The reason mistaken identification rates increase when witnessing or testing conditions get worse is because witnesses lower their criterion for making an affirmative identification. Paper accepted at #JARMAC Thread. https://www.researchgate.net/publication/343404190_Why_do_Mistaken_Identification_Rates_Increase_When_Either_Witnessing_or_Testing_Conditions_get_Worse/stats

There are two SDT-based explanations for why mistaken identifications from eyewitness lineups increase under weak recognition conditions: the differentiation account and the decisional account.

According to differentiation account, when witnessing/testing conditions are degraded, innocent persons provide stronger match-to-memory compared to under more favorable conditions (the lure distribution shifts rightwards) leading to an increase in mistaken identification.

According to decisional account, the match-to-memory of innocent persons is unaffected by changes in witnessing/testing conditions; mistaken identifications increase because witnesses lower their criterion (decision criterion moves leftwards).

Across two, large-sample, experiments, I had participants provide subjective memory ratings for the best-matching lineup member. Critically, memory ratings for innocent persons were unaffected by variations in the quality of either witnessing (E1) or testing (E2) conditions.

In fact, In E2, I used the TOST procedure ( @lakens) and found that memory ratings were statistically equivalent under clear and degraded testing conditions. I powered to reject small effect |.2069|. Critically, the upper limit of CI was only approximately d = 0.05

Contrary to the decisional account, these experiments suggest that the reason mistaken identifications increase when witnessing/testing conditions get worse is because witnesses lower their criterion for making an affirmative identification!

Oh yeah, I also quoted George Box (1976, p.792): Since all models are wrong the scientist cannot obtain a ‘correct’ one by excessive elaboration. On the contrary following William of Occam she should seek an economical description of natural phenomena...

Just as the ability to devise simple but evocative models is the signature of a great scientist so overelaboration and overparameterization is often the mark of mediocrity."

Both experiments were preregistered. Data and R code for both experiments (and three small pilot experiments) are also available on OSF (link in article).