Evaluation of maximum-likelihood estimators in nonintensive auditory psychophysics

This is a brief report on the use of maximum-likelihood (ML) estimators in auditory psychophysics. Slope parameters of psychometric functions are characterized for three nonintensive auditory tasks: forced-choice discrimination of interaural time differences (Delta ITD), frequency (Delta f), and duration (Delta t). Using these slope estimates, the ML method is implemented and threshold estimates are obtained for the three tasks and compared with previously published data Delta ITD thresholds were additionally measured for human observers by means of two other psychophysical procedures: the constant-stimuli (CS) and the 2-down 1-up methods (Wetherill & Levitt, 1965). Standard errors were smallest for the ML method. Finally, simulations showed ML estimates to be more efficient than the CS and k-down 1-up procedures for k = 2 to 5. For up-down procedures, efficiency was highest for k values of 3 and 4. The entropy (Shannon, 1949) of ML estimates was the smallest of the simulated procedures, but poorer than ideal by 0.5 bits.