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Too Good to be True - Individual and Group Decision-Making with Correlated Signals
Last registered on August 31, 2020

Pre-Trial

Trial Information
General Information
Title
Too Good to be True - Individual and Group Decision-Making with Correlated Signals
RCT ID
AEARCTR-0006323
Initial registration date
August 23, 2020
Last updated
August 31, 2020 11:37 AM EDT
Location(s)

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Primary Investigator
Affiliation
University of Konstanz
Other Primary Investigator(s)
PI Affiliation
University of Konstanz
PI Affiliation
University of Nottingham
Additional Trial Information
Status
In development
Start date
2020-08-24
End date
2020-12-31
Secondary IDs
Abstract
We conduct an online experiment on individual and group decision-making with correlated signals. In every
round, either one decision-maker individually or three decision makers collectively make a decision
under uncertainty that can be right or wrong. Our experiment follows a 2 (group or individual) x 2 (with or without bias) x 2 (with or without correlation) between-subjects design.
Depending on the treatment, we expect different success probabilities and communication patterns.
External Link(s)
Registration Citation
Citation
Fehrler, Sebastian, Anna Hochleitner and Moritz Janas. 2020. "Too Good to be True - Individual and Group Decision-Making with Correlated Signals." AEA RCT Registry. August 31. https://doi.org/10.1257/rct.6323-1.0.
Experimental Details
Interventions
Intervention(s)
We conduct an online experiment. In every round, decision-makers have to make a decision (red or blue), either individually or collectively (in groups of three), depending on the treatment. If the correct decision is taken, i.e. if the decision equals the state of the world (red or blue), each player enjoys a positive payoff. A priori, each state is equally likely and signals (red or blue) are randomly drawn from an urn representing the state of the world. Our treatments vary the bias of the decision makers, the correlation structure of the signals and whether the decisions are made individually or collectively.


Intervention Start Date
2020-08-24
Intervention End Date
2020-09-30
Primary Outcomes
Primary Outcomes (end points)
Decision accuracy rate
Primary Outcomes (explanation)
Correct decisions (all decisions are binary and either correct or wrong)
Secondary Outcomes
Secondary Outcomes (end points)
Communication honesty
Secondary Outcomes (explanation)
Communicated signals can be either true or false
Experimental Design
Experimental Design
Our experiment follows a 2 (group or individual) x 2 (with or without bias) x 2 (with or without correlation) between-subjects design. For the cell Group-No Bias-Correlation, we run an additional treatment with a message option. Hence, 9 treatments will be conducted in total.
Experimental Design Details
Not available
Randomization Method
Subjects are randomly assigned to treatments by the Prolific software
Randomization Unit
Individuals
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
1900
Sample size: planned number of observations
1900
Sample size (or number of clusters) by treatment arms
100 for individual choice treatments
300 for group decision treatments
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
20 percentage points
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
German Association for Experimental Economic Research e.V.
IRB Approval Date
2020-08-23
IRB Approval Number
6aJqoedH
Analysis Plan

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