The Retraction of Our Homeopathy ADHS Meta-Analysis Causes a Stir

A reference to an article on and my questions to the author, Hinnerk Feldwisch-Drentrup

On Monday, Nov 6, 2023, an article appeared on, which addresses the retraction of the publication of our homeopathy ADHS meta-analysis. On the occasion of this incident, he also mentions the other two retractions (of the “Vaccines” study [1], which was republished in “Science, Public Health Policy and the Law” after a triple-blinded review [2] and the children’s mask study [3], which was republished in “Environmental Research” after an extensive review in its long version [4]).

The article is a very good example of how one can apparently work journalistically correctly, namely by not making any false statements or providing good evidence for one’s assertions, but still lying. Because there are two kinds of lies: Someone can lie by claiming something false. And someone can lie by omitting or concealing known, true and important facts. In this case, the second form of lie is endemic. It leads very easily to the presumably intended effect, namely the assassination of my character in the view of all those who don’t know me and who don’t have the time or inclination to take a closer look at the matter. This will probably lead to Wikipedia authors finding even more reason to make critical comments in the article about me, which means that the critical citation cat bites its own tail once more.

Feldwisch-Drentrup knows from me what he is hiding, or could easily have found out by doing more research. I had sent him a detailed email with details about this retraction and the meta-analysis, which are not mentioned in the article.

I then sent him the following letter and waited until Monday, Nov 13, 2023, the deadline, for a response. Having received none, I am publishing the letter. If I receive a reply later, I will of course also publish it.

Here is my letter:

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Pitfalls of Meta-Analyses

A brief methodological commentary on the retraction of our homeopathy ADHD meta-analysis

We had rejoiced too soon. Last summer, I reported that we were able to publish a meta-analysis on homeopathy in ADHD, which showed a significant effect size of g = 0.6 [1]. It was recently retracted by the journal, not by us.

The background: We had made an extraction error, namely positively coding an effect size that should actually be negatively coded. This is one of the pitfalls in a meta-analysis that I have now stumbled across myself. Because you always have to ask yourself: Do the effects of a study point in the direction of the hypothesis, i.e. do they support the assumption that the difference speaks for the effectiveness of a treatment, or against it? In this case [2], the result was not only not significant in favor of homeopathy, but even pointed in the other direction. This should have been marked with a minus sign in the analysis, which I had simply overlooked. And my colleagues didn’t notice it either, so this very stupid mistake crept in.

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Modelling and Model Building

…using the example of our study: “Identification of different factors associated with Covid-19 deaths in Europe during the first pandemic wave”

A large group of statistical techniques designed to explain past data and also to predict future data is statistical modelling. This means that for a given data set with very different variables, one finds a mathematical structure that represents this data set as well as possible, firstly in a purely formal way. This procedure can be used to examine the influence of different variables on an outcome variable. In the language of modelling, the variable that one wants to explain is the dependent variable or criterion or outcome variable, and the different variables that are supposed to contribute to the clarification of this one variable are several independent variables resp. predictors.

I use our recently published modelling study [1] as a concrete example. It was conceived by me, I calculated the first analyses, then my colleague Rainer J. Klement got involved, who as a physicist is much more nimble in dealing with such models than I am.

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Homeopathy Works for Attention Deficit and Hyperactivity Disorder (ADHD)

and is helpful within limits in healing wounds.

Homeopathy and the results of two meta-analyses

A few years ago, the leader of the German Green Party, Robert Habeck, proclaimed in the heart of conviction, that homeopathy is no more than placebo. Many politicians and medical administrators dutifully agreed. Our health blabbermouth, Health Minister Lauterbach, wants to pour this into a set of rules and remove homeopathy completely from all medical books. Since then, it has become politically incorrect to be pro-homeopathy.

I still think homeopathy is good and have done for a long time, thus I have also been politically incorrect for a long time. Because I am less interested in the opinions of people who have only a very limited idea of the matter and certainly not in the arguments that proceed from unreflected theoretical presuppositions. What I am chiefly interested in, is the data. Because I am politically incorrect, a foundation that supports homeopathy a while ago removed me from my role as a blogger, where I used to comment on new data and studies on the blog Homö

Nevertheless, I like homeopathy and engage with it when the opportunity arises, or I am asked. I take the publication of our new meta-analysis on the efficacy of homeopathy in attention deficit hyperactivity disorder in children [1] and our somewhat older meta-analysis on Arnica in wound healing [2], published last year in Frontiers in Surgery, as an opportunity to draw attention to homeopathy.

I would also like to take this opportunity to pass on some methodological knowledge on the subject of meta-analyses in my newest chapter of my methodology blog.

I will start with a small political preface to help understand the general situation, then for those who do not yet know much about it, a few words about homeopathy in general.

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