated and the immunosuppressed.
I’m a fan of several provaxx pages on Facebook. Some of them have posted articles of people who didn’t get vaccinated against COVID, wound up in hospital or even the ICU, and bitterly regretted their decision to not get vaccinated. Some even paid with their lives.
Why didn’t they get vaccinated? They believed antivaxx lies that downplayed the risks of COVID and vastly exaggerated the vaccines’ risk.
Antivaxx beliefs are harmful, even deadly. That is why you don’t get a free pass from us.

The CDC is lying to the public!!!!
as of the 27th of July numbers on their website. I am uses the 22 May 2021 as an example. The deaths from all causes, but attribute the excess deaths to Covid.

on 22 may 2021
Average number of deaths 53,748
Upper bounds of deaths 55,354
Predicted number of deaths 57,200

on 21 May 2020
Average number of deaths 53,385
Upper Bounds of deaths 55,071
Predicted number of deaths 61,630

but on the 25 May 2019
Average number of deaths 54,360
Upper Bounds of deaths 55,921
Predicted number of deaths 53,846.

2019 was BEFORE the pandemic and the CDC labeled 55,921 deaths as the upper bounds (over which would be excessive deaths)
in 2020 and 2021 they lowered the Upper Bounds of deaths to 55,071 and 55,354.

In addition they CDC changes the Upper Bounds of deaths (excess deaths) to be lower than the actual deaths about every 10 days, thus insuring that the excessive death can be shown and attributed to Covid. You can do your own research, archive the CDC numbers then check in a week to 10 days and the upper bounds will be changed to always show excessive deaths, and be below historical numbers. The CDC now claims fewer people should/will die in their 2021 numbers then should/will died in 2019.

https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm

No, your source is lying to you. Scroll down the page you linked, you would see graph representing excess mortality by month. You would notice that it has peaks /COVID waves). Your source just picked months outside the waves

Aarno my source was the CDC website and the graph you mentioned in your post.

The graph is NOT a monthly graph but a weekly graph, I posted the numbers as the CDC reported.
To obtain the information, using your mouse hover over the graph in the blue area, for a specific week (a popup will appear with the information I used).
These three numbers should not change !!!
The average number of deaths should not change (they will change from one week to the next over time (winter vs summer, but not in the week predicted) but they should not change after the data comes in.
The upper bounds of excess deaths should not change either (again they will change from one week to the next, as the average number of deaths goes up and down based on the time of year) but this number should not be readjusted as the number of deaths are reported.
The information that I posted is listed for each week, for the 3rd week in May of the last 3 years.

Try this as a confirmation of what I am posting.
Today the 28th of July go to the graph and open each of the last three weeks then screen shot each of those numbers, then come back to that same site in 10 days to two weeks and the same graph and see how the, numbers of average number of deaths (predicted) changes and the upper bounds of excess deaths changes (predicted).

I have worked with this data for a number of years, I have never had those two numbers change (predicted) as they have during the Covid.

@Kay West Why do just not just check the graph. There are obvious peaks of excess deaths, COVID waves. If really want to coubr excess deaths, sum up deaths during COVID waves.

Checking the graph would require additional cognitive dissonance. Kay West does not want to learn anything that conflicts with their existing beliefs that COVID-19 deaths are a hoax.

Over the past few days, we’ve heard that there are changes about masking recommendations and about how the delta variant might affect people who are already fully vaccinated ( I’ll leave details to readers because they’re easy to find) so we can expect:
— anti-vaxxers/ Covid denialists to rant about how SBM never gets it right
— that this was planned all along to get additional vaccines and
— PH experts like Drs Fauci and Walensky can’t be trusted because Pharma..

HOWEVER I have also heard/ read the most insane BS courtesy of the usual suspects ( PRN, NN, AoA**, Mercola etc) such as “99% of people are already immune”, vaccines will kill millions SOON, Covid is just “another cold” etc.
I imagine that their ardent followers will appear at RI to argue about minute details taken out of context, misquotations or virology/ immunology that they don’t understand but here is the important fact:
the delta variant is causing illness and death at alarming rates in places with low vaccination rates AND places with higher vaccination rates have low rates of illness and death.
This is obvious and apparent wherever you look You don’t need peer reviewed studies, official documents or expert opinion- although they will come- to learn this: you only need maps.

