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Identifying suboptimalities with factorial model comparison.

¹Center for Neural Science and Department of Psychology,New York University,New York,NY 10003.weijima@nyu.edu.

The Behavioral and Brain Sciences

|February 16, 2019

Summary

This summary is machine-generated.

This study introduces factorial model comparison to simultaneously test for multiple forms of perceptual suboptimality. This approach allows for a more comprehensive understanding of cognitive process models.

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Area of Science:

Cognitive Science
Perception Research
Psychological Modeling

Background:

Perceptual systems exhibit various forms of suboptimality.
Existing methods often struggle to assess multiple suboptimality types concurrently.
Comparing complex cognitive process models requires robust analytical frameworks.

Purpose of the Study:

To propose a novel methodology for testing multiple forms of perceptual suboptimality simultaneously.
To provide a general framework for comparing process models that may differ in multiple components.
To adapt principles from factorial experimental design for model comparison.

Main Methods:

Advocating for factorial model comparison as an analytical strategy.
Drawing analogies to factorial experimental design principles.
Applying this framework to the analysis of perceptual suboptimality.

Main Results:

Factorial model comparison offers a structured approach to evaluating complex models.
This method facilitates the simultaneous assessment of diverse suboptimality types.
The proposed approach enhances the rigor of comparing cognitive process models.

Conclusions:

Factorial model comparison is a powerful tool for understanding perceptual suboptimality.
This methodology provides a unified framework for model comparison in cognitive science.
The approach has broad implications for the study of human perception and cognition.