Uncertain Data Invalidates Recommendations, Dude

Retraction Watch notes the retraction of a paper “… claiming two deaths from COVID-19 vaccination for every three prevented cases,” and the defense of the authors, lead by Harald Walach:

We are happy to concede that the data we used – the large Israeli field study to gauge the number needed to vaccinate and the LAREB data to estimate side-effects and harms – are far from perfect, and we said so in our paper. But we did not use them incorrectly. We used imperfect data correctly. We are not responsible for the validity and correctness of the data, but for the correctness of the analysis. We contend that our analysis was correct. We agree with LAREB that their data is not good enough. But this is not our fault, nor can one deduce incorrect use of data or incorrect analysis.

The title of this paper?

The Safety of COVID-19 Vaccinations—We Should Rethink the Policy

And my point is that if you’re writing a paper that recommends a course of action, of course you’re responsible for using data that meets adequate standards of dependability and applicability. Shrugging those responsibilities off on someone else also means losing the moral authority to recommend a change in the course of action.

Especially when the analysis conclusion is sending up red flags such as these.

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About Hue White

Former BBS operator; software engineer; cat lackey.

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