Shouldn’t there be a neutral group that gets to decide what data is tossed out before arriving at conclusions? Case in point: Ansel Keys Seven Nations Study (he tossed out data from countries that didn’t support the conclusion that saturated fats were bad). I mean, OK if funding sources, and pre-stated hypothesis creates bias, shouldn’t the publication process vet the data better?
In:
A person reading the paper can evaluate whether excluding certain data is valid or not. But generally, poor data is excluded. If you have 10 things saying A but the 10 things are biased or measured wrong, and 1 thing saying B which was bias-free and measured well, then you trust the 1 thing rather than the 10 things just because the evidence supporting A is poorer.
https://www.truehealthinitiative.org/wp-content/uploads/2017/07/SCS-White-Paper.THI_.8-1-17.pdf
In this white paper, pages 5-8 outline rationales for excluding certain data sets which include:
> While it is true that selection of cohorts was non-random, selection was based on
practicality and dietary variation.
1–4 Allegations suggesting that SCS researchers
chose locations where they already knew the outcomes are clearly false based on
review of primary source material, the relevant timelines, and direct questioning
of investigators.
and
> Critics attest that France was excluded because researchers were aware of the
“French Paradox”, but this concept represents an anachronism, since the
information and associations being used today to allege bias were simply not
available at the time the SCS was being designed and implemented.
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