Mitigating Bias in Evaluations

Last registered on May 14, 2025
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Pre-Trial

Trial Information

General Information

Title
Mitigating Bias in Evaluations
RCT ID
AEARCTR-0015968
Initial registration date
May 07, 2025

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
May 14, 2025, 10:32 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

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Primary Investigator

Name
Tong Wang
Affiliation
London Business School
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Other Primary Investigator(s)

PI Name
Kamalini Ramdas
PI Affiliation
London Business School
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PI Name
Monika Heller
PI Affiliation
University College London
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Additional Trial Information

Status
In development
Start date
2025-05-07
End date
2028-06-30
Keywords
Behavior, Education, Gender, Lab
Additional Keywords
Service Evaluation, Bias
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Ratings are essential for service providers to signal quality to customers, helping them make informed decisions. However, publishing prior ratings may inadvertently introduce bias in follow-up service evaluations. We explore the operational interventions to mitigate such prior ratings bias.
External Link(s)

Registration Citation

Citation
Heller, Monika, Kamalini Ramdas and Tong Wang. 2025. "Mitigating Bias in Evaluations." AEA RCT Registry. May 14. https://doi.org/10.1257/rct.15968-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2025-05-07
Intervention End Date
2028-06-30

Primary Outcomes

Primary Outcomes (end points)
Described in the pre-analysis plan.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This experiment investigates how different formats of rating displays influence follow-up service evaluations. Participants in the control group will not be exposed to any prior ratings, while those in the treatment group will view ratings presented in various formats. Further details can be found in the pre-analysis plan, titled "Ratings Display_PAP_May2025."
Experimental Design Details
Not available
Randomization Method
Randomization of the survey will be done via the randomizing function in Qualtrics.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
We plan to recruit 900 participants.
Sample size: planned number of observations
900 individuals.
Sample size (or number of clusters) by treatment arms
There are 150 participants per condition, and in total, six conditions. Details regarding random assignments are in the pre-analysis plan.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
London Business School
IRB Approval Date
2025-01-09
IRB Approval Number
REC1000
Analysis Plan

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