** Kim comes up with a mind-numbing comparison today re Olympic athletes
.

I have to note this because it might explain many things about alties and their audiences..
I skim through long audios like NN/ Del/ PRN and sometimes run into something too hilarious for words:
in Adams’ post of yesterday, towards the end, as he rants against Big Cities, liberals and their mayors, he advises his listeners that if they own property in NYC, sell it right away because the whole city is collapsing ( just like in that Will Smith movie) and soon the property will be totally WORTHLESS!!!

Seriously. Similar rants by Null over the years ( Sell, sell, sell!!).. I’m sure that most of his listeners know nothing about NY because this advice would immediately be rejected as fanciful BS and thus cast doubt upon all of his other information about health and politics,
Why do I say that?
Because I had/ have family members who owned/ own property and it’s easy to plug their addresses into RE sites and get current estimates. My late grandmother’s property is valued at 6.25- 6.5M USD, my late uncle’s 17 foot wide attached house at around 2M, my cousin’s 4 bedroom house at 1.5M and my other cousin’s tiny duplex at 800K
This is not a new trend.

So I doubt that he has many followers in large cities because they would see him as a
source of mis-information used to manipulate readers

From ESPN:

BUFFALO, N.Y. — “Buffalo Bills wide receiver Cole Beasley, who has openly opposed the NFL’s policy on COVID-19 vaccinations, attempted to clarify his stance Wednesday, saying his gripe with the league is over the differing standards for vaccinated and unvaccinated players.”

“I’m not anti- or pro-vax — I’m pro-choice,” Beasley said, reading from a prepared statement after the Bills’ first practice of training camp.”

Where have we heard that before?

Beasley claims he lacks “all the proper information” about being vaccinated and wants to “live my one life like I want.”

Isn’t it hell when your dumb life choices come back to bite you?*

*One of Beasley’s penalties is that he’ll have to be Covid-tested daily, instead of biweekly like the vaccinated players. I’d guess that gets old fast.

Question:

In this photo, does the baseball cap Lyons-Weiler is wearing say “Make Orwell Stew Again”? I mean, there is an Orwell recipe for stew with ox kidney, garlic and bacon ? (yum), but it’s hard to tell what point L-W would be making with that hat to whatever fringe group he’s addressing.*

https://i.ytimg.com/vi/PX0fF_ecc6Q/hqdefault.jpg

*the Julia Child affiliate of Querdenken 711?

Sorry, it is a Make Orwell Fiction Again hat. No bacon was consumed in the manufacture.

Beloved by conspiracy theorists who think Big Brother is secretly being imposed by the Illuminati.

The 2019 appearance is here, in case anyone wants to see more than the 45 seconds I watched on mute.

Aarno

Do I have to woman splaine this, this will take an effort on your part. When you posted at 1239 had you even tried to open the graph?

Lets take the 29 may 2021 from the same graph.

a screen shot was taken of the data contained in the chart on 24th of June 2021

53,699 average
55,295 upper bounds
53,898 predicted

a screen shot was taken of the data contained in the chart on 14th of June 2021

53,658 average
55,203 upper bounds
55,719 predicted

a screen shot was taken of the data contained in the chart on the 29 July 2021

55,563 average
55,100 upper bounds
55,798. predicted.

They are lowering the upper bounds so there are more excess deaths. This pattern is repeated since at least april of 2021.

Chris as you can see YOU didn’t check the graph you just did what you always do, projection.

So did everyone notice what Kay West did there? They reordered the dates to make it look like the numbers were going down. In reality, the numbers went up from June 14th to June 24th, before going down by July 29th. Not nearly so nefarious when you see that it is fluctuating by about 0.3%, rather than steadily dropping. And when you look at how the numbers are calculated, it becomes obvious that this is to be expected.

