Abstract
Estimatingd′ from extreme false-alarm or hit proportions (p = 0 orp = 1) requires the use of a correction, because thez score of such proportions takes on infinite values. Two commonly used corrections are compared by using Monte-Carlo simulations. The first is the 1/(2N) rule for which an extreme proportion is corrected by this factor befored′ 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 resulted in less biased estimates ofd′ that always underestimated populationd′. The 1/(2N) rule, apart from being more biased, could either over- or underestimate populationd′.
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I would like to thank John Irwin for his valuable comments on the draft of this manuscript.
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Hautus, M.J. Corrections for extreme proportions and their biasing effects on estimated values ofd′. Behavior Research Methods, Instruments, & Computers 27, 46–51 (1995). https://doi.org/10.3758/BF03203619
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Keywords
- Cell Frequency
- CORWIN
- Maximum Likelihood Estima
- Linear Rule
- Sensory Evidence