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Dprime and false alarm rates


In analysis of data from speech perception experiments using the AX
same-different roving model, the dprime is calculated using the
differencing model (McMillan and Creelman, 1991). Has anyone had the
problem of having false alarm rates that exceed the hit rate sometimes and
not being able to calculate dprime? How does one get around this? Is it
possible to do it, without compromising on the number of steps (currently
ten ) in the stimulus continuum? I am sure one suggestion might be that
the stimuli need to be redesigned. But the high false rates are seen in
discrimination despite the fact that in identification using the same
stimuli people have no trouble and are at ceiling for the endpoint

Also, I have seen a number of articles in literature that calculate the
percent/proportion correct for AX discrimination studies. I need some help
as to how this can be done. Is the percent correct calculated only for the
trials that use the different stimuli and the catch trials (with 2 same
stimuli)  discarded?

Thanks for any advice on this,