A basic description of how the average deaths is calculated (with perhaps some minor tweaks, as this is taken from a Canadian study) is as follows:

An overdispersed Poisson generalized linear model with a linear time trend and a seasonal factor is fit to the data. The seasonal component aims to represent the expected pattern across weeks that repeats from year-to-year, and consists of a zero-order spline term with 11 knots, representing 10 distinct periods within a given year.Footnote14 The 10 periods are split between a single 7-week period corresponding to the current week being estimated and the 3 preceding and subsequent weeks, and 9 other 5-week periods corresponding to the rest of the year.

https://www.statcan.gc.ca/eng/statistical-programs/document/3233_D5_V1

Because it is a spline, it will adjust slightly as the weeks progress and data is added. (Note also that the model is fit to the data) This is totally normal behavior.

“Because it is a spline, it will adjust slightly as the weeks progress”

Ah. I am familiar with the cubic spline smoothing. Made my sat images look really nice. Not real. Not like now. Not valid any more. Real .25 km spatial/2.5 min temporal resolution is a much better representation.

@Coriolis In this context, noise means random fluctuations. It is not physical noie.

(There was a transcription error for the data from the July 29th screenshot (should be 53,563, but I assume that was not intentional, unlike the reordering of the dates)

Kevin
I was not being nefarious, I clearly showed the dates the screen shot was made.
If you want I have several weeks of screen shots for those dates 3 dates., I would be happy to share.

The first line had an average, the average should not change as it is based on past deaths. (unless the past deaths have somehow changed). I pointed out that this was from the prediction made on the 29th May 2021. The CDC then changed their WAG even two months later, to show/prove that there were ‘excess’ deaths.

The upper bounds should also not change, as it is a prediction (again with past data to justify the prediction). I mean that would be changing the hypothesis of an experiment as the data that you are obtaining shows your hypothesis was wrong.

Simply put you don’t get to change your bet in the middle of a horse race or a poker game.

This did not just happen on the 29th of May this is an ongoing changing of the upper bounds (downward). As I put in my previous post the upper bounds for excessive deaths for 2021 was lower that excessive death in 2019 as does the average number of deaths. Shouldn’t the average number of death rise every year based on our gowning population?

Kay, to put it quite simply, you are wrong when you imply that the average is based solely on past deaths. As I stated, a seasonal factor using spline terms is also included in the calculation on average, and the knots in the spline terms shift forward a week, every week. As a result, every week the average deaths are recalculated and change slightly. And since the upper bound is determined by the average, that adjusts weekly as well. You haven’t looked far enough back, have you? Even the averages from the beginning of 2017 change slightly every week.

For example, using the Wayback Machine I grabbed the data file from March 18, 2021 and compared it to the data file from today, July 30th, 2021. Let’s take a look at the first date in each file (for the United States as a whole, they also have the data for the individual states), January 14, 2017.

March 18 data file
Predicted Deaths: 61114
Upper Bound: 63419
Average Deaths: 60567

July 30 data file
Predicted Deaths: 61114
Upper Bound: 63970
Average Deaths: 60823

The CDC has no reason to surreptitiously change average deaths and upper bounds all the way back in 2017. But given that we know they are using spline terms, with knots every 5 weeks or so, it becomes immediately apparent that they are not locking in the number each week, but rather letting the model change the numbers slightly as each week passes.

Why are they using a spline??????

The three numbers are projections.

Average

Upper Bounds

Predicted.

They are forecast (well two of them are).

The ‘average’ is the average deaths for population of 340 million people in the US for that week (the CDC uses a different number of the week, which usually starts in October, as week one etc)

The Upper Bounds is the point at which the deaths are outside the normal range of expected deaths.

The Predicted deaths are what the CDC thinks will be the final number of deaths.

The Average death should be a hard and fast number (pretty much/more or less based on actuarial tables).

The Upper bounds are determined by the a fore mentioned ‘average’ (they might be better to call it outside the range of expected deaths)

and the Predicted is based on what the CDC thinks will be the death toll, why would that number get to change, as it is what it says it is a PREDICTION ?

They may be using a spline, but the bottom line is WHY?????

