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At the end of the intervention, patients of the ID rated the organization of patient care more favourably than patients in the CD.
Thus, some between-group differences are significant at the post-intervention assessment: Patients in the ID rated "Organization of Physicians Caree" more positive than patients in the CD: t(df = 883) = 3.99, p < .01.01
Similar(58)
The diagonal line represents chance performance (where correct ID rate = false ID rate).
In other words, N26 monitors this fake ID rate.
Participants shown a sequential lineup had a correct ID rate of 0.50 and false ID rate of 0.17.
Integration of dystocia data with production data increased MGS ID rate from 58to73%3%.
You can try to keep the fake ID rate as low as possible.
In the lineup scenario, P(D|H1) is the HR (i.e., the correct ID rate) and P(D|H2) is the FAR (i.e., the false ID rate).
Instead, Procedure A would clearly be the one to use no matter what the filler ID rate and no ID rate happened to be for either procedure.
Thus, the DR (i.e., the likelihood ratio) is equal to the correct ID rate divided by the false ID rate (HR/FAR).
In their study, participants given a simultaneous lineup had a correct ID rate of 0.58 and a false ID rate of 0.43.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com