Makes sense to me. A random-effects is essentially a multilevel model, and you'd expect correct modeling of such heterogeneity to increase rather than decrease power.
Can meta-analyzing results from subsets give you more precision than analyzing all the data together? It would seem that it shouldn't, but hmm. https://www.reddit.com/r/rstats/comments/85t039/metafor_in_metaanalysis/ … #rstatspic.twitter.com/rNwsOMgorU
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Maybe do some simulations to confirm.
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Kahneman talks about the "law of small numbers" in Thinking, fast and slow. Small samples are more extreme/less representative than large samples. I could see getting more extreme t-stats from smaller samples. Not sure if relevant
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Sounds like bootstrap?
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