Guess et al. (2023) null findings on affective polarization do not rule out algorithmic effects below the study's detectable threshold or ef
Guess et al. (2023) null findings on affective polarization do not rule out algorithmic effects below the study's detectable threshold or effects on non-volunteer subpopulations; absence-of-evidence arguments require specification of minimum detectable effect size.
The study's statistical power was designed to detect effects substantially smaller than the framing's ≥10% bar, but null results do not establish that effects below the threshold do not exist.
Absence-of-evidence arguments require specification of the minimum detectable effect size and acknowledgment that non-detection does not prove absence, particularly when volunteer bias may suppress effects.
Guess et al. (2023) recruited volunteers consenting to treatment assignment, introducing volunteer bias that may reduce or mask treatment effects relative to the full population.
Argument from Lack of Evidence (Negative Evidence)