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Modelling and Model Building

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…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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Meta-Review: The Backbone of Evidence Based Medicine Is Weak

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Only about 6 percent of all interventions used in medicine have sufficiently good data and are effective

Our new meta-review shows: The backbone of Evidence Based Medicine is weak

Regular readers of my texts know that I am very sceptical about the postmodern redemption narrative of modern medicine that proclaims: We live so long and do so well because modern medicine has made such tremendous advances. Therefore, everything that modern pharmacology brings us is good, welcome and worthy of support (and should be funded by the public).

Even the legendary social physician Thomas McKeown from Birmingham pointed out in the 1970s that this widespread popular opinion is most likely wrong and said in the introduction to his still very readable work “The Role of Medicine: Dream, Mirage, or Nemesis?” [1,2]: If he were St. Peter, he would only allow two types of doctors into heaven, namely trauma surgeons and dentists. Because those would be the only ones who really contributed to a reduction of suffering. The real progress and thus the extension of life span and the improvement of quality of life would not be due to medicine, but to socio-political progress, better nutrition, hygiene and living conditions without constant fear of hardship and death.

Well, that was in the 70s. Maybe it’s different today? We did a very large meta-study to answer the question of how good the data is for medical interventions in general. It has now been published in the Journal of Clinical Epidemiology [3]. I discuss the study and its findings in a little more detail in this blog. For those in a hurry: the data has not changed much. A maximum of 6 percent of all interventions used in medicine, no matter where, are covered by good data.

Only for a limited time (until 08-22-2022) the meta-review is freely accessible at: https://authors.elsevier.com/c/1fIHz3BcJQAobl

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Homeopathy Works for Attention Deficit and Hyperactivity Disorder (ADHD)

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…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 Homöopathie.info. 

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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Monkey Pox – Conspiracy (Theory) for Advanced Learners…

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and some thoughts on prospective tests of such a theory

When one types “Monkeypox” into internet search engines, the first thing that comes up is agency reports from Reuter and Co debunking “conspiracy theories” about Monkeypox. Interested readers ask themselves: Why does this have to be mentioned so prominently? We examine what exactly could have given rise to a conspiracy theory and how, at best, this conspiracy could be checked prospectively, i.e. concerning the future.

Monkeypox

Monkeypox, we learn from a recent information column published in the Journal of the American Medical Association (JAMA) [1], is a virus from the smallpox family that is relatively harmless to humans and whose final hosts are not humans but small rodents such as gopher, prairie dog, etc. As a DNA virus, the Monkeypox virus is much more stable and therefore mutates only slowly and little. The doctor and biochemist who writes under the pseudonym Jochen Ziegler on Achgut has written a very concise article on this. Therefore, I do not need to repeat it.

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Face Masks Lead to Dangerously High Levels of Carbon Dioxide in Children’s Inhaled Air

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The long version of our mask study has been republished

A workshop report and some thoughts on it

Our mask study measured carbon dioxide levels in the inhaled air of 45 children wearing face masks. It found that the inhaled air under children’s face masks contained unacceptably high levels of carbon dioxide, about 1.3% to 1.4% by volume, or 13,000 to 14,000 parts per million. Normal outdoor carbon dioxide levels are 400 ppm or 0.04% by volume. The Federal Environment Agency and various protective regulations have determined that 2,000 ppm or 0.2 vol.-% is the upper limit above which damage to health cannot be ruled out. For children, such high values, as we measured after only 3 minutes, are absolutely unacceptable. Especially against the background that children are neither at high risk of corona infections and Sars-CoV2 nor are they important spreaders of infections.

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