A Simplified Form of the Psychometric Function for the m -Alternative Forced Choice (m AFC) Method

2016 ◽  
Vol 31 (4) ◽  
pp. 360-368
Author(s):  
Jian Bi ◽  
Carla Kuesten
Keyword(s):  
Psychometric Function ◽  
Forced Choice ◽  
Simplified Form

Effects of Signal and Masker Uncertainty on Children’s Detection

1995 ◽  
Vol 38 (2) ◽  
pp. 503-511 ◽  
Author(s):  
Prudence Allen ◽  
Frederic Wightman
Keyword(s):  
Psychometric Function ◽  
Forced Choice ◽  
Preschool Age ◽  
Signal Frequency ◽  
Focused Attention ◽  
Random Frequency ◽  
Random Level

This paper reports the results of two experiments that examined the effects of signal and masker uncertainty on preschool-age children’s and adults’ detection of tonal signals in noise maskers. In Experiment 1 (signal uncertainty) the signal was randomly at 501 or 2818 Hz. The majority of the adult listeners showed a slight decrement in performance consistent with an ability to monitor both frequencies simultaneously. The majority of the children, however, showed no decrement in performance, suggesting that the children may not have focused attention at the signal frequency even when it was fixed. In Experiment 2 (masker uncertainty), random-frequency, random-level, tonal distracters were added to each interval of the 2 alternative-forced-choice (2afc) procedure. The effect of masker uncertainty was much larger than that of signal uncertainty. For most of the adult listeners and some of the children, the distracters produced higher thresholds (on average by 10 dB) and shallower psychometric function slopes. For most of the children, thresholds increased by 20 dB or more and psychometric functions were often nearly flat. This paper reports the results of two experiments that examined the effects of signal and masker uncertainty on preschool-age children's and adults' detection of tonal signals in noise maskers. In Experiment 1 (signal uncertainty) the signal was randomly at 501 or 2818 Hz. The majority of the adult listeners showed a slight decrement in performance consistent with an ability to monitor both frequencies simultaneously. The majority of the children, however, showed no decrement in performance, suggesting that the children may not have focused attention at the signal frequency even when it was fixed. In Experiment 2 (masker uncertainty), random-frequency, random-level, tonal distracters were added to each interval of the 2 alternative-forced-choice (2afc) procedure. The effect of masker uncertainty was much larger than that of signal uncertainty. For most of the adult listeners and some of the children, the distracters produced higher thresholds (on average by 10 dB) and shallower psychometric function slopes. For most of the children, thresholds increased by 20 dB or more and psychometric functions were often nearly flat.

Psychometric Functions for Children’s Detection of Tones in Noise

1994 ◽  
Vol 37 (1) ◽  
pp. 205-215 ◽  
Author(s):  
Prudence Allen ◽  
Frederic Wightman
Keyword(s):  
Psychometric Function ◽  
Forced Choice ◽  
Choice Task ◽  
Large Variability ◽  
Forced Choice Task ◽  
The Individual ◽  
Over Time

This article reports the results of an experiment that used a two-alternative forced-choice task to measure the ability of 3- to 5-year-old children to detect 501 Hz, 1000 Hz, and 2818 Hz sinusoids in noise. Psychometric functions were fit to each individual’s data, and thresholds (signal level required for 75% correct) were interpolated from the fitted functions. Results showed that, on average, the children’s thresholds were higher and the slopes of their psychometric functions were shallower than those of the adults. However, the between-subjects variability in the children’s data was large, and the performance of many individual children was not well described by group mean performance. One-third of the children produced thresholds that were elevated by an average of 10 dB but psychometric function slopes that were adult-like. Another one-third of the children produced thresholds that were elevated relative to those of the adults by an average of 20 dB and psychometric function slopes that were very shallow. The data from a smaller group of children showed large variability in psychometric function slope and threshold, and for a very few children performance was at chance regardless of the signal level. A replication of the study several months later showed that for most listeners the individual patterns of performance persisted over time.

scholarly journals Sampling Plans for Fitting the Psychometric Function

2005 ◽  
Vol 8 (2) ◽  
pp. 256-289 ◽  
Author(s):  
Miguel A. García-Pérez ◽  
Rocío Alcalá-Quintana
Keyword(s):  
Parameter Estimation ◽  
Psychometric Function ◽  
Estimation Method ◽  
Forced Choice ◽  
Estimation Methods ◽  
Parameter Estimates ◽  
Mathematical Form ◽  
Sampling Plans ◽  
Forced Choice Tasks ◽  
Choice Tasks

Research on estimation of a psychometric function Ψ has usually focused on comparing alternative algorithms to apply to the data, rarely addressing how best to gather the data themselves (i.e., what sampling plan best deploys the affordable number of trials). Simulation methods were used here to assess the performance of several sampling plans in yes–no and forced-choice tasks, including the QUEST method and several variants of up–down staircases and of the method of constant stimuli (MOCS). We also assessed the efficacy of four parameter estimation methods. Performance comparisons were based on analyses of usability (i.e., the percentage of times that a plan yields usable data for the estimation of all the parameters of Ψ) and of the resultant distributions of parameter estimates. Maximum likelihood turned out to be the best parameter estimation method. As for sampling plans, QUEST never exceeded 80% usability even when 1000 trials were administered and rendered accurate estimates of threshold but misestimated the remaining parameters. MOCS and up–down staircases yielded similar and acceptable usability (above 95% with 400–500 trials) and, although neither type of plan allowed estimating all parameters with optimal precision, each type appeared well suited to estimating a distinct subset of parameters. An analysis of the causes of this differential suitability allowed designing alternative sampling plans (all based on up–down staircases) for yes–no and forced-choice tasks. These alternative plans rendered near optimal distributions of estimates for all parameters. The results just described apply when the fitted Ψ has the same mathematical form as the actual Ψ generating the data; in case of form mismatch, all parameters except threshold were generally misestimated but the relative performance of all the sampling plans remained identical. Detailed practical recommendations are given.

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