Does the local weather person get to go back 10 days or two weeks or 2 years and change their forecast so it looks like they were more accurate then their original prediction.

Does NOAA get to change the range of highs and lows after the day in question?

As I said before does a person playing poker get to pull back money he/she bet after each turn to the card?

Does an insurance company get to go back after you died and charge you more because you died before they predicted you would?

Your explanation of the CDC using a spline may be accurate but the question still stands, why?

Block this request

They may be using a spline, but the bottom line is WHY?????

Great, you’re shrieking because you don’t understand something or have an idea of how to figure it out. Would you prefer polynomials?

Time series data are noisy.

@Kay West I assure you, health insurance company would rise premium when health care costs rise (Personal experience)
If you meant literally, why spline is used, that is because many low grade polynoms fit better to data than one hign degree one,
If you ask why data from previous months is taken into account, that is what modelling is. How you can predict future if you drop all past data ? Metereologists include observations (which is past data) to their predictions.

Kevin
Would heath care or life insurance companies go back and adjust your past payments, because their tables were wrong.
I have no issues with the CDC using past data from previous months to make a better model. The weather service does that all the time.
But is different than what the CDC is doing is, the weather service is not going back in time to change the basic data. the data is collected and then compared with what was predicted and future models are adjusted to make better forecasts models based on what they predicted would happen vs what really did happen.

But that is not what is happening at the CDC as far as these figures show.
The CDC makes a prediction for those 3 categories based on the past (as I said must the same as a life insurance company uses an actuary table). But then they change those numbers to fit.

If they keep adjusting past numbers (of the 3 categories) they will never get a model to accurately predict anything.

What they are doing is adjust the numbers to fit their model, that would explain your use of a spline.

but that still begs the question

But is different than what the CDC is doing is, the weather service is not going back in time to change the basic data.

But that’s just it. The CDC isn’t altering the basic data, you just don’t understand what the basic data is. The basic data is in fact the predicted value from previous years. The predicted value is the actual reported deaths, weighted to account for deaths that haven’t yet been reported. Eventually (it takes more than a year to finalize) the predicted value becomes the actual number of deaths, and doesn’t change. Whereas the average deaths is just an approximation calculated by the model using the predicted deaths of previous years. Because splines are used to smooth the data, every five weeks of data is bundled together to make a knot for the spline (except the current week and the three weeks before and after). Every week, the groups of five shift forward a week, causing the average deaths for a given historical week to change slightly. However, there follows another knot, moving at the same speed as the first, so the average deaths for the week in question end up cycling through a narrow range of values every 5 weeks (modulo close to the current week number).

Would you object if the average deaths were expressed as say, 55,200 +/- 100? That is effectively how the CDC is treating the data, just giving numbers that fluctuate with the range.

@W. Kevin Vicklund

There is information in noise. An extreme example might be the anomalous readings of automated tilting bucket rain guages. Later to be used as a proxy for the strength of the tornado that passed over.

For those interested in Orwellian cookery, here is his basic recipe for kidney stew:

1/2 lb Ox kidney chopped-up small
1/2 lb Mushrooms
1 Onion Chopped Fine
2 Cloves Garlic
Four Skinned Tomatoes,
1 Slice of Lean Bacon chopped up
Salt.
Stew gently for 2.5 hours in very little beef stock

They go into more detail on the following site, for those who are not “intimidated by offal”. I am not intimidated, but my pathology experiences have made me leery of consuming certain body parts.

http://criticaldispatches.com/cooking-orwells-recipe/

Orwell was also an enthusiastic vegetable gardener based on his diaries.

A faith in “research”, no matter how dubious, makes you vulnerable to false beliefs. Who’da thunk it?

“We identify two critical determinants of vulnerability to pseudoscience. First, participants who trust science are more likely to believe and disseminate false claims that contain scientific references than false claims that do not. Second, reminding participants of the value of critical evaluation reduces belief in false claims, whereas reminders of the value of trusting science do not. We conclude that trust in science, although desirable in many ways, makes people vulnerable to pseudoscience.”

http://sciencedirect.com/science/article/abs/pii/S0022103121000871?fbclid=IwAR3xhXMRO1kzdpCsyKn-g-pNNHxO4hVVUh2eQpB6VkS6OVlP9hIE6MfWO1c

Wonder if the authors of this study considered the possibility that people with critical thinking skills tend to trust properly conducted, validated and repeatable science, and that such outcomes are beneficial.

