Is it sensible to consider meta-analysis the strongest level of evidence for or against an intervention?

[R_cubed]

There are some good links in this discussion from a philosophical POV:

2019 Nobel Prize in Economic Sciences is about limitations of RCT

This article summarizes the 2019 Nobel Price in Economics" What randomisation can and cannot do: The 2019 Nobel Prize Their critique of randomized controlled trials (RCT) is three-fold: They make no specific claim about external validity. In economics it requires a pre-existing system the study is embedded within. In a plumbing metaphor, the studies focus on problems in existing plumbing–not upon how to engineer and install a system. Optimal experimental design is generally not an RCT. From …

I collected some references here:

Stability of results from small RCTs

Blockquote Randomization does not guarantee exchangeability. The very definition of random implies imbalances in prognostic factors could happen, even if they are more and more rare as the sample size increases. This very important point is carefully elaborated in the following: So that leads me to the following question: Are small randomized trials worth conducting? In a previous post @f2harrell wrote: Blockquote Most statisticians I’ve spoken with who frequently collaborate with …

The paper on Theory of Experimenters is likely your best starting point.

For a more pragmatic discussion, the following dissertation is worth close study if your field involves small sample research. With small samples, we need to think hard about the need for efficiency that algorithmic balancing provides, with the need for robustness that randomization provides. The author was advised by Dr. Harrell and Dr. Blume.

Chipman, Jonathan Joseph (2019) Sequential Rematched Randomization and Adaptive Monitoring with the Second-Generation p-Value to increase the efficiency and efficacy of Randomized Clinical Trials (link)