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Related Experiment Video

Updated: Nov 17, 2025

Author Spotlight: A Novel Setup to Conduct Naturalistic Laboratory Experiments with Real Human Actors in Scenarios

Author Spotlight: A Novel Setup to Conduct Naturalistic Laboratory Experiments with Real Human Actors in Scenarios

Published on: August 4, 2023

A double-slit experiment with human subjects.

John Duffy¹, Ted Loch-Temzelides²

¹Department of Economics, University of California, Irvine, Irvine, California, United States of America.

|February 11, 2021

Summary

This summary is machine-generated.

Repeated attribute measurements in decision theory experiments show significant variance. Initial measurements influence subsequent responses, altering frequency distributions and challenging established decision models.

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Area of Science:

Cognitive Science
Decision Theory
Behavioral Economics

Background:

Decision theory often assumes stable attribute measurement.
Previous research has not fully explored the impact of sequential measurements on attribute perception.
Crowdsourcing platforms offer new avenues for large-scale behavioral experiments.

Purpose of the Study:

To investigate the impact of repeated attribute measurements on subject responses.
To compare experimental findings with predictions from standard decision theory.
To analyze how the sequence of measurements affects response variability and distribution.

Main Methods:

Conducting "double-slit" style experiments involving repeated attribute measurements.
Utilizing Amazon's Mechanical Turk for subject recruitment and data collection.
Analyzing response patterns and frequency distributions based on measurement order.

Main Results:

Subject responses varied significantly between initial and subsequent measurements of the same attribute.
The outcome of a sequel measurement was contingent on whether a prior measurement had occurred.
Absence of an initial measurement led to increased response variability and multimodal distributions, unlike cases with a preceding measurement.

Conclusions:

Sequential measurement order demonstrably influences attribute perception and response behavior.
Findings present a challenge to traditional decision theory models that may not account for measurement sequence effects.
The study highlights the importance of considering measurement context in behavioral research.