Anti-vaxxers are all about the people. They think they care about the science but, in reality, they only believe in information that confirms their preconceptions or that comes from people like them.

We have to rely on experts. Those experts are human and have preconceptions, biasses, politics, bad days….humanity in other words. So, if I’m going to pick a person to believe, it’s going to be the person who has done the most to remove those concepts from their work. It’s going to be the person who’s results match up with multiple other people’s scientific research because there’s nothing like multiple sources of confirmation to indicate a correct answer.

At the end of the day, they still might get it wrong but if you want a kidney removed you don’t ask a dentist. The dentist is never the correct solution when there’s a surgeon available. Even if you dislike the surgeon.

So very true.
Anti-vaxxers and pseudo-scientists pre-select their answers in advance and the people who provide them. It’s a cult of personality amongst the like-minded.

But there is usually window-dressing/ cosplay / cargo-cult/ posturing at science to lend an air of credibility to their machinations. They set up studies, use statistics, quote “experts” and mis-quote actual research or merely mangle it to fit into their pre-conceived notions. If you listened to/ read the people I survey about Covid, you might think that most people who are ill or have died recently are vaccinated when the results are quite the reverse. They might say, ” There is an increase in the number of vaccinated people testing positive for Covid ” but leave out the rest of the sentence ( without the ellipsis) that says that 95% of them were asymptomatic or had mild illness.

in addition, they select their own experts. Paradoxically, they usually heap scorn upon mainstream science and universities BUT if they want to raise up a contrarian, they will cite- and inflate- his or her academic background and “orthodoxy”. Cosplay often involves lab coats ( Adams) and titles like “senior research fellow” ( Null) as well as “investigative reporter” ( Bigtree) and “science journalist”, Jeffery Jaxen.

Thus they are able to con people who never studied the area of concern in detail and
don’t understand how material becomes regarded as consensus science rather than cherry picked outlier results. During Wakefield’s heyday, there were not any unaligned researchers’ results that replicated his own or suggested his correctness.. .

Jimmy (on Twitter) is clapping his paws with glee over Dr. Stella Immanuel suing CNN for $100 million, for making her look like a deranged quack.

Could it be that Satanists are infecting his mind with alien DNA?

Kay West wrote: “the weather service is not going back in time to change the basic data. the data is collected and then compared with what was predicted and future models are adjusted to make better forecasts models based on what they predicted would happen vs what really did happen.”

Have you heard about reanalysis of past storm seasons? They don’t “change the data” in the sense of making up numbers they like better, but they do apply the data we have now to find past tropical storms that weren’t identified while they were happening, where “past” can mean anything from a few months ago to decades ago.

There are also people who look at old data to figure out whether reported temperature records from decades ago are reliable/meaningful. The currently recognized world high temperature, from Death Valley, isn’t as hot as the long-reported record from Libya, and the weather historians who determined that the Libyan record wasn’t valid have raised doubts about the old Death Valley record. (A lot of records from before World War II are questionable, for reasons including both lazy or careless recording, and thermometers in direct sunlight instead of shade.)

I really didn’t want to get this far off topic on exact temperature measurement.
But you are questioning the ability, skill, care and ‘laziness” of the weather service to exactly measure temperature, wind speed etc. to even a few months ago (according to your post)(and a what point did all the temperature, precipitation, wind speed etc. become good data?) . But you did make my point that they don’t change the data, they “reanalysis” it, that is not what the CDC is doing!

and climate change is for a blog some where else.

Do you also question other scientist to be able to read gauges or measurements in any of the scientific papers in medicine etc.

I put into my first post the website for the CDC under excess deaths. No one that has responded to me has ever mentioned that the CDC on the 9 of September 2020 (in the middle of the pandemic) changed the method of reporting and accounting of excess deaths.

