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Random effects won't solve the problem of generalizability.

Adam BearJonathan Phillips
Published in: The Behavioral and brain sciences (2022)
Yarkoni argues that researchers making broad inferences often use impoverished statistical models that fail to include important sources of variation as random effects. We argue, however, that for many common study designs, random effects are inappropriate and insufficient to draw general inferences, as the source of variation is not random, but systematic.
Keyphrases
  • drinking water
  • neural network