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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

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Measuring decision weights in recognition experiments with multiple response alternatives: comparing the correlation

Huanping Dai¹, Christophe Micheyl

¹Department of Speech, Language, and Hearing Sciences, University of Arizona, 1131 East 2nd Street, Tucson, Arizona 85721, USA. hdai@email.arizona.edu

The Journal of the Acoustical Society of America

|November 14, 2012

Summary

Psychophysical reverse-correlation methods reveal perceptual strategies. A correlation method is more efficient and simpler for multi-alternative tasks than multinomial logistic regression (MLR).

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Area of Science:

Cognitive psychology
Perception science
Psychophysics

Background:

Psychophysical reverse-correlation methods offer insights into perceptual representations and decision strategies.
Previous methods were limited to two-response categories.
New methods are needed for multi-alternative tasks.

Purpose of the Study:

Compare two methods for estimating decision weights in m-alternative tasks: a correlation method and multinomial logistic regression (MLR).
Evaluate the convergence and statistical efficiency of these methods.
Identify the most suitable method for analyzing decision strategies in complex perceptual tasks.

Main Methods:

Monte Carlo simulations were used to quantitatively evaluate the two methods.
The study compared estimated weighting patterns and their convergence to asymptotic values.
Statistical efficiency and interpretability of weight estimates were assessed.

Main Results:

The correlation method showed faster convergence to asymptotic values compared to MLR across various trial numbers.
MLR exhibited strong correlations between weight estimates for different stimulus components, complicating interpretation.
The correlation method demonstrated greater statistical efficiency and simpler analysis.

Conclusions:

The correlation method is a more advantageous tool for decision-making research in m-alternative experiments.
Its computational simplicity and established links to other psychophysical methods enhance its utility.
This method provides a more straightforward approach to uncovering decision strategies in complex perceptual tasks.