Normal companies, when they do change accounting methods, have to provide to the stock holders a side by side comparison on what the numbers would look like under the old method vs the new method.

@Key West CDC changed algorithms ?Perhaps you can give us a citation ?

It’s from the technical notes of the CDC site:

Methods to address reporting lags (i.e. underreporting) were updated as of September 9, 2020. Generally, these updates resulted in estimates of the total number of excess deaths that were approximately 5% smaller than the previous method, as weights in some jurisdictions with improved timeliness were reduced. While these adjustments likely reduce potential overestimation for those jurisdictions with improved timeliness, estimates for the most recent weeks for the US overall are likely underestimated to a larger extent than in previous releases. Some jurisdictions have little to no provisional data available in the most recent week(s) (CT, NC, WV); together, these jurisdictions represent approximately 5% of US deaths. In previous releases, some of the underestimation or lack of provisional data from certain jurisdictions was offset by the overestimation in other jurisdictions with improved timeliness when considering trends for the US overall. Because the updated weighting methods mitigate the impact of the previous overestimation for some jurisdictions with improved timeliness but provide no additional adjustments for underestimation or a lack of recent provisional data in other jurisdictions, the excess death estimates for the US overall are expected to result in a larger degree of underestimation than in previous releases.

Kay read the first sentence and couldn’t be bothered to read the rest of the paragraph (which discusses how the numbers changed due to the change in methodology). While we’re on the topic, the methods were previously updated on May 12, 2020. Note that this only affects the first few weeks that a given week is reported, in the Predicted Deaths category. Basically, due to the pandemic, a number of jurisdictions were more timely in reporting data than they were historically, so the algorithm was putting too much weight on their early death counts. As more data comes in, the weighting relaxes, until the death counts for the week in question (keep in mind, only 60% of the deaths are reported in the first 10 days, so it takes a while for the official death count to match up to the predicted).

You can see how the difference in weighted vs. unweighted (or predicted vs. reported) gradually declines by clicking on the third dashboard, Excess deaths with and without weighting (don’t forget to refresh the graph). The dark blue is the deaths reported so far, the light blue is the additional predicted deaths (which are always based on weighting the deaths reported so far).

AARNO
I only posted ONE citation, in my posts.
https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm

I posted TWO sets of numbers from this same ONE citation.

I posted that the CDC was clearly changing their projections, excess deaths and average deaths even after the week in question had passed, one poster claimed they were monthly projections, excess deaths and average deaths (clearly having not even examined the chart/graph or the research that went into the making of the chart/graph as the chart/graph is broken down into weeks.

I attempted to make comparison to everyday things like weather forecast, wagers for the non science people who might visit this site, and that changing predictions is at best nonsensical, and was met with hollow arguments and defection, but that really never answered the question, as to why they were changing the first two projections (average and excess deaths).

You demanded a citation for my claim that the CDC changed ‘Methodology” in the middle of the pandemic.
So I will cut and paste from the Technical Notes that were published right below the graph in the same CDC site. as you asked.
“Methods to address reporting lags (i.e. underreporting) were updated as of September 9, 2020. Generally, these updates resulted in estimates of the total number of excess deaths that were approximately 5% smaller than the previous method, as weights in some jurisdictions with improved timeliness were reduced.”

You all claim to be skeptics and science based but most of you never really read or comprehend what you read, but just post stuff to be contrarians or many be just get a thrill out of posting.

If any of you do peer review,it is no wonder the belief in science is in decline.

I posted that the CDC was clearly changing their projections, excess deaths and average deaths even after the week in question had passed,

EVEN after the week in question had passed? They aren’t posting their first projections until about two weeks after the week in question has passed. They aren’t trying to predict the future, they’re trying to project past events based on partial data.

Does FEMA (or whoever) change its estimated death toll after a disaster as more deaths are confirmed? Yes, of course. You’re using the wrong examples – all your examples involve predicting a future event (especially inapt because the outcome is immediately measurable). It can take months for the total deaths for a given week to be reported. The CDC has to make decisions on a shorter time frame than that, and you damn well better believe I want them to be able to use the most up-to-date information. I certainly don’t want them to be forced to use projections based on weeks-old data when more recent data is available.

