Studying how individuals compare two given quantitative stimuli, say d(1) and d(2), is a fundamental problem. One very common way to address it is through ratio estimation, that is to ask individuals not to give values to d(1) and d(2), but rather to give their estimates of the ratio p = d(1)/d(2). Several psychophysical theories (the best known being Stevens' power-law) claim that this ratio cannot be known directly and that there are cognitive distortions on the apprehension of the different quantities. These theories result in the so-called separable representations [Luce, R. D. (2002). A psychophysical theory of intensity proportions, joint presentations, and matches. Psychological Review, 109, 520-532; Narens, L. (1996). A theory of ratio magnitude estimation. Journal of Mathematical Psychology, 40, 109-788], which include Stevens' model as a special case. In this paper we propose a general statistical framework that allows for testing in a rigorous way whether the separable representation theory is grounded or not. We conclude in favor of it, but reject Stevens' model. As a byproduct, we provide estimates of the psychophysical functions of interest.
Measurement by Subjective Estimation: Testing for Separable Representations
SERI, RAFFAELLO
2008-01-01
Abstract
Studying how individuals compare two given quantitative stimuli, say d(1) and d(2), is a fundamental problem. One very common way to address it is through ratio estimation, that is to ask individuals not to give values to d(1) and d(2), but rather to give their estimates of the ratio p = d(1)/d(2). Several psychophysical theories (the best known being Stevens' power-law) claim that this ratio cannot be known directly and that there are cognitive distortions on the apprehension of the different quantities. These theories result in the so-called separable representations [Luce, R. D. (2002). A psychophysical theory of intensity proportions, joint presentations, and matches. Psychological Review, 109, 520-532; Narens, L. (1996). A theory of ratio magnitude estimation. Journal of Mathematical Psychology, 40, 109-788], which include Stevens' model as a special case. In this paper we propose a general statistical framework that allows for testing in a rigorous way whether the separable representation theory is grounded or not. We conclude in favor of it, but reject Stevens' model. As a byproduct, we provide estimates of the psychophysical functions of interest.
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