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Extracts the image random effects of a sad_fit() model: the shift, common to all raters and conditions, of the estimates of each image relative to what its actual severity predicts. Large absolute values flag images that are hard to assess, or whose actual severity may be wrong.

Usage

sad_images(fit)

Arguments

fit

An object returned by sad_fit().

Value

A tibble with image, actual, difficulty (percentage points for the gaussian family) and its conditional standard error se, ordered by absolute difficulty.