It’s almost as if you don’t have a clue what this is chart is being used for…

@Kay West As Kevin already noticed, you missed something:
“Methods to address reporting lags (i.e. underreporting) were updated as of September 9, 2020. Generally, these updates resulted in estimates of the total number of excess deaths that were approximately 5% smaller than the previous method, as weights in some jurisdictions with improved timeliness were reduced.”
You cited first sentence, but not second one. Change of method reduced number of excess deaths. CDC said, too, that they fixed problem with untimely reporting.
You were dishonest, I would say. But I am not surprised that an antivaxer uses selective citations. Usually they are not this obvious, though.

Correction, Aarno, Kay did cite the second sentence, but as you and I noted, does not seem to have understood it.

AARNO

You made my point that I posted in my first two posts.

The CDC is under counting the excess deaths in their prediction. That in turn makes the actual number of deaths in excess of the posted number look higher.
And I did post what you claimed I didn’t, as usual you didn’t read or comprehend.

And as usual you ended your post with an attack with an “ad hominem”.

But at least you didn’t call me “DEARY” as some other posters do in their replies to females.

KEVIN

We have a word issue then. The CDC is calling it a ‘Prediction/Predicted’

You use FEMA as an example (please don’t go to global warming in response).

FEMA doesn’t predict death toll or damage due to hurricanes etc. They do estimates after the fact, that is not what CDC is doing. Have you ever heard FEMA saying, well based on the past land fall of a cat 4 hurricane we predict 185 people will die. Or state, 20 people are going to die during the hurricane anything over that number will be excess deaths. The CDC is mixing apples (Covid) and oranges (cancers) and grapes (heart issues) and cherries (drug overdoses) and blaming the excess numbers on COVID. (the title of the CDC website is call “excess deaths due to Covid”

A better example would be your state law enforcement predicting that 35 people will die in traffic accidents over the 4th of July, 3 day weekend, that estimation is based on science involving gasoline delivered to filling station, alcohol deliveries , expected weather conditions, estimations from auto insurance companies of miles that will be driven and from police records of past 3 day weekends on the 4th of July. If the estimates are wrong the added facts are inputted to the computer to make the next prediction closer to what (will) really happened. (the output is used to make corrections to the problematic issues that the state finds (poor road design, lack of enforcement etc.) The predicted accident deaths are not change but the CDC does change the predicted/excess deaths numbers, which in reality does not do anything to enhance the prevention and only serves to make the CDC look good in their predictions.

I would apologize calling you dishonest. You just do not understand anything.
Actually CDC fixed their prediction, resulting less excess deaths. How this would mean more excess deaths after September 2020 ? My point was that this not how somebody making out excess deaths would behave. You must understand error margin, too. It is excess deaths plus minus something.
You do not understand that CDC does not have all data immediately at hand. Reporting takes time.. Prediction changes when CDC has more accurate data. It is all explained in a chapter from you picked your sentence

AARNO

Definition of average (Entry 1 of 3)
1a : a single value (such as a mean, mode, or median) that summarizes or represents the general significance of a set of unequal values
b : MEAN sense 1b
2a : an estimation of or approximation to an arithmetic mean
b : a level (as of intelligence) typical of a group, class, or series
above the average

Definition of predict
transitive verb
to declare or indicate in advance
especially : foretell on the basis of observation, experience, or scientific reason
intransitive verb

to make a prediction

Key words “in advance”, If I got to place a bet on a horse race after the race was finished, I’d be richer then Jeff “Bezos”

@Kay West CDC says this:
“Until data are finalized (typically 12 months after the close of the data year), it is not possible to determine whether observed decreases in mortality using provisional data are due to true declines or to incomplete reporting. ”
Taking all data would really take time. CDC is correcting estimates when data comes in.

So what’s up with this latest “bombshell” Covid-19 vaccine news that the Usual Suspects are suppressing?

