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I'm a signal detection theory newbie. I have data with a classical SDT design: the participants can answer YES or NO to a question where the correct answer is YES or NO, depending on the presence or absence of a stimulus feature. I looked online for a script to calculate d', and found one which is confusing me.

What's confusing is that the criterion is calculated in two different ways. Does anybody have an idea why this is the case? These are the relevant lines of (matlab) code:

% Convert to Z scores zHit = norminv(proportion_of_hits) ; zFA = norminv(proportion_of_false_alarms) ; % Calculate d-prime dPrime = zHit - zFA ; % calculate BETA beta = exp((zFA^2 - zHit^2)/2); % calculate C C = -.5 * (zHit + zFA);

I'm interested in beta and C - how one interprets them, how they differ from each other, what a high/low score in each of the two means. And also, which is the one that is more likely to be understandable to a reader who knows SDT.

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I've been meaning to answer this for months now...In case you can beat me to it, here are some resources I found that seemed to have answers: exhibits A, B, and C. –  Nick Stauner Jul 2 at 1:41

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