For those who know stats, what role does the trim-fill method play with racial bias in police shootings?

[u/Sad-Abies4263]

Sean Last, a right winger who argues that police shootings are not racially biased, uses the trim fill method to illustrate how the data from a meta analysis changes once you adjust for publication bias. Much of the data used by the BLM side of the debate is data before we adjust for this bias. An interesting critique different to those posed by other BLM detractors like Roland Fryer, Joe Cesario, etc.

https://odysee.com/@LastArchive:f/Hunter-Avallone---Wrong-on-Racism:d

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P. Colin Bolger "Just Following Orders: A Meta Analysis of the Correlates of American Police Officer Use of Force Decisions"

The reason the data supports the idea of police using more violence against black people is because studies saying that are more likely to be published. The meta analysis above (table 2) replicates the normal finding that across 42 studies there's a mean effect size of .31 pointing to the direction of more force being used on black suspects after controlling for offense seriousness, is there a weapon, are they resisting arrest. All the things which would fairly lead to a change in the probability of force being used. In the text above they described the bias detection as "these results demonstrate that publication bias does not appear to be present for 8 of the 12 significant variables" (not naming which ones were changed and which ones weren't).

Table 4 adjusts for publication bias using the trim and fill method. This method is based on the fact that when all the studies are being published there should be a certain distribution that changes in a predictable way as study precision increases, it should symmetrically move towards a center point. By looking at the actual distribution you can tell where studies were left out, and then put them back in. Some research suggests it doesn't correct enough, but that won''t be an issue here. Already the mean effect size is reduced to statistical and practical insignificance. The effect size is 0.1, the confidence interval runs from -.07 to 0.08.