2017
DOI: 10.1167/17.4.1
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Maximum likelihood difference scales represent perceptual magnitudes and predict appearance matches

Abstract: One central problem in perception research is to understand how internal experiences are linked to physical variables. Most commonly, this relationship is measured using the method of adjustment, but this has two shortcomings: The perceptual scales that relate physical and perceptual variables are not measured directly, and the method often requires perceptual comparisons between viewing conditions. To overcome these problems, we measured perceptual scales of surface lightness using maximum likelihood differen… Show more

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Cited by 11 publications
(22 citation statements)
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“…All statistical analyses were performed using the OpenSource software R [30]. The signal detection model underlying MLDS and the fitting procedure have been previously described [25][26][27]31,32]. In summary, given a set of p stimuli ordered along a physical continuum, triples or non-overlapping quadruples are sampled on each trial.…”
Section: Mldsmentioning
confidence: 99%
See 2 more Smart Citations
“…All statistical analyses were performed using the OpenSource software R [30]. The signal detection model underlying MLDS and the fitting procedure have been previously described [25][26][27]31,32]. In summary, given a set of p stimuli ordered along a physical continuum, triples or non-overlapping quadruples are sampled on each trial.…”
Section: Mldsmentioning
confidence: 99%
“…In practice, we fit the data using functions from the R package MLDS [26,27]. These functions implement the fitting procedure in terms of a generalized linear model with a binomial family and a probit link function [26,27,[31][32][33]. The obtained scales are unique up to addition of a constant or multiplication by a coefficient.…”
Section: Mldsmentioning
confidence: 99%
See 1 more Smart Citation
“…In practice, we fit the data using functions from the R package MLDS [26,27]. These functions implement the fitting procedure in terms of a generalized linear model with a binomial family [26,27,[31][32][33]. The obtained scales are unique up to addition of a constant or multiplication by a coefficient.…”
Section: Mldsmentioning
confidence: 99%
“…The representation of the MLDS response scale in terms of the signal detection parameter d is based on a parameterization that sets the judgment noise equal to unity on the response scale. How this measure of d relates to that obtained from discrimination experiments is an unsettled question [31,32] that perhaps can be answered by comparing MLDS response estimates directly with those from discrimination experiments.…”
Section: Mldsmentioning
confidence: 99%