Bayesian Updating, Incentives, and Removal of Valence

Last registered on April 26, 2021

Pre-Trial

Trial Information

General Information

Title
Bayesian Updating, Incentives, and Removal of Valence
RCT ID
AEARCTR-0007561
Initial registration date
April 20, 2021
Last updated
April 26, 2021, 5:32 AM EDT

Locations

Primary Investigator

Affiliation
University of Zurich

Other Primary Investigator(s)

PI Affiliation
University of Zurich
PI Affiliation
University of Zurich
PI Affiliation
University of Zurich

Additional Trial Information

Status
In development
Start date
2021-04-27
End date
2021-09-30
Secondary IDs
Abstract
This preregistration describes an online experiment investigating a belief-updating task with various incentive levels while removing the valence of the information feedback. We describe the experimental design, the variables of interest, the hypotheses, and sample size. The experiment is conducted online via Prolific (recruiting) and Qualtrics (study).
External Link(s)

Registration Citation

Citation
Alós-Ferrer, Carlos et al. 2021. "Bayesian Updating, Incentives, and Removal of Valence." AEA RCT Registry. April 26. https://doi.org/10.1257/rct.7561-1.1
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2021-04-27
Intervention End Date
2021-09-30

Primary Outcomes

Primary Outcomes (end points)
Error Rates when State of the World is not revealed
Error Rates when State of the World is revealed
Primary Outcomes (explanation)
Individual relative frequency of errors in the second draw (choosing the urn not prescribed by Bayesian updating) when the left urn was selected during the first draw.
Individual relative frequency of errors in the second draw (choosing the urn not prescribed by Bayesian updating) when the right urn was selected during the first draw (used as exclusion criteria).

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This preregistration describes an online experiment investigating a belief-updating task with various incentive levels while removing the valence of the information feedback. We describe the experimental design, the variables of interest, the hypotheses, and sample size. The experiment is conducted online via Prolific (recruiting) and Qualtrics (study).
Experimental Design Details
Randomization Method
Randomization done by computer (Qualtrics).
Randomization Unit
Incentives randomized across individuals between 1 and 25 pence for a correct draw (integer values).
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
600 subjects
Sample size: planned number of observations
600 subjects
Sample size (or number of clusters) by treatment arms
approximately 24 observations for 25 different incentive levels.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

There are documents in this trial unavailable to the public. Use the button below to request access to this information.

Request Information
IRB

Institutional Review Boards (IRBs)

IRB Name
Human Subjects Committee of the Faculty of Economics, Business Administration, and Information Technology, University of Zurich
IRB Approval Date
2021-04-19
IRB Approval Number
OEC IRB # 2021-022

Post-Trial

Post Trial Information

Study Withdrawal

There are documents in this trial unavailable to the public. Use the button below to request access to this information.

Request Information

Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials