The paper, linked below, is now In Press in Statistics in Biopharmaceutical Research. If you have any interest in meta-analysis, which is at the apex of most evidence pyramids, or are seeking a fertile area for further research, you should pay close attention to this paper. If you are a peer-reviewer of a report of a meta-analysis of clinical trials, I hope you prioritize the math over tradition to be sure there are evidence-based conclusions. Start by reading the second and third paragraphs of the introduction, which motivate the importance of this article. Next, Section 2 demonstrates that the current mainstream methods (Inverse variance weighting) represent a misuse of linear combination theory, rendering these estimates potentially seriously biased. Mainstream methodology can lead to unsupportable conclusions about a therapy. Section 3 produces an asymptotically valid methodology, but it defines its target population differently from the mainstream. The Shuster (2023) reference in the link showed in two examples from major medical journals that unsupportable public health conclusions that affected patient safety were reached.
Mainstream Meta-Analysis of Clinical Trials produces strongly Inconsistent Estimators
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Jonathan Shuster
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