A German pathologist, Peter Schirmacher, who is described as “renowned” or “respected” (never heard of him myself, but he has been part of quite of a few published papers, including one having to do with a vaccine against nicotine, apparently for smoking cessation) has announced that Covid-19 vaccination is killing a whole mess of people, and so we should be alarmed. I can only find the story on a few obscure websites whose grip on reality seems to be a bit tenuous, but they all seem to be quoting from a release that badly needs fleshing out. This is the jist of it:

“In Baden-Württemberg, the pathologists therefore worked with public prosecutors, the police and resident doctors, reports Schirmacher. More than 40 people have already been autopsied who died within two weeks of being vaccinated. Schirmacher assumes that 30 to 40 percent of them died from the vaccination.”*

http://noqreport.com/2021/08/04/media-blackout-renowned-german-pathologists-vaccine-autopsy-data-is-shocking-and-being-censored/

And that’s it. No word on what the gross and microscopic findings and official causes of death are in the 40 cases, but vague allusions are made to cerebral thrombosis and autoimmune diseases.

Critics have apparently faulted his conclusions, but Schirmacher says they are “definitely wrong”, which is the way you settle scientific disagreements.

Antivaxers are leaping on this story, because of course they are, and you can’t disagree with a doctor even when loads of his/her physician colleagues think they’re full of it.

*That’s how I’ve always signed out autopsy reports. “I _assume_ this patient died of X.”

This has a certain ring of familiarity:

Dennoch: Schirmacher selbst betont, er sei keinesfalls ein Impfgegner. Er selbst ist nach eigenen Angaben geimpft. Eine Impfung gegen Corona ist seiner Ansicht nach auch ein wesentlicher Bestandteil im Kampf gegen das Virus. Die Gründe für eine Impfung müsse man allerdings individuell abwägen. Die Zahl tödlicher Impffolgen wird aus seiner Sicht aktuell aber unterschätzt.

Or,

Nevertheless: Schirmacher himself emphasizes that he is in no way opposed to vaccinations. He himself is vaccinated by his own account. In his opinion, a vaccination against corona is also an essential component in the fight against the virus. The reasons for a vaccination, however, have to be weighed up individually. From his point of view, the number of fatal consequences of vaccinations is currently underestimated.

Problem is, even if there are some quibbles with the methodology, how would such issues explain such ENORMOUS differences between the health of the vaxxed and unvaxxed children are telling. It would be more difficult to rig a study to produce such results than to rig a “vaccine safety” study, which is in fact the norm by using other vaccines of equally questionable safety as “placebos” in most instances; or, even if proper placebos were used, as for the COVID genetic modifications, disregarding “probable cases”, as noted from the editorial in the BMJ: ttps://blogs.bmj.com/bmj/2021/01/04/peter-doshi-pfizer-and-modernas-95-effective-vaccines-we-need-more-details-and-the-raw-data/

And now a little over a half year since the COVID jabs were rolled out, and after a majority of people got them, a new variant has foiled them, just as so many people who were mocked had predicted. Look how fully vaccinated Gibraltar has been doing as of late: https://www.worldometers.info/coronavirus/country/gibraltar/ In July they had the highest number of cases since… just after the vaccine rollout. Now how do we blame the unvacciated for that one?

Let’s see: lab origin, emergence of variants, only effective for symptoms in the sort term, what “crazy theory” of these “crackpots” will be proven correct next? Maybe instead of mocking them and turning a blind eye, we’d be better off paying better attention.

Instead of attacking the methodology, the far better course of action for public health would be a deep dive into medical records to really get at the truth. But the CDC has balked at numerous overtures to do so, and keeps the records it has sealed under lock and key. Where are the v-safe data on the COVID jabs, for example. Just why is this?

Mine were not “minor quibbles with the methodology.” The methodology was awful and bogus right from the inception of the study.

Ah, the ol’ “Gibraltar gambit.” (It’s a lot more built up than when I saw it last.)

In July they had the highest number of cases since… just after the vaccine rollout.

With one death, and one-third the prevaccine peak number of cases.

Now how do we blame the unvacciated for that one?

Try putting on your cipherin’ hat and muse on how the Delta variant got there in the first place.

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