CORRECTIONS FOR EXTREME PROPORTIONS AND THEIR BIASING EFFECTS ON ESTIMATED VALUES OF D'

Estimating d' from extreme false-alarm or hit proportions (p = 0 or p = 1) requires the use of a correction, because the z score of such pro portions takes on infinite values. Two commonly used corrections are c ompared by using Monte-Carlo simulations. The first is the 1/(2N) rule for which an extreme proportion is corrected by this factor before d' is calculated. The second is the log-linear rule for which each cell frequency in the contingency table is increased by 0.5 irrespective of the contents of each cell. Results showed that the log-linear rule re sulted in less biased estimates of d' that always underestimated popul ation d'. The 1/(2N) rule, apart from being more biased, could either over- or underestimate population d'.